Patent Publication Number: US-11383721-B2

Title: System and method for responding to driver state

Description:
RELATED APPLICATIONS 
     This application is a continuation of U.S. application Ser. No. 16/385,108 filed on Apr. 16, 2019, and now published as U.S. Pub. No. 2019/0241190, which is expressly incorporated herein by reference. U.S. application Ser. No. 16/385,108 is a continuation application of U.S. application Ser. No. 15/720,489 filed on Sep. 29, 2017, and published as U.S. Pub. No. 2018/0022358, and now issued as U.S. Pat. No. 10,308,258, which is also expressly incorporated herein by reference. 
     U.S. application Ser. No. 15/720,489 is a continuation application of U.S. application Ser. No. 15/656,595 filed on Jul. 21, 2017, published as U.S. Pub. No. 2017/0341658, and now issued as U.S. patent Ser. No. 10/246,098 on Apr. 2, 2019, which is expressly incorporated by reference. U.S. application Ser. No. 15/656,595 is a continuation application of U.S. application Ser. No. 14/851,753 filed on Sep. 11, 2015, published as U.S. Pub. No. 2016/0001781, and now issued as U.S. Pat. No. 9,751,534 on Sep. 5, 2017, which is also expressly incorporated herein by reference. U.S. application Ser. No. 14/851,753 is a continuation application of International Application No. PCT/US15/37019 filed on Jun. 22, 2015, which is further expressly incorporated herein by reference. 
     International Application No. PCT/US15/37019 claims priority to U.S. Prov. Application Ser. No. 62/016,037 filed on Jun. 23, 2014 and U.S. Prov. Application Ser. No. 62/098,565 filed on Dec. 31, 2014, both of which are expressly incorporated herein by reference. In the United States, International Application No. PCT/US15/37019 is a continuation-in-part of U.S. application Ser. No. 14/573,778 filed on Dec. 17, 2014, published as U.S. Pub. No. 2015/0367858, and now issued as U.S. Pat. No. 9,352,751 on May 31, 2016, which claims priority to U.S. Prov. Application Ser. No. 62/016,020 filed on Jun. 23, 2014; a continuation-in-part of U.S. application Ser. No. 14/697,593 filed on Apr. 27, 2015, published as U.S. Pub. No. 2015/0229341, and now issued as U.S. Pat. No. 10,153,796 on Dec. 11, 2018, which is a continuation-in-part of U.S. application Ser. No. 13/858,038 filed on Apr. 6, 2013, published as U.S. Pub. No. 2014/0303899, and now issued as U.S. Pat. No. 9,272,689 on Mar. 1, 2016; a continuation-in-part of U.S. application Ser. No. 14/733,836 filed on Jun. 8, 2015, and issued as U.S. Pat. No. 9,475,521 on Oct. 25, 2016; a continuation-in-part of U.S. application Ser. No. 14/744,247 filed on Jun. 19, 2015, and issued as U.S. Pat. No. 9,475,389 on Oct. 25, 2016; a continuation-in-part of U.S. application Ser. No. 14/315,726 filed on Jun. 26, 2014, published as U.S. Pub. No. 2014/0309881, and issued as U.S. Pat. No. 9,505,402 on Nov. 29, 2016; and a continuation-in-part of U.S. application Ser. No. 14/461,530 filed on Aug. 18, 2014, published as U.S. Pub. No. 2014/0371984, and now issued as U.S. Pat. No. 9,440,646 on Sep. 13, 2016; all of the foregoing are expressly incorporated herein by reference. 
     Further, U.S. application Ser. No. 14/851,753 claims priority to U.S. Prov. Application Ser. No. 62/098,565 filed on Dec. 31, 2014, which again is expressly incorporated herein by reference. 
     Additionally, U.S. application Ser. No. 14/851,753 is a continuation-in-part of U.S. application Ser. No. 13/843,077 filed on Mar. 15, 2013, published as U.S. Pub. No. 2014/0276112, and now issued as U.S. Pat. No. 9,420,958 on Aug. 23, 2016; a continuation-in-part of U.S. application Ser. No. 14/074,710 filed on Nov. 7, 2013, published as U.S. Pub. No. 2015/0126818, and now issued as U.S. Pat. No. 9,398,875 on Jul. 26, 2016; a continuation-in-part of U.S. application Ser. No. 14/573,778 filed on Dec. 17, 2014, published as U.S. Pub. No. 2015/0367858, and now issued as U.S. Pat. No. 9,352,751 on May 31, 2016, which claims priority to U.S. Prov. Application Ser. No. 62/016,020 filed on Jun. 23, 2014; a continuation-in-part of U.S. application Ser. No. 14/697,593 filed on Apr. 27, 2015, published as U.S. Pub. No. 2015/0229341, and now issued as U.S. Pub. No. 10,153,796 on Dec. 11, 2018, which is a continuation-in-part of U.S. application Ser. No. 13/858,038 filed on Apr. 6, 2013, published as U.S. Pub. No. 2014/0303899, and now issued as U.S. Pat. No. 9,272,689 on Mar. 1, 2016; a continuation-in-part of U.S. application Ser. No. 14/733,836 filed on Jun. 8, 2015, and now issued as U.S. Pat. No. 9,475,521 on Oct. 25, 2016; and a continuation-in-part of U.S. application Ser. No. 14/744,247 filed on Jun. 19, 2015, and now issued as U.S. Pat. No. 9,475,389 on Oct. 25, 2016; all of the foregoing are expressly incorporated herein by reference. 
     Additionally, in the United States, International Application No. PCT/US15/37019, and thus this application, expressly incorporates herein by reference the following: U.S. application Ser. No. 13/030,637 filed on Feb. 18, 2011, published as U.S. Pub. No. 2012/0212353 on Aug. 23, 2012, and now issued as U.S. Pat. No. 8,698,639 on Apr. 15, 2014; U.S. application Ser. No. 13/843,194 filed on Mar. 15, 2013, published as U.S. Pub. No. 2013/0226408 on Aug. 29, 2013, and now issued as U.S. Pat. No. 9,292,471 on Mar. 22, 2016; U.S. application Ser. No. 13/843,249 filed on Mar. 15, 2013, published as U.S. Pub. No. 2013/0245886 on Sep. 19, 2013, and now issued as U.S. Pat. No. 9,296,382 on Mar. 29, 2016; U.S. application Ser. No. 13/195,675 filed on Aug. 1, 2011, published as U.S. Pub. No. 2013/0033382 on Feb. 7, 2013, and now issued as U.S. Pat. No. 8,941,499 on Jan. 27, 2015; U.S. application Ser. No. 13/023,323 filed on Feb. 8, 2011, and published as U.S. Pub. No. 2012/0202176 on Aug. 9, 2012; U.S. application Ser. No. 13/843,077 filed on Mar. 15, 2013, published as U.S. Pub. No. 2014/0276112 on Sep. 18, 2014, and now issued as U.S. Pat. No. 9,420,958 on Aug. 23, 2016; and U.S. application Ser. No. 14/074,710 filed on Nov. 7, 2013, published as U.S. Pub. No. 2015/0126818 on May 7, 2015, and now issued as U.S. Pat. No. 9,398,875 on Jul. 26, 2016; all of the foregoing again are expressly incorporated herein by reference. 
    
    
     BACKGROUND 
     The current embodiment relates to motor vehicles and in particular to a system and method for responding to driver state. 
     Motor vehicles are operated by drivers in various conditions. Lack of sleep, monotonous road conditions, use of items, or health-related conditions can increase the likelihood that a driver can become drowsy or inattentive while driving. Drowsy or inattentive drivers can have delayed reaction times. 
     SUMMARY 
     In one aspect, a method of controlling vehicle systems in a motor vehicle includes, receiving monitoring information from one or more monitoring systems, determining a plurality of driver states based on the monitoring information from the one or more monitoring systems and determining a combined driver state index based on the plurality of driver states. The method also includes modifying control of one or more vehicle systems based on the combined driver state index. 
     In another aspect, a method of controlling vehicle systems in a motor vehicle includes, receiving monitoring information from one or more monitoring systems, determining a first driver state and a second driver state based on the monitoring information from the one or more monitoring systems and determining a combined driver state index based on the first driver state and the second driver state. The method also includes modifying the control of one or more vehicle systems based on the combined driver state index. 
     In another aspect, a method of controlling vehicle systems in a motor vehicle includes, receiving monitoring information from one or more monitoring systems, determining a plurality of driver states based on the monitoring information from the one or more monitoring systems and determining a combined driver state index based on the plurality of driver states. The method also includes modifying control of one or more vehicle systems based on the combined driver state index. 
     In another aspect, a method of controlling vehicle systems in a motor vehicle includes, receiving monitoring information from one or more monitoring systems, determining a plurality of driver states based on the monitoring information from the one or more monitoring systems and determining a combined driver state index based on the plurality of driver states. The method also includes operating one or more vehicle system based on the combined driver state index. 
     In another aspect, a method of controlling vehicle systems in a motor vehicle includes, receiving monitoring information from a plurality of monitoring systems, determining a plurality of driver states based on the monitoring information from the plurality of monitoring systems and determining a combined driver state index based on the plurality of driver states. The method also includes operating one or more vehicle systems based on the combined driver state index. 
     Other systems, methods, features and advantages will be, or will become, apparent to one of ordinary skill in the art upon examination of the following figures and detailed description. It is intended that all such additional systems, methods, features and advantages be included within this description and this summary, be within the scope of the embodiments, and be protected by the following claims. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The embodiments can be better understood with reference to the following drawings and detailed description. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Moreover, in the figures, like reference numerals designate corresponding parts throughout the different views. 
         FIG. 1A  is a schematic view of an embodiment of various components and systems of a motor vehicle; 
         FIG. 1B  is a block diagram of an embodiment of the ECU of  FIG. 1A ; 
         FIG. 2  is a schematic view of an embodiment of various different vehicle systems; 
         FIG. 3  is a schematic view of an embodiment of various different monitoring systems; 
         FIG. 4  is a perspective view of an exemplary vehicle seat, including various sensors, and an associated seat belt that may be used to selectively couple an occupant to the seat; 
         FIG. 5  is a block diagram of an exemplary computing device that may be used with the seat and seat belt shown in  FIG. 4 ; 
         FIG. 6  is a schematic view of a heart rate monitoring system for determining changes in a driver state according to an exemplary embodiment; 
         FIG. 7  is a process flow diagram of a method for determining changes in a driver state that can be implemented with the system of  FIG. 6  according to an exemplary embodiment; 
         FIG. 8  is a schematic view of locations on an individual for measuring cardiac activity; 
         FIG. 9A  is a schematic representation of a cardiac waveform of an electrical signal representing cardiac activity; 
         FIG. 9B  is a schematic representation of a series of cardiac waveforms of  FIG. 9A ; 
         FIG. 10A  is a schematic representation of a cardiac waveform of an acoustic signal representing cardiac activity; 
         FIG. 10B  is a schematic representation of a series of cardiac waveforms of  FIG. 10A ; 
         FIG. 10C  is a schematic representation of a cardiac waveform of an optical signal representing cardiac activity; 
         FIG. 10D  is a schematic representation of a series of cardiac waveforms of  FIG. 10C ; 
         FIG. 11  is a schematic view of a system for biological signal analysis according to an exemplary embodiment; 
         FIG. 12  is a top schematic view of a multidimensional sensor array implemented in the system of  FIG. 11  according to an exemplary embodiment; 
         FIG. 13  is an orthographic view of the multidimensional sensor array of  FIG. 12 ; 
         FIG. 14  is a schematic view of the system of  FIG. 11  implemented in a vehicle according to an exemplary embodiment; 
         FIG. 15  is a schematic electric circuit diagram of the multidimensional sensor array of  FIG. 12 ; 
         FIG. 16A  is a side view of a motor vehicle according to an exemplary embodiment; 
         FIG. 16B  is an overhead view of the motor vehicle shown in  FIG. 16A  including exemplary head looking directions according to an exemplary embodiment; 
         FIG. 17  illustrates a head coordinate frame of a driver&#39;s head according to an exemplary embodiment; 
         FIG. 18  is an illustrative example of a touch steering wheel according to an exemplary embodiment; 
         FIG. 19  a schematic view of a vehicle having an information transfer rate system; 
         FIG. 20  is a schematic detailed view of an information transfer rate system of  FIG. 19  for determining an information transfer rate; 
         FIG. 21  is a process flow diagram of a method for determining an information transfer rate between a driver and a vehicle; 
         FIG. 22  is a schematic view of an illustrative computing environment for a computer system for personal identification in a vehicle according to an exemplary embodiment; 
         FIG. 23  is a process flow diagram of an exemplary method for identifying a vehicle occupant that can be implemented with the system of  FIG. 22 ; 
         FIG. 24A  is an embodiment of a process of controlling vehicle systems according to driver state; 
         FIG. 24B  is an embodiment of a process of controlling vehicle systems according to driver state similar to  FIG. 24  but including identification of a driver; 
         FIG. 25  is a table showing the impact of a response system on various vehicle systems; 
         FIG. 26  is an embodiment of a process of determining a level of distractedness and operating one or more vehicle systems; 
         FIG. 27  is an embodiment of a process for operating a vehicle system using a control parameter; 
         FIG. 28  is an embodiment of a relationship between driver state index and a control coefficient; 
         FIG. 29  is an embodiment of a calculation unit for determining a control parameter; 
         FIG. 30  is an embodiment of a relationship between driver state index and a vehicle system status; 
         FIG. 31  is a schematic view of an embodiment of a method of monitoring autonomic nervous system information to determine driver state; 
         FIG. 32  is an embodiment of a process of monitoring autonomic nervous system information to determine driver state; 
         FIG. 33  is a schematic view of an embodiment of a method of monitoring the eye movement of a driver to help determine driver state; 
         FIG. 34  is an embodiment of a process of monitoring eye movement of a driver to determine driver state; 
         FIG. 35  is a schematic view of an embodiment of a method of monitoring the head movement of a driver to determine driver state; 
         FIG. 36  is an embodiment of a process of monitoring the head movement of a driver to determine driver state; 
         FIG. 37  is a schematic view of an embodiment of a method of monitoring the distance between the driver&#39;s head and a headrest to determine driver state; 
         FIG. 38  is an embodiment of a process of monitoring the distance between the driver&#39;s head and a headrest to determine driver state; 
         FIG. 39  is a flow chart of a method of an embodiment of a process for detecting driver state by monitoring hand contact and position information with respect to a steering wheel; 
         FIG. 40  is a schematic view of an embodiment of a method of monitoring steering information to determine driver state; 
         FIG. 41  is an embodiment of a process of monitoring steering information to determine driver state; 
         FIG. 42  is a schematic view of an embodiment of a method of monitoring lane departure information to determine driver state; 
         FIG. 43  is an embodiment of a process of monitoring lane departure information to determine driver state; 
         FIG. 44  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on a combined driver state based on a plurality of driver states according to an exemplary embodiment; 
         FIG. 45  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on a combined driver state based on a plurality of driver state levels according to an exemplary embodiment; 
         FIG. 46  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle based on one or more combined driver states according to an exemplary embodiment; 
         FIG. 47  is a schematic view of how a combined driver state index can be used to retrieve a control coefficient according to an exemplary embodiment; 
         FIG. 48  is a schematic diagram illustrating an embodiment of a general relationship between the combined driver state index of the driver and a system status according to an exemplary embodiment; 
         FIG. 49  is a schematic view of an AND logic gate for combining a plurality of driver states (i.e., two driver states) according to an exemplary embodiment; 
         FIG. 50  is a schematic view of an AND logic gate for combining a plurality of driver states (i.e., three driver states) according to an exemplary embodiment; 
         FIG. 51  is a schematic view of an AND/OR logic gate for combining a plurality of driver states (i.e., three driver states) according to an exemplary embodiment; 
         FIG. 52  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on a combined driver state using thresholds according to an exemplary embodiment; 
         FIG. 53  is a schematic view of an AND logic gate for combining a plurality of driver states (i.e., three driver states) with thresholds according to an exemplary embodiment; 
         FIG. 54  is a flow chart of a method of an embodiment of a process for determining and/or modifying a threshold, control parameter, and/or control coefficient according to an exemplary embodiment; 
         FIG. 55  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on a combined driver state and confirmation of one or more driver states. according to an exemplary embodiment; 
         FIG. 56  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on a combined driver state and confirmation of one or more driver states with thresholds according to an exemplary embodiment; 
         FIG. 57  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on a combined driver state and confirmation of one or more driver states with thresholds according to another exemplary embodiment; 
         FIG. 58  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on a combined driver state and confirmation of one or more driver states (i.e., three driver states) with thresholds according to another exemplary embodiment; 
         FIG. 59  is a flow chart of a method of an embodiment of a process for confirming one or more driver states according to a priority level; 
         FIG. 60  is a network diagram of a multi-modal neural network system for controlling one or more vehicle systems according to an exemplary embodiment; 
         FIG. 61  is a flow chart of a process of controlling vehicle systems according to a combined driver state index according to another exemplary embodiment; 
         FIG. 62  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on one or more driver states and one or more vehicular states; 
         FIG. 63  is a schematic view of an embodiment of a method of modifying the operation of a power steering system when a driver is drowsy; 
         FIG. 64  is a schematic view of an embodiment of a method of modifying the operation of a power steering system when a driver is drowsy; 
         FIG. 65  is an embodiment of a process of controlling a power steering system when a driver is drowsy; 
         FIG. 66  is an embodiment of a detailed process for controlling power steering assistance in response to driver state; 
         FIG. 67  is a schematic view of an embodiment of a method of modifying the operation of a climate control system when a driver is drowsy; 
         FIG. 68  is a schematic view of an embodiment of a method of modifying the operation of a climate control system when a driver is drowsy; 
         FIG. 69  is an embodiment of a process of controlling a climate control system when a driver is drowsy; 
         FIG. 70  is a schematic view of an embodiment of various provisions that can be used to wake a drowsy driver; 
         FIG. 71  is a schematic view of an embodiment of a method of waking up a drowsy driver using tactile devices, visual devices and audio devices; 
         FIG. 72  is an embodiment of a process for waking up a drowsy driver using tactile devices, visual devices and audio devices; 
         FIG. 73  is a schematic view of an electronic pretensioning system for a motor vehicle; 
         FIG. 74  is a schematic view of a method of waking up a driver using the electronic pretensioning system of  FIG. 73 ; 
         FIG. 75  is an embodiment of a process of controlling an electronic pretensioning system according to driver state; 
         FIG. 76  is a schematic view of an embodiment of a method of operating an antilock braking system when a driver is fully awake; 
         FIG. 77  is a schematic view of an embodiment of a method of modifying the operation of the antilock braking system of  FIG. 76  when the driver is drowsy; 
         FIG. 78  is an embodiment of a process of modifying the operation of an antilock braking system according to driver state; 
         FIG. 79  is an embodiment of a process of modifying the operation of a brake system according to driver state; 
         FIG. 80  is an embodiment of a process of modifying the operation of a brake assist system according to driver state; 
         FIG. 81  is an embodiment of a process for controlling brake assist according to driver state; 
         FIG. 82  is an embodiment of a process for determining an activation coefficient for brake assist; 
         FIG. 83  is a schematic view of an embodiment of a motor vehicle operating with an electronic stability control system; 
         FIG. 84  is a schematic view of an embodiment of a method of modifying the operation of the electronic control assist system of  FIG. 83  when the driver is drowsy; 
         FIG. 85  is an embodiment of a process of modifying the operation of an electronic stability control system according to driver state; 
         FIG. 86  is an embodiment of a process for controlling an electronic stability control system in response to driver state; 
         FIG. 87  is an embodiment of a process for setting an activation threshold for an electronic stability control system; 
         FIG. 88  is a schematic view of an embodiment of a motor vehicle equipped with a collision warning system; 
         FIG. 89  is an embodiment of a process of modifying the control of a collision warning system according to driver state; 
         FIG. 90  is an embodiment of a detailed process of modifying the control of a collision warning system according to driver state; 
         FIG. 91  is a schematic view of an embodiment of a motor vehicle operating with an automatic cruise control system; 
         FIG. 92  is a schematic view of an embodiment of a method of modifying the control of the automatic cruise control system of  FIG. 91  according to driver state; 
         FIG. 93  is an embodiment of a process of modifying the control of an automatic cruise control system according to driver state; 
         FIG. 94  is an embodiment of a process of modifying operation of an automatic cruise control system in response to driver state; 
         FIG. 95  is an embodiment of a process of modifying a cruising speed of a vehicle according to driver state; 
         FIG. 96  is an embodiment of a process for controlling a low speed follow function associated with cruise control; 
         FIG. 97  is a schematic view of an embodiment of a motor vehicle operating with a lane departure warning system; 
         FIG. 98  is a schematic view of an embodiment of a method of modifying the control of the lane departure warning system of  FIG. 97  when the driver is drowsy; 
         FIG. 99  is an embodiment of a process of modifying the control of a lane departure warning system according to driver state; 
         FIG. 100  is an embodiment of a process of modifying the operation of a lane departure warning system in response to driver state; 
         FIG. 101  is an embodiment of a process for setting a road crossing threshold; 
         FIG. 102  is an embodiment of a process of modifying the operation of a lane keep assist system in response to driver state; 
         FIG. 103  is a schematic view of an embodiment in which a blind spot indicator system is active; 
         FIG. 104  is a schematic view of an embodiment in which a blind spot indicator system is active and a blind spot monitoring zone is increased in response to driver state; 
         FIG. 105  is an embodiment of a process of modifying the control of a blind spot indicator system; 
         FIG. 106  is an embodiment of a process for controlling a blind spot indicator system is response to driver state; 
         FIG. 107  is an embodiment of a process for determining a zone threshold for a blind spot indicator system; 
         FIG. 108  is an embodiment of a chart for selecting warning type according to driver state index; 
         FIG. 109  is a schematic view of an embodiment of a collision mitigation braking system in which no warning is provided when the driver is alert; 
         FIG. 110  is a schematic view of an embodiment of a collision mitigation braking system in which a warning is provided when the driver is drowsy; 
         FIG. 111  is a schematic view of an embodiment of a collision mitigation braking system in which no automatic seat belt pretensioning is provided when the driver is alert; 
         FIG. 112  is a schematic view of an embodiment of a collision mitigation braking system in which automatic seat belt pretensioning is provided when the driver is drowsy; 
         FIG. 113  is an embodiment of a process for controlling a collision mitigation braking system in response to driver state; 
         FIG. 114  is an embodiment of a process for setting time to collision thresholds; 
         FIG. 115  is an embodiment of a process for operating a collision mitigation braking system during a first warning stage; 
         FIG. 116  is an embodiment of a process for operating a collision mitigation braking system during a second warning stage; 
         FIG. 117  is an embodiment of a process for operating a navigation system according to driver monitoring; 
         FIG. 118  is a flow chart of a method of an embodiment of a process for modifying failure thresholds according to an exemplary embodiment; 
         FIG. 119  is a schematic diagram of an exemplary control signal and failure detection system thresholds; 
         FIG. 120  is a flow chart of a method of an embodiment of a process for modifying one or more vehicle systems based on detecting a failure and a driver state according to an exemplary embodiment; 
         FIG. 121  is a flow chart of a method of an embodiment of a process for modifying failure thresholds according to an exemplary embodiment; 
         FIG. 122A  is a schematic view of modifying a failure threshold according to the method of  FIG. 121  according to one embodiment; 
         FIG. 122B  is a schematic view of modifying a failure threshold according to the method of  FIG. 121  according to another embodiment; 
         FIG. 123  is a schematic view of modifying a failure threshold according to the method of  FIG. 121 ; 
         FIG. 124  is a schematic view of modifying a failure threshold according to the method of  FIG. 121 ; 
         FIG. 125  is a flow chart of an illustrative process of controlling vehicle systems according to combined driver state index using heart rate information and eye movement information according to an exemplary embodiment; 
         FIG. 126  is a flow chart of an illustrative process of controlling vehicle systems according to combined driver state index using heart rate information and steering information according to an exemplary embodiment; 
         FIG. 127  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle based on a combined driver state and confirmation of one or more driver states with thresholds according to an exemplary embodiment; 
         FIG. 128  is a flow chart of an illustrative process of controlling vehicle systems according to combined driver state index and a vehicular state according to an exemplary embodiment; 
         FIG. 129  is a schematic view of an embodiment of a response system including a central ECU; 
         FIG. 130  is schematic view of an embodiment of a first vehicle system and a second vehicle system communicating through a network; 
         FIG. 131  is an embodiment of a process for modifying the operation of one or more vehicle systems; 
         FIG. 132  is an embodiment of a process for controlling selected vehicle systems in response to driver state; 
         FIG. 133  is an embodiment of a process for determining a risk level associated with a potential hazard; 
         FIG. 134  is an embodiment of a process for modifying the control of two vehicle systems; 
         FIG. 135A  is a flow chart of a method of an embodiment of a process for modifying control of one or more vehicle systems; 
         FIG. 135B  is a flow chart of a method of an embodiment of a process for modifying control of one or more vehicle systems; 
         FIG. 136A  is a schematic view of an embodiment of a motor vehicle configured with a blind spot indicator system; 
         FIG. 136B  is a schematic view of an embodiment of a motor vehicle configured with a blind spot indicator system in which the vehicle is switching lanes; 
         FIG. 137A  is a schematic view of an embodiment of a motor vehicle configured with a blind spot indicator system in which the size of a blind spot warning zone is increased as the driver becomes drowsy; 
         FIG. 137B  is a schematic view of an embodiment of a motor vehicle configured with a blind spot indicator system and an electronic power steering system working in cooperation with the blind spot indicator system; 
         FIG. 138  is an embodiment of a process for controlling a blind spot indicator system in cooperation with an electronic power steering system; 
         FIG. 139  is a schematic view of an embodiment of a motor vehicle configured with a blind spot indicator system with cross-traffic alert and a brake control system working in cooperation with the blind spot indicator system; 
         FIG. 140  is an embodiment of a process for controlling a blind spot indicator system in cooperation with a brake control system; 
         FIG. 141  is a flow chart of a method of an embodiment of a process for modifying control of one or more vehicle systems including auto control according to an exemplary embodiment; 
         FIG. 142  is a flow chart of a method of an embodiment of a process for modifying control of one or more vehicle systems including auto control according to another exemplary embodiment; 
         FIG. 143A  is an exemplary look-up table for auto control of a low speed follow system based on a driver state according to an exemplary embodiment; 
         FIG. 143B  is an exemplary look-up table for auto control of a lane keep assist system based on a driver state according to an exemplary embodiment; 
         FIG. 143C  is an exemplary look-up table for auto control of an automatic cruise control system based on a driver state according to an exemplary embodiment; 
         FIG. 143D  is an exemplary look-up table for auto control of a visual device system based on a driver state according to an exemplary embodiment; 
         FIG. 144  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems including suppressing and/or restricting vehicle systems according to an exemplary embodiment; 
         FIG. 145  is a flow chart of a method of an embodiment of a process for controlling one or more vehicle systems including confirming a risk and/or hazard according to an exemplary embodiment; 
         FIG. 146  is a flow chart of a method for an embodiment of controlling a lane departure warning system according to an exemplary embodiment; 
         FIG. 147A  is a schematic view of controlling a lane departure warning system according to the method of  FIG. 146 ; 
         FIG. 147B  is a schematic view of controlling a lane departure warning system according to the method of  FIG. 146 ; 
         FIG. 148  is a flow chart of a method for an embodiment of controlling a blind spot indicator system according to an exemplary embodiment; 
         FIG. 149A  is a schematic view of controlling a blind spot indicator system according to the method of  FIG. 148 ; 
         FIG. 149B  is a schematic view of controlling a blind spot indicator system according to the method of  FIG. 148 ; 
         FIG. 150  is a flow chart of a method of an embodiment of a process for controlling a lane departure warning system and a blind spot indicator system according to an exemplary embodiment; 
         FIG. 151A  is a schematic view of controlling a lane departure warning system and a blind spot indicator system according to the method of  FIG. 150 ; 
         FIG. 151B  is a schematic view of controlling a lane departure warning system and a blind spot indicator system according to the method of  FIG. 150 ; 
         FIG. 152  is a flow chart of a method of an embodiment of a process for controlling an idle mode of an engine according to an exemplary embodiment; 
         FIG. 153  is a flow chart of a method of an embodiment of a process for controlling a brake hold of an electric parking brake system according to an exemplary embodiment; 
         FIG. 154  is a flow chart of a method of an embodiment of a process for controlling an electric parking brake system according to an exemplary embodiment; 
         FIG. 155A  is a flow chart of a method of an embodiment of a process for controlling vehicle systems according to hand contact transitions according to an exemplary embodiment; 
         FIG. 155B  is a flow chart of a method of an embodiment of a process for controlling a vehicle mode selector system based in part on hand contact transitions according to an exemplary embodiment; 
         FIG. 156  is a flow chart of a method of an embodiment of a process for controlling a power steering system according to an exemplary embodiment; 
         FIG. 157  is a flow chart of a method of an embodiment of a process for controlling a low speed follow system according to an exemplary embodiment; 
         FIG. 158A  is a schematic view of controlling a low speed follow system according to the method of  FIG. 157 ; 
         FIG. 158B  is a schematic view of controlling a low speed follow system according to the method of  FIG. 157 ; 
         FIG. 159  is a flow chart of a method of an embodiment of a process for controlling a low speed follow system according to another exemplary embodiment; 
         FIG. 160  is a flow chart of a method of an embodiment of a process for controlling an automatic cruise control system and a lane keep assist system according to an exemplary embodiment; 
         FIG. 161A  is a schematic view of controlling an automatic cruise control system and a lane keep assist system according to the method of  FIG. 160 ; 
         FIG. 161B  is a schematic view of controlling an automatic cruise control system and a lane keep assist system according to the method of  FIG. 160 ; 
         FIG. 161C  is a schematic view of controlling an automatic cruise control system and a lane keep assist system according to the method of  FIG. 160 ; 
         FIG. 162  is a flow chart of a method of an embodiment of a process for controlling an automatic cruise control system and a lane keep assist system according to another exemplary embodiment; 
         FIG. 163  is a flow chart of a method of an embodiment of a process for controlling an automatic cruise control system and a lane keep assist system according to further exemplary embodiment; 
         FIG. 164  is a flow chart of a method of an embodiment of a process for controlling an automatic cruise control system and a lane keep assist system according to another exemplary embodiment; 
         FIG. 165A  is a schematic view of controlling an automatic cruise control system and a lane keep assist system according to the method of  FIG. 164 ; and 
         FIG. 165B  is a schematic view of controlling an automatic cruise control system and a lane keep assist system according to the method of  FIG. 164 . 
     
    
    
     DETAILED DESCRIPTION 
     The following detailed description is intended to be exemplary and those of ordinary skill in the art will recognize that other embodiments and implementations are possible within the scope of the embodiments described herein. The exemplary embodiments are first described generally with a system overview including the components of a motor vehicle, exemplary vehicle systems and sensors, and monitoring systems and sensors. After the general description, systems and methods for assessing driver state and operational response including discussions of determining a driver state, determining one or more driver states, determining a combined driver state, and confirming driver states are presented. Exemplary implementations of detecting the driver states and exemplary operational responses of vehicle systems based on the driver states and/or combined driver state are also described. Further, embodiments related to various levels of operational response based on the driver state from no control to semi-autonomous and fully autonomous responses are also discussed. For organizational purposes, the description is structured into sections identified by headings, which are not intended to be limiting. 
     I. Overview 
     The detailed description and exemplary embodiments discussed herein describe systems and methods implementing state monitoring of a biological being (e.g., a human, an animal, a driver, a passenger). In particular, the detailed description and exemplary embodiments discussed herein refer to methods and systems with respect to a motor vehicle. For example,  FIG. 1A  illustrates a schematic view of an exemplary motor vehicle  100  and various components for implementing systems and methods for responding to driver state. In  FIG. 1A , the motor vehicle  100  is carrying a driver  102 . In the systems and methods described herein, the motor vehicle  100  and components of the motor vehicle  100  can provide state monitoring of the driver  102  and implement control based on the state monitoring. The term “driver” as used throughout this detailed description and in the claims can refer to any biological being where a state (e.g., a driver state) of the biological being is monitored. In some situations, the biological being is completing a task that requires state monitoring. Examples of the term “driver” can include, but are not limited to, a driver operating a vehicle, a vehicle occupant, a passenger in a vehicle, a patient, a security guard, an air traffic controller, an employee, a student, among others. It is understood that these systems and methods can also be implemented outside of a vehicle. Thus, the systems and methods described herein can be implemented in any location, situation, or device that requires or implements state monitoring of a biological being. For example, in any location, situation, or device for monitoring a person executing a task that requires a particular state. Examples include, but are not limited to, a hospital location, a home location, a job location, a personal medical device, a portable device, among others. 
     The “state” of the biological being or “driver state,” as used herein, refers to a measurement of a state of the biological being and/or a state of the environment surrounding (e.g., a vehicle) the biological being. A driver state or alternatively a “being state” can be one or more of alert, vigilant, drowsy, inattentive, distracted, stressed, intoxicated, other generally impaired states, other emotional states and/or general health states, among others. Throughout this specification, drowsiness and/or distractedness will be used as the example driver state being assessed. However, it is understood that any driver state could be determined and assessed, including but not limited to, drowsiness, attentiveness, distractedness, vigilance, impairedness, intoxication, stress, emotional states and/or general health states, among others. 
     A driver state can be quantified as a driver state level, a driver state index, among others. Further, one or more driver states can be used to determine a combined driver state level, a combined driver state index, among others. It is understood that the systems and methods for responding to driver state discussed herein can include determining and/or assessing one or more driver states based on information from the systems and sensors discussed herein. One or more driver states can be based on various types of information, for example, monitoring information, physiological information, behavioral information, vehicle information, among others. 
     As mentioned above, in addition to state monitoring, the systems and methods described herein can provide one or more responses by the motor vehicle  100  based on driver state. Thus, the assessment and adjustment discussed with the systems and methods herein can accommodate for the driver&#39;s health, slower reaction time, attention lapse and/or alertness. For example, in situations where a driver can be drowsy and/or distracted, the motor vehicle can include provisions for detecting that the driver is drowsy and/or distracted. Moreover, since drowsiness and/or distractedness can increase the likelihood of hazardous driving situations, the motor vehicle can include provisions for modifying one or more vehicle systems automatically to mitigate against hazardous driving situations. Accordingly, the systems and methods described herein can monitor and determine a state of a person and provide responses based on the state (e.g., control the motor vehicle and components of the motor vehicle based on the state). Further, in some embodiments discussed herein, the systems and methods can monitor and determine a state of a person and provide automatic control of the motor vehicle and components of the motor vehicle based on driver state. 
     II. Motor Vehicle Architecture Overview 
     Referring now to the drawings, wherein the showings are for purposes of illustrating one or more exemplary embodiments and not for purposes of limiting the same, an exemplary motor vehicle architecture for responding to driver state will be described with reference to  FIGS. 1A and 1B . For purposes of clarity, only some components of a motor vehicle are shown in the current embodiment. Furthermore, it will be understood that in other embodiments some of the components can be optional. As mentioned above,  FIG. 1A  illustrates a schematic view of an exemplary motor vehicle  100 , carrying a driver  102 , with various components of the motor vehicle for implementing systems and methods for responding to driver state. The term “motor vehicle” as used throughout this detailed description and in the claims refers to any moving vehicle that is capable of carrying one or more human occupants and is powered by any form of energy. The term “motor vehicle” includes, but is not limited to: cars, trucks, vans, minivans, SUVs, motorcycles, scooters, boats, personal watercraft, and aircraft. Further, the term “motor vehicle” can refer to an autonomous vehicle and/or self-driving vehicle powered by any form of energy. The autonomous vehicle may or may not carry one or more biological beings (e.g., humans, animals, etc.). 
     Generally, the motor vehicle  100  can be propelled by any power source. In some embodiments, the motor vehicle  100  can be configured as a hybrid vehicle that uses two or more power sources. In other embodiments, the motor vehicle  100  can use one or more engines. For example, in  FIG. 1A , the motor vehicle  100  includes a single power source, an engine  104 . The number of cylinders in the engine  104  could vary. In some cases, the engine  104  could include six cylinders. In some cases, the engine  104  could be a three cylinder, four cylinder, or eight cylinder engine. In still other cases, the engine  104  could have any other number of cylinders. 
     The term “engine” as used throughout the specification and claims refers to any device or machine that is capable of converting energy. In some cases, potential energy is converted to kinetic energy. For example, energy conversion can include a situation where the chemical potential energy of a fuel or fuel cell is converted into rotational kinetic energy or where electrical potential energy is converted into rotational kinetic energy. Engines can also include provisions for converting kinetic energy into potential energy. For example, some engines include regenerative braking systems where kinetic energy from a drive train is converted into potential energy. Engines can also include devices that convert solar or nuclear energy into another form of energy. Some examples of engines include, but are not limited to: internal combustion engines, electric motors, solar energy converters, turbines, nuclear power plants, and hybrid systems that combine two or more different types of energy conversion processes. It will be understood that in other embodiments, any other arrangements of the components illustrated herein can be used for powering the motor vehicle  100 . 
     Generally, the motor vehicle  100  can include provisions for communicating, and in some cases controlling, the various components associated with the engine  104  and/or other systems of the motor vehicle  100 . In some embodiments, the motor vehicle  100  can include a computer or similar device. In the current embodiment, the motor vehicle  100  can include an electronic control unit  106 , hereby referred to as the ECU  106 . In one embodiment, the ECU  106  can be configured to communicate with, and/or control, various components of the motor vehicle  100 . 
     Referring now to  FIG. 1B , an exemplary block diagram of the ECU  106  in a connected vehicle environment according to one embodiment is shown. Generally, the ECU  106  can include a microprocessor, RAM, ROM, and software all serving to monitor and supervise various parameters of the engine  104 , as well as other components or systems of the motor vehicle  100 . For example, the ECU  106  is capable of receiving signals from numerous sensors, devices, and systems located in the engine  104 . The output of various devices is sent to the ECU  106  where the device signals can be stored in an electronic storage, such as RAM. Both current and electronically stored signals can be processed by a central processing unit (CPU, processor) in accordance with software stored in an electronic memory, such as ROM. 
     As illustrated in the embodiment shown in  FIG. 1B , the ECU  106  includes a processor  108 , a memory  110 , a disk  112 , and a communication interface  114 . The processor  108  processes signals and performs general computing and arithmetic functions. Signals processed by the processor can include digital signals, data signals, computer instructions, processor instructions, messages, a bit, a bit stream, or other means that can be received, transmitted and/or detected. Generally, the processor can be a variety of various processors including multiple single and multicore processors and co-processors and other multiple single and multicore processor and co-processor architectures. The processor, in some embodiments, can include various modules to execute various functions. 
     The memory  110  can include volatile memory and/or non-volatile memory. Non-volatile memory can include, for example, ROM (read only memory), PROM (programmable read only memory), EPROM (erasable PROM), and EEPROM (electrically erasable PROM). Volatile memory can include, for example, RAM (random access memory), synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), and direct RAM bus RAM (DRRAM). The memory can store an operating system that controls or allocates resources of the ECU  106 . 
     Further, in some embodiments, the memory  110  can store and facilitate execution (e.g., by the processor  108 ) of various software modules  116 . The modules, as described herein, can include non-transitory computer readable medium that stores instructions, instructions in execution on a machine, hardware, firmware, software in execution on a machine, and/or combinations of each to perform a function(s) or an action(s), and/or to cause a function or action from another module, method, and/or system. A module may also include logic, a software controlled microprocessor, a discrete logic circuit, an analog circuit, a digital circuit, a programmed logic device, a memory device containing executing instructions, logic gates, a combination of gates, and/or other circuit components. Multiple modules may be combined into one module and single modules may be distributed among multiple modules. It is understood that in other embodiments, the software modules  116 , could be stored at the processor  108  and/or the disk  112 . 
     The disk  112  can be, for example, a magnetic disk drive, a solid state disk drive, a floppy disk drive, a tape drive, a Zip drive, a flash memory card, and/or a memory stick. Furthermore, the disk can be a CD-ROM (compact disk ROM), a CD recordable drive (CD-R drive), a CD rewritable drive (CD-RW drive), and/or a digital video ROM drive (DVD ROM). The disk can store an operating system that controls or allocates resources of the ECU  106 . 
     The communication interface  114  provides software and hardware to facilitate data input and output between the components of the ECU  106  and other components, networks and data sources. The processor  108 , the memory  110 , the disk  112 , and the communication interface  114  can each be operable connected for computer communication via a data bus  118 . The data bus  118  refers to an interconnected architecture that is operably connected to other computer components inside a computer or between computers. The bus can transfer data between the computer components. The bus can be a memory bus, a memory controller, a peripheral bus, an external bus, a crossbar switch, and/or a local bus, among others. The bus can also be a vehicle bus that interconnects components inside a vehicle (e.g., including vehicle systems and sensors) using protocols such as Media Oriented Systems Transport (MOST), Controller Area network (CAN), Local Interconnect Network (LIN), among others. 
     As mention above, the communication interface  114  can facilitate a connected environment for the motor vehicle  100 . Thus, the communication interface  114  facilitates the input and output of information to the ECU  106 , other components of the motor vehicle  100  and other network devices via computer communication in a network environment. The computer communication can include, but is not limited to, a network transfer, a file transfer, a data transfer, an applet transfer, a HTTP transfer, and so on. The computer communication can occur across, for example, logical connections, a wireless system (e.g., IEEE 802.11), an Ethernet system (e.g., IEEE 802.3), a token ring system (e.g., IEEE 802.5), a local area network (LAN), a wide area network (WAN), a point-to-point system, a circuit switching system, a packet switching system, among others. 
     For example, in  FIG. 1B , the communication interface  114  can facilitate an operable connection for computer communication to a network  120 . This connection can be implemented in various ways, for example, through a portable device  122 , a cellular tower  124 , a vehicle to vehicle ad-hoc network (not shown), an in-vehicle network (not shown), and other wired and wireless technologies, among others. Accordingly, the motor vehicle  100  can transmit data to and receive data from external sources, for example, the network  120  and the portable device  122 . 
     In addition to the communication interface  114 , the ECU  106  can include a number of ports, shown in  FIG. 1A , that facilitate the input and output of information and power. The term “port” as used throughout this detailed description and in the claims refers to any interface or shared boundary between two conductors. In some cases, ports can facilitate the insertion and removal of conductors. Examples of these types of ports include mechanical connectors. In other cases, ports are interfaces that generally do not provide easy insertion or removal. Examples of these types of ports include soldering or electric traces on circuit boards. In still other cases, ports can facilitate wireless connections. 
     The ports facilitate the input and output of information to the ECU  106 , other components of the motor vehicle  100  and other network devices via computer communication in a network environment. The computer communication can include, but is not limited to, a network transfer, a file transfer, a data transfer, an applet transfer, a HTTP transfer, and so on. The computer communication can occur across, for example, logical connections, a wireless system (e.g., IEEE 802.11), an Ethernet system (e.g., IEEE 802.3), a token ring system (e.g., IEEE 802.5), a local area network (LAN), a wide area network (WAN), a point-to-point system, a circuit switching system, a packet switching system, among others. The ports along with the data transfer between the ports and different vehicle systems will described in more detail herein. 
     As will be discussed in further detail throughout the detailed description, the ports and provisions associated with the ECU  106  are optional. Some embodiments can include a given port or provision, while others can exclude it. The detailed description discloses many of the possible ports and provisions that can be used, however, it should be kept in mind that not every port or provision must be used or included in a given embodiment. It is understood that components of the motor vehicle  100  and the ECU  106 , as well as the components of other systems, hardware architectures and software architectures discussed herein, may be combined, omitted or organized into different architecture for various embodiments. 
     III. Systems and Sensors 
     As mentioned above, one or more driver states can be assessed based on various types of information. Different systems and sensors can be used to gather and/or analyze this information. Generally, sensors discussed herein sense and measure a stimulus (e.g., a signal, a property, a measurement, a quantity) associated with the motor vehicle  100 , a vehicle system and/or component, the environment of the motor vehicle  100 , and/or a biological being (e.g., the driver  102 ). The sensors can generate a data stream and/or a signal representing the stimulus, analyze the signal and/or transmit the signal to another component, for example the ECU  106 . In some embodiments, the sensors are part of vehicle systems and/or monitoring systems, which will be discussed herein. 
     The sensors discussed herein can include one sensor, more than one sensor, groups of sensors, and can be part of larger sensing systems, for example, monitoring systems. It is understood that the sensors can be in various configurations and can include different types of sensors, for example, electric current/potential sensors (e.g., proximity, inductive, capacitive, electrostatic), acoustic sensors, subsonic, sonic, and ultrasonic sensors, vibration sensors (e.g., piezoelectric) visual sensors, imaging sensors, thermal sensors, temperature sensors, pressure sensors, photoelectric sensors, among others. 
     Exemplary vehicle systems, monitoring systems, sensors and sensor analysis will now be described in detail. It is understood that the vehicle systems, monitoring systems, sensors, and sensor analysis described herein are exemplary in nature and other systems and sensors can be implemented with the methods and systems for assessing one or more driver states and controlling one or more vehicle systems. 
     A. Vehicle Systems and Sensors 
     Referring again to  FIG. 1A , the motor vehicle  100 , the engine  104  and/or the ECU  106  can facilitate information transfer between components of the motor vehicle  100  and/or can facilitate control of the components of motor vehicle  100 . For example, the components of the motor vehicle  100  can include vehicle systems and vehicle sensors. As shown in the embodiments of  FIG. 1A  and  FIG. 2 , the motor vehicle  100  can include various systems, including vehicle systems  126 . The vehicle systems  126  can include, but are not limited to, any automatic or manual systems that can be used to enhance the vehicle, driving, and/or safety. The motor vehicle  100  and/or the vehicle systems  126  can include one or more vehicle sensors for sensing and measuring a stimulus (e.g., a signal, a property, a measurement, a quantity) associated with the motor vehicle  100  and/or a particular vehicle system. In some embodiments, the ECU  106  can communicate and obtain data representing the stimulus from the vehicle systems  126  and/or the one or more vehicle sensors via, for example, a port  128 . The data can be vehicle information and/or the ECU  106  can process the data into vehicle information and/or process the vehicle information further. Thus, the ECU  106  can communicate and obtain vehicle information from the motor vehicle  100 , the vehicle systems  126  themselves, one or more vehicle sensors associated with the vehicle systems  126 , or other vehicle sensors, for example, cameras, external radar and laser sensors, among others. 
     Vehicle information includes information related to the motor vehicle  100  of  FIG. 1A  and/or the vehicle systems  126 , including those vehicle systems listed in  FIG. 2 . Specifically, vehicle information can include vehicle and/or vehicle system conditions, states, statuses, behaviors, and information about the external environment of the vehicle (e.g., other vehicles, pedestrians, objects, road conditions, weather conditions). Exemplary vehicle information includes, but is not limited to, acceleration information, velocity information, steering information, lane departure information, blind spot monitoring information, braking information, collision warning information, navigation information, collision mitigation information and cruise control information. 
     It is understood that the vehicle sensors can include, but are not limited to, vehicle system sensors of the vehicle systems  126  and other vehicle sensors associated with the motor vehicle  100 . For example, other vehicle sensors can include cameras mounted to the interior or exterior of the vehicle, radar and laser sensors mounted to the exterior of the vehicle, external cameras, radar and laser sensors (e.g., on other vehicles in a vehicle-to-vehicle network, street cameras, surveillance cameras). The sensors can be any type of sensor, for example, acoustic, electric, environmental, optical, imaging, light, pressure, force, thermal, temperature, proximity, among others. 
     In some embodiments, the ECU  106  can include provisions for communicating and/or controlling various systems and/or functions associated with the engine  104 . In one embodiment, the ECU  106  can include a port  130  for receiving various kinds of steering information. In some cases, the ECU  106  can communicate with an electronic power steering system  132 , also referred to as an EPS  132 , through the port  130 . The EPS  132  can comprise various components and devices utilized for providing steering assistance. In some cases, for example, the EPS  132  can include an assist motor as well as other provisions for providing steering assistance to a driver. In addition, the EPS  132  could be associated with various sensors including torque sensors, steering angle sensors as well as other kinds of sensors. Examples of electronic power steering systems are disclosed in Kobayashi, U.S. Pat. No. 7,497,471, filed Feb. 27, 2006 and Kobayashi, U.S. Pat. No. 7,497,299, filed Feb. 27, 2006, the entirety of both being hereby incorporated by reference. 
     In some embodiments, the ECU  106  can include provisions for communicating and/or controlling various systems associated with a touch steering wheel. The ECU  106  can communicate with the various systems associated with a touch steering wheel  134  via the port  130  and/or the EPS  132 . In the embodiments described herein, the touch steering wheel  134  can also be referred to as a touch steering wheel system  134 . The touch steering wheel system  134  can include various components and devices utilized for providing information about the contact and location of the driver&#39;s hands with respect to the touch steering wheel  134 . More specifically, the touch steering wheel  134  can include sensors (e.g., capacitive sensors, electrodes) mounted in or on the touch steering wheel  134 . The sensors are configured to measure contact of the hands of the driver with the touch steering wheel  134  and a location of the contact (e.g., behavioral information). It is understood that in some embodiments, the touch steering wheel  134  can provide contact information of other appendages of the driver with the touch steering wheel  134 , for example, wrists, elbows, shoulders, knees, and arms, among others. 
     In some embodiments, the sensors are located on the front and back of the touch steering wheel  134 . Accordingly, the sensors can determine if the driver&#39;s hands are in contact with the front and/or back of the touch steering wheel  134  (e.g., gripped and wrapped around the steering wheel). In further embodiments, the touch steering wheel system  134  can measure the force and/or pressure of the contact of the hands on the touch steering wheel  134 . In still further embodiments, the touch steering wheel system  134  can provide information and/or monitor movement of hands on the touch steering wheel  134 . For example, the touch steering wheel system  134  can provide information on a transition of hand movements or a transition in the number of hands in contact with the touch steering wheel  134  (e.g., two hands on the touch steering wheel  134  to one hand on the touch steering wheel  134 ; one hand on the touch steering wheel  134  to two hands on the touch steering wheel  134 ). In some embodiments, a time component can be provided with the transition in hand contact, for example, a time period between the switch from two hands on the touch steering wheel  134  to one hand on the touch steering wheel  134 . The information provided by the touch steering wheel system  134  about contact with the touch steering wheel  134  can be referred to herein as hand contact information. 
     In some embodiments, the touch steering wheel system  134  can include sensors to measure a biological parameter of the driver of the vehicle (e.g., physiological information). For example, biological parameters can include heart rate, skin capacitance, and/or skin temperature. The sensors can include, for example, one or more bio-monitoring sensors  180 . In another embodiment, the touch steering wheel  134  can provide information for actuating devices and/or functions of vehicle systems. For example, the sensors of the touch steering wheel system  134  can function as a switch wherein the contact of the hands of the driver and the location of the contact are associated with actuating a device and/or a vehicle function of the vehicle. In still a further embodiment, the touch steering wheel system  134  can present information to the driver. For example, the touch steering wheel  134  can include one or more light elements and/or visual devices to provide information and/or indications to the driver. The light elements and/or visual devices can provide warning signals and/or information related to one or more vehicle systems. As an illustrative example, the warning signals can be associated with different visual cues (e.g., colors, patterns). The visual cues can be a function of the warning signals and/or driver state. Examples of touch steering wheel systems are disclosed in U.S. application Ser. No. 14/744,247 filed on Jun. 19, 2015, the entirety being hereby incorporated by reference. 
     In some embodiments, the ECU  106  can include provisions for communicating with and/or controlling various visual devices. Visual devices include any devices that are capable of displaying information in a visual manner. These devices can include lights (such as dashboard lights, cabin lights, etc.), visual indicators, video screens (such as a navigation screen or touch screen), as well as any other visual devices. In one embodiment, the ECU  106  includes a port  138  for communicating with visual devices  140 . Further, in one embodiment, the visual devices  140  can include light elements and/or visual devices integrated with other vehicle systems, for example the touch steering wheel system  134 . 
     In some embodiments, the ECU  106  can include provisions for communicating with and/or controlling various audio devices. Audio devices include any devices that are capable of providing information in an audible manner. These devices can include speakers as well as any of the systems associated with speakers such as radios, DVD players, BD players, CD players, cassette players, MP3 players, smartphones, portable devices, navigation systems as well as any other systems that provide audio information. In one embodiment, the ECU  106  can include a port  142  for communicating with audio devices  144 . Moreover, the audio devices  144  could be speakers in some cases, while in other cases the audio devices  144  could include any systems that are capable of providing audio information to speakers that can be heard by a driver. 
     In some embodiments, the ECU  106  can include provisions for communicating with and/or controlling various tactile devices. The term “tactile device” as used throughout this detailed description and in the claims refers to any device that is capable of delivering tactile stimulation to a driver or occupant. For example, a tactile device can include any device that vibrates or otherwise moves in a manner that can be sensed by a driver. Tactile devices could be disposed in any portion of a vehicle. In some cases, a tactile device could be located in a steering wheel (e.g., the touch steering wheel  134 ) to provide tactile feedback to a driver. In other cases, a tactile device could be located in a vehicle seat (e.g., the vehicle seat  168 ), to provide tactile feedback or to help relax a driver. In one embodiment, the ECU  106  can include a port  146  for communicating and/or controlling tactile devices  148 . 
     In some embodiments, the ECU  106  can include provisions for receiving input from a user. For example, in some embodiments, the ECU  106  can include a port  150  for receiving information from a user input device  152 . In some cases, the user input device  152  could comprise one or more buttons, switches, a touch screen, touch pad, dial, pointer or any other type of input device. For example, in one embodiment, the user input device  152  could be a keyboard or keypad. In another embodiment, the user input device  152  could be a touch screen. In one embodiment, the user input device  152  could be an ON/OFF switch. In another embodiment, the user input device  152  can include the touch steering wheel system  134 . The user input device  152  can receive user input from the touch steering wheel system  134 . In some cases, the user input device  152  could be used to turn ON or OFF any driver state monitoring devices associated with the vehicle or driver. For example, in an embodiment where an optical sensor is used to detect driver state information, the user input device  152  could be used to switch this type of monitoring ON or OFF. In embodiments using multiple monitoring devices, the user input device  152  can be used to simultaneously turn ON or OFF all the different types of monitoring associated with these monitoring devices. In other embodiments, the user input device  152  can be used to selectively turn ON or OFF some monitoring devices but not others. In further embodiments, the user input device  152  can be associated with vehicle systems  126  to selective turn ON or OFF some vehicle systems  126 . 
     In some embodiments, the visual devices, audio devices, tactile devices and/or input devices could be part of a larger infotainment system  154 . In  FIG. 1A , the ECU can receive information from the infotainment system  154  via a port  156 . The infotainment system  154  may include a telematics control unit (TCU) (not shown) to allow a connection to the Internet for receiving various media content. In one embodiment, the TCU can facilitate connection to a cellular network (e.g., 3G, 4G, LTE). For example, the TCU can facilitate connection to the network  120 , the portable device  122  and/or the cellular tower  124 , similar to the communication interface  114 . In a further embodiment, the TCU can include dedicated short-range communications (DSRC) providing one-way or two-way short-range to medium-range wireless communication to the vehicle. Other systems and technologies can be used to allow connection to the Internet (e.g., network  120 ) and communicate data between the Internet, other vehicles and other devices. For example, other vehicular communication systems (e.g., networks with communication nodes between vehicles, other vehicles, roadside units and other devices), vehicle-to-vehicle (V2V) networks allowing communication between vehicles, and other ad-hoc networks. It is understood that the communication interface  114  shown in  FIG. 1B  could facilitate the communication described above between the infotainment system  154  and other networks and devices. 
     In some embodiments, the ECU  106  can include ports for communicating with and/or controlling various different engine components or systems. Examples of different engine components or systems include, but are not limited to: fuel injectors, spark plugs, electronically controlled valves, a throttle, as well as other systems or components utilized for the operation of the engine  104 . Moreover, the ECU  106  could include additional ports for communicating with various other systems, sensors or components of the motor vehicle  100 . As an example, in some cases, the ECU  106  could be in electrical communication with various sensors for detecting various operating parameters of the motor vehicle  100 , including but not limited to: vehicle speed, vehicle acceleration, accelerator pedal input, accelerator pedal input pressure/rate, vehicle location, yaw rate, lateral g forces, fuel level, fuel composition, various diagnostic parameters as well as any other vehicle operating parameters and/or environmental parameters (such as ambient temperature, pressure, elevation, etc.). 
     In one embodiment, the ECU  106  can include a port  160  for receiving information from one or more optical sensing devices, such as an optical sensing device  162 . The optical sensing device  162  could be any kind of optical device including a digital camera, video camera, infrared sensor, laser sensor, as well as any other device capable of detecting optical information. In one embodiment, the optical sensing device  162  can be a video camera. In another embodiment, the optical sensing device  162  can be one or more cameras or optical tracking systems. In addition, in some cases, the ECU  106  could include a port  164  for communicating with a thermal sensing device  166 . The thermal sensing device  166  can be configured to detect thermal information about the state of a driver and/or thermal information about the vehicle environment. In some cases, the optical sensing device  162  and the thermal sensing device  166  could be combined into a single sensor. As will be discussed in further detail herein, the optical sensing device  162  and the thermal sensing device  166  can be used to sense and detect physiological and/or behavioral information about the driver  102 . 
     As discussed herein, the motor vehicle  100  can include one or more sensors to ascertain, retrieve and/or obtain information about a driver, and more particularly, a driver state. In  FIG. 1A , the driver  102  is seated in a vehicle seat  168 . The vehicle seat  168  can include a lower support  170  and a seat back support  172  that extends generally upward from the lower support  170 . Further, the vehicle seat  168  can include a headrest  174  that extends generally upward from the seat back support  172 . In some embodiments, the vehicle seat  168  can also include a seat belt  176 . In  FIG. 1A , the seat belt  176  is generally shown with a sash belt portion, however, the seat belt  176  can also include a lap belt portion (not shown). It is understood that other configurations of a vehicle seat can be implemented. 
     The motor vehicle  100  can include one or more bio-monitoring sensors, for example, positioned and/or located in the vehicle seat  168 . In  FIG. 1A , the ECU  106  can include a port  178  for receiving information from a bio-monitoring sensor  180  located in the seat back support  172 . In a further embodiment, the ECU  106  can include a port  182  for receiving information from a proximity sensor  184  located in the headrest  174 . In some embodiments, the bio-monitoring sensor  180  can be used to sense, receive, and monitor physiological information about the driver  102 , for example, heart rate information. In some embodiments, the proximity sensor  184  can be used to sense, receive and monitor behavioral information about the driver  102 , for example, a distance between the headrest  174  and a head  186  of the driver  102 . The bio-monitoring sensor  180  and the proximity sensor  184  will be described in more detail herein for sensing and monitoring physiological and/or behavioral information about the driver  102 . 
     In some embodiments, the ECU  106  can include provisions for communicating with and/or controlling various other different vehicle systems. Vehicle systems include any automatic or manual systems that can be used to enhance the driving experience and/or enhance safety. As mentioned above, in one embodiment, the ECU  106  can communicate and/or control vehicle systems  126  via the port  128 . For purposes of illustration, a single port is shown in the current embodiment for communicating with the vehicle systems  126 . However, it will be understood that in some embodiments, more than one port can be used. For example, in some cases, a separate port can be used for communicating with each separate vehicle system of the vehicle systems  126 . Moreover, in embodiments where the ECU  106  comprises part of the vehicle system, the ECU  106  can include additional ports for communicating with and/or controlling various different components or devices of a vehicle system. Further, in some embodiments discussed herein, a response system can receive information about a state of the driver  102  and automatically adjust the operation of the vehicle systems  126 . In these embodiments, various components, alone or in combination, shown in  FIGS. 1A and 1B  can be referred to herein as a response system  188 . In some cases, the response system  188  comprises the ECU  106  as well as one or more sensors, components, devices or systems discussed herein. 
     Examples of different vehicle systems  126  are illustrated in  FIG. 2 .  FIG. 2 , also includes the vehicle systems described above in relation with  FIG. 1A , in particular, the EPS  132 , the touch steering wheel system  134 , visual devices  140 , tactile devices  148 , user input devices  152 , and infotainment system  154 . It should be understood that the systems shown in  FIG. 2  are only intended to be exemplary and in some cases, some other additional systems can be included. In other cases, some of the systems can be optional and not included in all embodiments.  FIG. 2  will be described with reference to the components of  FIGS. 1A and 1B . Referring now to  FIG. 2 , the motor vehicle  100  can include an electronic stability control system  202  (also referred to as ESC system  202 ). The ESC system  202  can include provisions for maintaining the stability of the motor vehicle  100 . In some cases, the ESC system  202  can monitor the yaw rate and/or lateral g acceleration of the motor vehicle  100  to help improve traction and stability. The ESC system  202  can actuate one or more brakes automatically to help improve traction. An example of an electronic stability control system is disclosed in Ellis et al., U.S. Pat. No. 8,423,257, filed Mar. 17, 2010, the entirety of which is hereby incorporated by reference. In one embodiment, the electronic stability control system can be a vehicle stability system. 
     In some embodiments, the motor vehicle  100  can include an antilock brake system  204  (also referred to as an ABS system  204 ). The ABS system  204  can include various different components such as a speed sensor, a pump for applying pressure to the brake lines, valves for removing pressure from the brake lines, and a controller. In some cases, a dedicated ABS controller can be used. In other cases, ECU  106  can function as an ABS controller. In still other cases, the ABS system  204  can provide braking information, for example brake pedal input and/or brake pedal input pressure/rate, among others. Examples of antilock braking systems are known in the art. One example is disclosed in Ingaki, et al., U.S. Pat. No. 6,908,161, filed Nov. 18, 2003, the entirety of which is hereby incorporated by reference. Using the ABS system  204  can help improve traction in the motor vehicle  100  by preventing the wheels from locking up during braking. 
     The motor vehicle  100  can include a brake assist system  206 . The brake assist system  206  can be any system that helps to reduce the force required by a driver to depress a brake pedal. In some cases, the brake assist system  206  can be activated for older drivers or any other drivers who can need assistance with braking. An example of a brake assist system can be found in Wakabayashi et al., U.S. Pat. No. 6,309,029, filed Nov. 17, 1999, the entirety of which is hereby incorporated by reference. 
     In some embodiments, the motor vehicle  100  can include an automatic brake prefill system  208  (also referred to as an ABP system  208 ). The ABP system  208  includes provisions for prefilling one or more brake lines with brake fluid prior to a collision. This can help increase the reaction time of the braking system as the driver depresses the brake pedal. Examples of automatic brake prefill systems are known in the art. One example is disclosed in Bitz, U.S. Pat. No. 7,806,486, filed May 24, 2007, the entirety of which is hereby incorporated by reference. 
     In some embodiments, the motor vehicle  100  can include an electric parking brake (EPB) system  210 . The EPB system  210  includes provisions for holding the motor vehicle  100  stationary on grades and flat roads. In particular, the motor vehicle  100  can include an electric park brake switch (e.g., a button) that can be activated by the driver  102 . When activated, the EPB system  210  controls the braking systems discussed above to apply braking to one or more wheels of the motor vehicle  100 . To release the braking, the driver can engage the electric park brake switch and/or press on the accelerator pedal. Additionally, the EPB system  210  or other braking systems can include an automatic brake hold control feature that maintains brake hold when the vehicle is stopped, even after the brake pedal is released. Thus, when the vehicle comes to a full stop, brake hold is engaged and the brakes continue to hold until the accelerator pedal is engaged. In some embodiments, the automatic brake hold control feature can be manually engaged with a switch. In other embodiments, the automatic brake hold control feature is engaged automatically. 
     As mentioned above, the motor vehicle  100  includes provisions for communicating and/or controlling various systems and/or functions associated with the engine  104 . In one embodiment, the engine  104  includes an idle stop function that can be controlled by the ECU  106  and/or the engine  104  based information from, for example, the engine  104  (e.g., automatic transmission), the antilock brake system  204 , the brake assist system  205 , the automatic brake prefill system  208 , and/or the EPB system  210 . Specifically, the idle stop function includes provisions to automatically stop and restart the engine  104  to help maximize fuel economy depending on environmental and vehicle conditions. For example, the ECU  106  can activate the idle stop function based on gear information from the engine  104  (e.g., automatic transmission) and brake pedal position information from the braking systems described above. Thus, when the vehicle stops with a gear position in Drive (D) and the brake pedal is pressed, the ECU  106  controls the engine to turn OFF. When the brake pedal is subsequently released, the ECU  106  controls the engine to restart (e.g., turn ON) and the vehicle can begin to move. In some embodiments, when the idle stop function is activated, the ECU  106  can control the visual devices  140  to provide an idle stop indicator to the driver. For example, a visual device  140  on a dashboard of the motor vehicle  100  can be controlled to display an idle stop indicator. Activation of the idle stop function can be disabled in certain situations based on other vehicle conditions (e.g., seat belt is fastened, vehicle is stopped on a steep hill). Further, the idle stop function can be manually controlled by the driver  102  using, for example, an idle stop switch located in the motor vehicle  100 . 
     In some embodiments, the motor vehicle  100  can include a low speed follow system  212  (also referred to as an LSF system  212 ). The LSF system  212  includes provisions for automatically following a preceding vehicle at a set distance or range of distances. This can reduce the need for the driver to constantly press and depress the acceleration pedal in slow traffic situations. The LSF system  212  can include components for monitoring the relative position of a preceding vehicle (for example, using remote sensing devices such as lidar or radar). In some cases, the LSF system  212  can include provisions for communicating with any preceding vehicles for determining the GPS positions and/or speeds of the vehicles. Examples of low speed follow systems are known in the art. One example is disclosed in Arai, U.S. Pat. No. 7,337,056, filed Mar. 23, 2005, the entirety of which is hereby incorporated by reference. Another example is disclosed in Higashimata et al., U.S. Pat. No. 6,292,737, filed May 19, 2000, the entirety of which is hereby disclosed by reference. 
     The motor vehicle  100  can include a cruise control system  214 . Cruise control systems are well known in the art and allow a user to set a cruising speed that is automatically maintained by a vehicle control system. For example, while traveling on a highway, a driver can set the cruising speed to 55 mph. The cruise control system  214  can maintain the vehicle speed at approximately 55 mph automatically, until the driver depresses the brake pedal or otherwise deactivates the cruising function. 
     The motor vehicle  100  can include an automatic cruise control system  216  (also referred to as an ACC system  216 ). In some cases, the ACC system  216  can include provisions for automatically controlling the vehicle to maintain a predetermined following distance behind a preceding vehicle or to prevent a vehicle from getting closer than a predetermined distance to a preceding vehicle. The ACC system  216  can include components for monitoring the relative position of a preceding vehicle (for example, using remote sensing devices such as lidar or radar). In some cases, the ACC system  216  can include provisions for communicating with any preceding vehicles for determining the GPS positions and/or speeds of the vehicles. An example of an automatic cruise control system is disclosed in Arai et al., U.S. Pat. No. 7,280,903, filed Aug. 31, 2005, the entirety of which is hereby incorporated by reference. 
     The motor vehicle  100  can include a collision warning system  218 . In some cases, the collision warning system  218  can include provisions for warning a driver of any potential collision threats with one or more vehicles, objects and/or pedestrians. For example, a collision warning system can warn a driver when another vehicle is passing through an intersection as the motor vehicle  100  approaches the same intersection. Examples of collision warning systems are disclosed in Mochizuki, U.S. Pat. No. 8,558,718, filed Sep. 20, 2010, and Mochizuki et al., U.S. Pat. No. 8,587,418, filed Jul. 28, 2010, the entirety of both being hereby incorporated by reference. In one embodiment, the collision warning system  218  could be a forward collision warning system, including warning of vehicles and/or pedestrians. In another embodiment, the collision warning system  218  could be a cross traffic monitoring system, utilizing backup cameras or back sensors to determine if a pedestrian or another vehicle is behind the vehicle. 
     The motor vehicle  100  can include a collision mitigation braking system  220  (also referred to as a CMBS  220 ). The CMBS  220  can include provisions for monitoring vehicle operating conditions (including target vehicles, objects, pedestrians in the environment of the vehicle) and automatically applying various stages of warning and/or control to mitigate collisions. For example, in some cases, the CMBS  220  can monitor forward vehicles using a radar or other type of remote sensing device. If the motor vehicle  100  gets too close to a forward vehicle, the CMBS  220  could enter a first warning stage. During the first warning stage, a visual and/or audible warning can be provided to warn the driver. If the motor vehicle  100  continues to get closer to the forward vehicle, the CMBS  220  could enter a second warning stage. During the second warning stage, the CMBS  220  could apply automatic seat belt pretensioning. In some cases, visual and/or audible warnings could continue throughout the second warning stage. Moreover, in some cases, during the second stage automatic braking could also be activated to help reduce the vehicle speed. In some cases, a third stage of operation for the CMBS  220  can involve braking the vehicle and tightening a seat belt automatically in situations where a collision is very likely. An example of such a system is disclosed in Bond, et al., U.S. Pat. No. 6,607,255, and filed Jan. 17, 2002, the entirety of which is hereby incorporated by reference. The term collision mitigation braking system as used throughout this detailed description and in the claims can refer to any system that is capable of sensing potential collision threats and providing various types of warning responses as well as automated braking in response to potential collisions. 
     The motor vehicle  100  can include a lane departure warning system  222  (also referred to as an LDW system  222 ). The LDW system  222  can determine when a driver is deviating from a lane and provide a warning signal to alert the driver. Examples of lane departure warning systems can be found in Tanida et al., U.S. Pat. No. 8,063,754, filed Dec. 17, 2007, the entirety of which is hereby incorporated by reference. 
     The motor vehicle  100  can include a blind spot indicator system  224  (also referred to as a BSI system  224 ). The blind spot indicator system  224  can include provisions for helping to monitor the blind spot of a driver. In some cases, the blind spot indicator system  224  can include provisions to warn a driver if a vehicle is located within a blind spot. In other cases, the blind spot indicator system  224  can include provisions to warn a driver if a pedestrian or other object is located within a blind spot. Any known systems for detecting objects traveling around a vehicle can be used. 
     In some embodiments, the motor vehicle  100  can include a lane keep assist system  226  (also referred to as an LKAS system  226 ). The lane keep assist system  226  can include provisions for helping a driver to stay in the current lane. In some cases, the lane keep assist system  226  can warn a driver if the motor vehicle  100  is unintentionally drifting into another lane. Also, in some cases, the lane keep assist system  226  can provide assisting control to maintain a vehicle in a predetermined lane. For example, the lane keep assist system  226  can control the electronic power steering system  132  by applying an amount of counter-steering force to keep the vehicle in the predetermined lane. In another embodiment, the lane keep assist system  226 , in, for example, an automatic control mode, can automatically control the electronic power steering system  132  to keep the vehicle in the predetermined lane based on identifying and monitoring lane markers of the predetermined lane. An example of a lane keep assist system is disclosed in Nishikawa et al., U.S. Pat. No. 6,092,619, filed May 7, 1997, the entirety of which is hereby incorporated by reference. 
     In some embodiments, the motor vehicle  100  can include a lane monitoring system  228 . In some embodiments, the lane monitoring system  228  could be combined or integrated with the blind spot indicator system  224  and/or the lane keep assist system  226 . The lane monitoring system  228  includes provisions for monitoring and detecting the state of the vehicle, and elements in the environment of the vehicle, for example, pedestrians, objects, other vehicles, cross traffic, among others. Upon detection of said elements, the lane monitoring system  228  can warn a driver and/or work in conjunction with the lane keep assist system  226  to assist in maintaining control of the vehicle to avoid potential collisions and/or dangerous situations. The lane keep assist system  226  and/or the lane monitoring system  228  can include sensors and/or optical devices (e.g., cameras) located in various areas of the vehicle (e.g., front, rear, sides, roof). These sensors and/or optical devices provide a broader view of the roadway and/or environment of the vehicle. In some embodiments, the lane monitoring system  228  can capture images of a rear region of a vehicle and a blind spot region of the vehicle out of viewing range of a side mirror adjacent to the rear region of the vehicle, compress said images and display said images to the driver. An example of a lane monitoring system is disclosed in Nishiguichi et al., U.S. Publication Number 2013/0038735, filed on Feb. 16, 2011, the entirety of which is incorporated by reference. It is understood that after detecting the state of the vehicle, the lane monitoring system  228  can provide warnings or driver assistances with other vehicles systems, for example, the electronic stability control system  202 , the brake assist system  206 , the collision warning system  218 , the collision mitigation braking system  220 , the blind spot indicator system  224 , among others. 
     In some embodiments, the motor vehicle  100  could include a navigation system  230 . The navigation system  230  could be any system capable of receiving, sending and/or processing navigation information. The term “navigation information” refers to any information that can be used to assist in determining a location or providing directions to a location. Some examples of navigation information include street addresses, street names, street or address numbers, apartment or suite numbers, intersection information, points of interest, parks, any political or geographical subdivision including town, township, province, prefecture, city, state, district, ZIP or postal code, and country. Navigation information can also include commercial information including business and restaurant names, commercial districts, shopping centers, and parking facilities. In some cases, the navigation system could be integrated into the motor vehicle, for example, as a part of the infotainment system  154 . Navigation information could also include traffic patterns, characteristics of roads, and other information about roads the motor vehicle currently is travelling on or will travel on in accordance with a current route. In other cases, the navigation system could be a portable, stand-alone navigation system, or could be part of a portable device, for example, the portable device  122 . 
     As mentioned above, in some embodiments, the visual devices  140 , the audio devices  144 , the tactile devices  148  and/or the user input devices  152  can be part of a larger infotainment system  154 . In a further embodiment, the infotainment system  154  can facilitate mobile phone and/or portable device connectivity to the vehicle to allow, for example, the playing of content from the mobile device to the infotainment system. Accordingly, in one embodiment, the vehicle can include a hands free portable device (e.g., telephone) system  232 . The hands free portable device system  232  can include a telephone device, for example integrated with the infotainment system, a microphone (e.g., audio device) mounted in the vehicle. In one embodiment, the hands free portable device system  232  can include the portable device  122  (e.g., a mobile phone, a smart phone, a tablet with phone capabilities). The telephone device is configured to use the portable device, the microphone and the vehicle audio system to provide an in-vehicle telephone feature and/or provide content from the portable device in the vehicle. In some embodiments, the telephone device is omitted as the portable device can provide telephone functions. This allows the vehicle occupant to realize functions of the portable device through the infotainment system without physical interaction with the portable device. 
     The motor vehicle  100  can include a climate control system  234 . The climate control system  234  can be any type of system used for controlling the temperature or other ambient conditions in the motor vehicle  100 . In some cases, the climate control system  234  can comprise a heating, ventilation and air conditioning system as well as an electronic controller for operating the HVAC system. In some embodiments, the climate control system  234  can include a separate dedicated controller. In other embodiments, the ECU  106  can function as a controller for the climate control system  234 . Any kind of climate control system known in the art can be used. 
     The motor vehicle  100  can include an electronic pretensioning system  236  (also referred to as an EPT system  236 ). The EPT system  236  can be used with a seat belt (e.g., the seat belt  176 ) for the motor vehicle  100 . The EPT system  236  can include provisions for automatically tightening, or tensioning, the seat belt  176 . In some cases, the EPT system  236  can automatically pretension the seat belt  176  prior to a collision. An example of an electronic pretensioning system is disclosed in Masuda et al., U.S. Pat. No. 6,164,700, filed Apr. 20, 1999, the entirety of which is hereby incorporated by reference. 
     The motor vehicle  100  can include a vehicle mode selector system  238  that modifies driving performance according to preset parameters related to the mode selected. Modes can include, but are not limited to, normal, economy, sport, sport+ (plus), auto, and terrain/condition specific modes (e.g., snow, mud, off-road, steep grades). For example, in an economy mode, the ECU  106  can control the engine  104  (or vehicle systems related to the engine  104 ) to provide a more consistent engine speed thereby increasing fuel economy. The ECU  106  can also control other vehicle systems to ease the load on the engine  104 , for example, modifying the climate control system  234 . In a sport mode, the ECU  106  can control the EPS  132  and/or the ESC system  202  to increase steering feel and feedback. In terrain/condition specific modes (e.g., snow, mud, sand, off-road, steep grades), the ECU  106  can control various vehicle systems to provide handling, and safety features conducive to the specific terrain and conditions. In an auto mode, the ECU  106  can control various vehicle systems to provide full (e.g., autonomous) or partial automatic control of the vehicle. It is understood that the modes and features of the modes described above are exemplary in nature and that other modes and features can be implemented. Further it is appreciated that more than one mode could be implemented at the same or substantially the same time. 
     The motor vehicle  100  can include a turn signal control system  240  for controlling turn signals (e.g., directional indicators) and braking signals. For example, the turn signal control system  240  can control turn signal indicator lamps (e.g., mounted on the left and right front and rear corners of the vehicle, the side of the vehicle, the exterior side mirrors). The turn signal control system  240  can control (e.g., turn ON/OFF) the turn signal indicator lamps upon receiving a turn signal input from the driver (e.g., input via a user input device  152 , a turn signal actuator, etc.). In other embodiments, the turn signal control system  240  can control a feature and/or a visual cue of the turn signal indicator lamps. For example, a brightness, a color, a light pattern, a mode among others. The feature and/or visual cue control can be based on input received from the driver or can be an automatic control based on input from another vehicle system and/or a driver state. For example, the turn signal control system  240  can control the turn signal indicator lamps based on an emergency event (e.g., receiving a signal from the collision warning system) to provide warnings to other vehicles and/or provide information about occupants in the vehicle. Further, the turn signal control system  240  can control braking signals (e.g., braking indicator lamps mounted on the rear of the vehicle) alone or in conjunction with a braking system discussed herein. The turn signal control system  240  can also control a feature and/or visual cue of the braking signals similar to the turn signal indicator lamps described above. 
     The motor vehicle  100  can include a headlight control system  242  for controlling headlamps and/or flood lamps mounted on the vehicle (e.g., located the right and left front corners of the vehicle). The headlight control system  242  can control (e.g., turn ON/OFF, adjust) the headlamps upon receiving an input from the driver. In other embodiments, the headlight control system  242  can control (e.g., turn ON/OFF, adjust) the headlamps automatically and dynamically based on information from one or more of the vehicle systems. For example, the headlight control system  242  can actuate the headlamps and/or adjust features of the headlights based on environmental/road conditions (e.g., luminance outside, weather), time of day, among others. It is understood that the turn signal control system  240  and the headlight control system  242  could be part of a larger vehicle lighting control system. 
     The motor vehicle  100  can include a failure detection system  244  that detects a failure in one or more of the vehicle systems  126 . More specifically, the failure detection system  244  receives information from a vehicle system and executes a fail-safe function (e.g., system shut down) or a non-fail-safe function (e.g., system control) based on the information and a level of failure. In operation, the failure detection system  244  monitors and/or receives signals from one or more vehicle systems  126 . The signals are analyzed and compared to pre-determined failure and control levels associated with the vehicle system. Once the failure detection system  244  detects the signals meets a pre-determined level, the failure detection system  244  initiates control of the one or more vehicle systems and/or shuts down the one or more vehicle systems. It is understood that one or more of the vehicle systems  126  could implement an independent failure detection system. In some embodiments, the failure detection system  244  can be integrated with an on-board diagnostic system of the motor vehicle  100 . Further, in some embodiments, the failure detection system  244  could determine failure of a vehicle system based on a comparison of information from more than one vehicle system. For example, the failure detection system  244  can compare information indicating hand and/or appendage contact from the touch steering wheel system  134  and the electronic power steering system  132  to determine failure of a touch sensor as described in U.S. application Ser. No. 14/733,836 filed on Jun. 8, 2015 and incorporated herein by reference. 
     It is understood that, the vehicle systems  126  could incorporate any other kinds of devices, components, or systems used with vehicles. Further, each of these vehicle systems can be standalone systems or can be integrated with the ECU  106 . For example, in some cases, the ECU  106  can operate as a controller for various components of one or more vehicle systems. In other cases, some systems can comprise separate dedicated controllers that communicate with the ECU  106  through one or more ports. 
     Further, it is understood that the vehicle systems  126  other vehicle systems, sensors and monitoring systems discussed herein, for example, the physiological monitoring systems discussed in Section III (B) (1), the behavioral monitoring systems discussed in Section III (B) (2), the vehicular monitoring systems discussed in Section III (B) (3), and the identification systems and sensors discussed in Section III (B) (4) can be a vehicle system and/or include vehicle systems and discussed herein. Further, it is appreciated, that any combination of vehicle systems and sensors, physiological monitoring systems, behavioral monitoring systems, vehicular monitoring systems, and identification systems can be implemented to determine and/or assess one or more driver states discussed herein. 
     B. Monitoring Systems and Sensors 
     Generally, monitoring systems, as used herein, can include any system configured to provide monitoring information related to the motor vehicle  100 , the driver  102  of the motor vehicle  100 , and/or the vehicle systems  126 . More particularly, these monitoring systems ascertain, retrieve and/or obtain information about a driver, for example, information about a driver state or information to assess a driver state. In some embodiments, the ECU  106  can communicate and obtain monitoring information from the monitoring systems and/or one or more monitoring system sensors, for example, via one or more ports. 
     Monitoring systems can include, but are not limited to, optical devices, thermal devices, autonomic monitoring devices as well as any other kinds of devices, sensors or systems. More specifically, monitoring systems can include vehicular monitoring systems, physiological monitoring systems, behavioral monitoring systems, related sensors, among other systems and sensors. Further, monitoring information can include physiological information, behavioral information, and vehicle information, among others. 
     It will be understood that in certain embodiments, vehicle systems and monitoring systems can be used alone or in combination for receiving monitoring information. In some cases, monitoring information could be received directly from a vehicle system, rather than from a system or component designed for monitoring a driver state. In some cases, monitoring information could be received from both a monitoring system and a vehicle system. Accordingly, one or more monitoring systems can include one or more vehicle systems ( FIGS. 1A, 1B   2 ) and/or one or more monitoring systems ( FIG. 3 ). Additionally, as mentioned above, and as will be described in detail below, other additional vehicle systems and/or monitoring systems can be included that are not shown in  FIGS. 1A, 1B, 2 and 3 . 
     It will be understood that each of the monitoring systems discussed herein could be associated with one or more sensors or other devices. In some cases, the sensors could be disposed in one or more portions of the motor vehicle  100 . For example, the sensors could be integrated into a dashboard, seat (e.g., the seat  168 ), seat belt (e.g., the seat belt  176 ), door, dashboard, steering wheel (e.g., the touch steering wheel system  134 ), center console, roof or any other portion of the motor vehicle  100 . In other cases, however, the sensors could be portable sensors worn by a driver, integrated into a portable device (e.g., the portable device  122 ) carried by the driver, integrated into an article of clothing worn by the driver or integrated into the body of the driver (e.g. an implant). Specific types of sensors and sensor placement will be discussed in more detail below. 
     Exemplary monitoring systems as well as other exemplary sensors, sensing devices and sensor analysis (e.g., analysis and processing of data measured by the sensors) are described in detail below. It is appreciated that one or more components/functions of each of the systems and methods discussed herein can be implemented within or in conjunction with the motor vehicle  100 , the components of the motor vehicle  100 , the vehicle systems  126 , the monitoring systems of  FIGS. 1A, 1B, 2 and 3  and the systems and methods described in relation to  FIGS. 1A, 1B, 2, and 3 . The exemplary monitoring systems, the sensors, the sensing devices and the sensor analysis described below generally detect and provide monitoring information and can determine one or more driver states of the driver of the motor vehicle  100 . The one or more driver states can be utilized by the methods and systems described in relation to the other figures herein to control and/or modify one or more vehicle systems. The exemplary monitoring systems, sensors, sensing devices and sensors analysis are non-limiting and components and/or functions of the configurations and methods can be reorganized and/or omitted for other exemplary embodiments, including those related to  FIGS. 1A, 1B, 2 and 3 . 
     1. Physiological Monitoring Systems and Sensors 
     Generally, physiological monitoring systems and sensors include, but are not limited to, any automatic or manual systems and sensors that monitor and provide physiological information related to a driver of a motor vehicle (e.g., related to a driver state). The physiological monitoring systems can include one or more physiological sensors for sensing and measuring a stimulus (e.g., a signal, a property, a measurement, and/or a quantity) associated with the driver of the motor vehicle  100 . In some embodiments, the ECU  106  can communicate and obtain a data stream representing the stimulus from the physiological monitoring system from, for example, a port. In other words, the ECU  106  can communicate and obtain physiological information from the physiological monitoring systems of the motor vehicle  100 . 
     Physiological information includes information about the human body (e.g., a driver) derived intrinsically. Said differently, physiological information can be measured by medical means and quantifies an internal characteristic of a human body. Physiological information is typically not externally observable to the human eye. However, in some cases, physiological information is observable by optical means, for example, heart rate measured by an optical device. Physiological information can include, but is not limited to, heart rate, blood pressure, oxygen content, blood alcohol content (BAC), respiratory rate, perspiration rate, skin conductance, brain wave activity, digestion information, salivation information, among others. Physiological information can also include information about the autonomic nervous systems of the human body derived intrinsically. 
     Derived intrinsically includes physiological sensors that directly measure the internal characteristic of the human body. For example, heart rate sensors, blood pressure sensors, oxygen content sensors, blood alcohol content (BAC) sensors, EEG sensors, FNIRS sensors, FMRI sensors, bio-monitoring sensors, among others. It is understood that physiological sensors can be contact sensors and/or contactless sensors and can include electric current/potential sensors (e.g., proximity, inductive, capacitive, electrostatic), acoustic sensors, subsonic, sonic, and ultrasonic sensors, vibration sensors (e.g., piezoelectric), optical sensors, imaging sensors, thermal sensors, temperature sensors, pressure sensors, photoelectric sensors, among others. 
     In some embodiments, the ECU  106  can include provisions for receiving information about the physiological state of a driver. In one embodiment, the ECU  106  could receive physiological information related to the autonomic nervous system (or visceral nervous system) of a driver. As mentioned above, in one embodiment, the ECU  106  can include a port  178  for receiving physiological information about the state of a driver from a bio-monitoring sensor  180 . Examples of different physiological information about a driver that could be received from the bio-monitoring sensor  180  include, but are not limited to: heart information, such as, heart rate, blood pressure, blood flow, oxygen content, blood alcohol content (BAC), etc., brain information, such as, electroencephalogram (EEG) measurements, functional near infrared spectroscopy (fNIRS), functional magnetic resonance imaging (fMRI), digestion information, respiration rate information, salivation information, perspiration information, pupil dilation information, as well as other kinds of information related to the autonomic nervous system or other biological systems of the driver. 
     Generally, a bio-monitoring sensor could be disposed in any portion of a motor vehicle. In some cases, a bio-monitoring sensor could be disposed in a location proximate to a driver. For example, in one embodiment shown in  FIG. 1A , the bio-monitoring sensor  180  is located within or on the surface of the vehicle seat  168 , more specifically, the seat back support  172 . In other embodiments, however, the bio-monitoring sensor  180  could be located in any other portion of the motor vehicle  100 , including, but not limited to: a steering wheel (e.g., the touch steering wheel  134 ), a headrest (e.g., the headrest  174 ), a seat belt (e.g., the seat belt  176 ), an armrest, dashboard, rear-view mirror as well as any other location. Moreover, in some cases, the bio-monitoring sensor  180  can be a portable sensor that is worn by a driver, associated with a portable device located in proximity to the driver, such as a smart phone (e.g., the portable device  122 ) or similar device, associated with an article of clothing worn by the driver or integrated into the body of the driver (e.g. an implant). Further, it is understood, that the systems and methods described herein can include one or more bio-monitoring sensors. Exemplary types and locations of sensors will be discussed in more detail herein. 
     In some embodiments, the ECU  106  can include provisions for receiving various kinds of optical information about a physiological state of a driver. As mentioned above, in one embodiment, the ECU  106  includes a port  160  for receiving information from one or more optical sensing devices, such as an optical sensing device  162 . The optical sensing device  162  could be any kind of optical device including a digital camera, video camera, infrared sensor, laser sensor, as well as any other device capable of detecting optical information. In one embodiment, the optical sensing device  162  can be a video camera. In another embodiment, the optical sensing device  162  can be one or more cameras or optical tracking systems. In addition, in some cases, the ECU  106  could include a port  164  for communicating with a thermal sensing device  166 . The thermal sensing device  166  can be configured to detect thermal information about the physiological state of a driver. In some cases, the optical sensing device  162  and the thermal sensing device  166  could be combined into a single sensor. 
     The optical and thermal sensing devices can be used to monitor physiological information, for example, heart rate, pulse, blood flow, skin color, pupil dilation, respiratory rate, oxygen content, blood alcohol content (BAC), among others, from image data. For example, heart rate and cardiac pulse can be extracted and computed in by remote and non-contact means from digital color video recordings of, for example, the human face as proposed by Poh et al., in “Advancements in Noncontact, Multiparameter Physiological Measurements Using a Webcam,” Biomedical Engineering, IEEE Transactions on, vol. 58, no. 1, pp. 7, 11, January 2011, and “Non-contact, Automated Cardiac Pulse Measurements Using Video Imaging and Blind Source Separation,” Optics Express 18 (2010):10762. 
     Further, image and video magnification can be used to visualize the flow of blood and small motions of the drivers face. This information can be used to extract blood flow rate, pulse rates, and skin color information as proposed by Wu et al., in “Eulerian Video Magnification for Revealing Subtle Changes in the World,” ACM Trans. Graph. 31, 4, Article 65 (July 2012), 8 pages. It is appreciated that other types of physiological information can be extracted using information from optical and thermal sensing devices, such as oxygen content and blood alcohol content. 
     Referring now to  FIG. 3 , an illustration of an embodiment of various monitoring systems  300  and sensors that can be associated with the motor vehicle  100  is shown. The monitoring systems  300  ascertain, retrieve, and/or obtain information about a driver, and more particularly, a driver state. In some cases, the monitoring systems are autonomic monitoring systems. These monitoring systems could include one or more bio-monitoring sensors  180 . In one embodiment, the monitoring systems  300  and sensors of  FIG. 3  can be part of a larger physiological monitoring system and/or a larger behavioral monitoring system (discussed below). Thus, in some embodiments, the monitoring systems  300  and sensors of  FIG. 3  can monitor and obtain physiological information and/or behavioral information related to a state of a driver. It is understood, that reference to monitoring systems herein, can in some embodiments, refer to the vehicle systems of  FIG. 2 . For example, the vehicle systems of  FIG. 2  can monitor and provide vehicle information. 
     i. Heart Rate Monitoring Systems, Sensors and Signal Processing 
     Referring again to  FIG. 3 , in some embodiments, the motor vehicle  100  can include a heart rate monitoring system  302 . The heart rate monitoring system  302  can include any devices or systems for monitoring the heart information of a driver. In some cases, the heart rate monitoring system  302  could include heart rate sensors  304 , blood pressure sensors  306 , oxygen content sensors  308  and blood alcohol content sensors  310 , as well as any other kinds of sensors for detecting heart information and/or cardiovascular information. Moreover, sensors for detecting heart information could be disposed in any locations within the motor vehicle  100  to detect the heart information of the driver  102 . For example, the heart rate monitoring system  302  could include sensors disposed in a dashboard, steering wheel (e.g., the steering wheel  134 ), seat (e.g., the vehicle seat  168 ), seat belt (e.g., the seat belt  176 ), armrest or other component to detect the heart information of a driver. 
     In one embodiment, the heart rate sensors  304  of the heart rate monitoring system  302  includes optical sensing devices  162  and/or thermal sensing devices  166  to sense and provide heart rate information, for example, a heart rate signal indicative of a driver state. For example, the optical sensing devices  162  and/or the thermal sensing device  166  can provide information (e.g., images, video) of the upper body, face, extremities, and/or head of a driver or occupant. Heart rate information can be extracted from said information, for example, heart information can be detected from head movements, eye movements, facial movements, skin color, skin transparency, chest movement, upper body movement, among others. It is understood that the heart rate sensors  304  including optical sensing devices  162  and/or thermal sensing devices  166  to sense and provide heart rate information can be implemented with other exemplary monitoring systems, sensors and sensor analysis described herein. 
     A.) Monitoring System for Use with a Vehicle 
     In one embodiment, the heart rate monitoring system  302  includes heart rate sensors  304  located in specific positions within a vehicle to provide a signal indicative of a driver state, as discussed in U.S. Pat. No. 8,941,499, filed on Aug. 1, 2011 and issued on Jan. 27, 2015, entitled Monitoring System for use with a Vehicle and Method of Assembling Same, which is incorporated by reference in its entirety herein. As will be discussed herein, at least some known heart rate detections have a low signal-to-noise ratio because the heart rate signal may be relatively weak and/or because the environmental noise in a vehicle may be relatively high. Accordingly, to accurately determine a driver state, a monitoring system must be configured properly to account for these issues. The &#39;499 patent will now be discussed, however, for brevity, the &#39;499 patent will not be discussed in its entirety. 
       FIG. 4  illustrates an exemplary monitoring system  400  that includes a seat  402  and a seat belt  404  that is selectively coupleable to seat  402  to secure an occupant (not shown) within seat  402 . More specifically, in the exemplary embodiment, seat belt  404  is selectively moveable between an engaged configuration (shown generally in  FIG. 4 ), wherein seat belt  404  is coupled to seat  402 , and a disengaged configuration (not shown), wherein at least a portion of seat belt  404  is uncoupled from seat  402 . As described herein, monitoring system  400  is used to monitor a driver of the vehicle. Additionally or alternatively, the monitoring system  400  may be configured to monitor any other occupant of the vehicle. It is appreciated that the seat  402  and the components shown in  FIG. 4  can be implemented in the motor vehicle  100  of  FIG. 1A . For example, seat  402  can be similar to the vehicle seat  168  with similar components discussed herein. The monitoring system  400  can be part of the monitoring systems shown in  FIG. 3 , for example a heart rate monitoring system  302 . Additionally, the monitoring system  400  can include various sensors for heart rate monitoring, for example, the heart rate sensors  304 , the blood pressure sensors  306 , the oxygen content sensors  308 , and/or the blood alcohol content sensors  310 . 
     In the exemplary embodiment of  FIG. 4 , the seat  402  includes a lower support  406  and a back support  408  that extends generally upward from lower support  406 . The seat  402  can also include a headrest  410  that extends generally upward from the back support  408 . The back support  408  includes a seat back surface  412  that is oriented to face a front (not shown) of the vehicle. In the exemplary embodiment, seat belt  404  is selectively extendable across seat back surface  412 . More specifically, in the exemplary embodiment, a lap belt portion  414  of seat belt  404  is extendable substantially horizontally with respect to seat back surface  412 , and a sash belt portion  416  of seat belt  404  is extendable substantially diagonally with respect to seat back surface  412 . Alternatively, seat belt  404  may be extendable in any direction that enables the monitoring system  400  to function as described herein 
     In the exemplary embodiment illustrated in  FIG. 4 , when the monitoring system  400  is used, a first sensor  418  is positioned to detect an occupant&#39;s heart rate and/or blood flow rate. It is understood that the first sensor could be the bio-monitoring sensor  180  of  FIG. 1A . More specifically, in the exemplary embodiment shown in  FIG. 4 , first sensor  418  detects an occupant&#39;s heart rate and/or blood flow rate when the occupant is secured within seat  402  and seat belt  404  is in the engaged configuration. For example, in the exemplary embodiment, when seat belt  404  is in the engaged configuration, first sensor  418  is positioned in relative close proximity to the occupant&#39;s heart. More specifically, in the exemplary embodiment, first sensor  418  is coupled to seat belt  404  or, more specifically, to seat back surface  412  and/or to sash belt portion  416 . Alternatively, first sensor  418  may be positioned in any other location that enables the monitoring system  400  to function as described herein. 
     In the exemplary embodiment, first sensor  418  has a passive state, as described above, and an active state. In the exemplary embodiment, first sensor  418  generates a raw signal (not shown), when in the active state, that is representative of biological data and noise detected and/or measured by first sensor  418 . More specifically, in the exemplary embodiment, the raw signal is generated proportional to a mechanical stress and/or vibration detected by first sensor  418 . Moreover, in the exemplary embodiment, first sensor  418  generates an alert signal (not shown), when in the active state, that is detectable by the occupant. For example, in one embodiment, first sensor  418  is used to produce a tactile and/or audible signal that may be detected by the occupant. As used herein, the term “biological data” is used to refer to data associated with the occupant&#39;s heart rate, blood flow rate, and/or breathing rate. Biological data can also refer to physiological information. Moreover, as used herein, the term “noise” is used to refer to sensor detections other than biological data. 
     Furthermore, in the exemplary embodiment, a second sensor  420  is positioned remotely from first sensor  418 . More specifically, in the exemplary embodiment, second sensor  420  is positioned to detect noise that is substantially similar to noise detected by first sensor  418 . For example, in the exemplary embodiment, second sensor  420  is coupled to seat belt  404  or, more particularly, to lap belt portion  414  and/or to lower support  406 . Alternatively, second sensor  420  may be positioned in any other location that enables the monitoring system  400  to function as described herein. 
     In the exemplary embodiment, second sensor  420  generates a baseline signal (not shown) that is representative of noise and, more particularly, noise that is substantially similar to noise subjected to and detected by first sensor  418 . More specifically, in the exemplary embodiment, the baseline signal generated is proportional to mechanical stresses and/or vibrations detected by second sensor  420 . 
     In the exemplary embodiment, first sensor  418  and/or second sensor  420  is formed with a thin film (not shown) that is flexible, lightweight, and/or durable. As such, in the exemplary embodiment, the thin film may be contoured to be generally ergonomic and/or comfortable to the occupant being monitored by the monitoring system  400 . For example, in the exemplary embodiment, the thin film has a substantially low profile with a thickness (not shown) that is, for example, less than 600 nm. More particularly, in the exemplary embodiment, the thin film thickness is between approximately 100 nm and 300 nm. Moreover, in the exemplary embodiment, the flexibility and durability of the material used enables first sensor  418  and/or second sensor  420  to be embedded in seat  402  and/or seat belt  404 . Alternatively, the thin film may have any thickness that enables first sensor  418  and/or second sensor  420  to function as described herein. In the exemplary embodiment, the thin film is fabricated from a thermoplastic fluropolymer, such as polyvinylidene fluoride, and poled in an electric field to induce a net dipole moment on first sensor  418  and/or second sensor  420 . Alternatively, the thin film may be fabricated from any material that enables first sensor  418  and/or second sensor  420  to function as described herein. 
     In some embodiments, the first sensor  418  and/or the second sensor  420  can be photoplethysmopgraphy (PPG) sensors that optically sense changes in blood volume and blood composition. Thus, PPG sensors can optically obtain a photoplethysmogram of cardiac activity as a volumetric measurement of pulsatile blood flow. PPG measurements can be sensed at various locations on (e.g., contact sensors) or near (e.g., contactless sensors) an vehicle occupant&#39;s body. In another embodiment shown in  FIG. 4 , the seat  402  can also include one or more sensors and/or sensor arrays. For example, the sensor array  422  can include sensors, indicated by circular elements, in various configurations and locations within the seat  402 . It is understood that the sensor array  422  can include sensors in other shapes, configurations, and positions than those shown in  FIG. 4 . 
     In one embodiment, the sensor array  422  includes PPG sensors as described in U.S. application Ser. No. 14/697,593 filed on Apr. 27, 2015, which is incorporated by reference herein. Similar to the embodiment described above, the &#39;593 application includes provisions for capturing and decontaminating PPG signals in a vehicle from the sensor array  422 . For example, the sensor array  422  can sense PPG signals to determine a driver&#39;s physiological state and/or motion artifacts associated with the driver and/or the vehicle. The PPG signals and the motion artifacts can be processed to provide a true biological signal (i.e., PPG signal). Other embodiments including PPG sensors will be described in more detail herein with reference to  FIG. 8 . 
     Referring now to  FIG. 5  is a block diagram of an exemplary computing device  500  that may be used with monitoring system  400  of  FIG. 4 . In some embodiments, the computing device  500  could be integrated with the motor vehicle  100  of  FIGS. 1A and 1B , for example, as part of the ECU  106 . In the exemplary embodiment of  FIG. 5 , computing device  500  determines a state of the occupant based on raw signals generated by first sensor  418  and/or baseline signals generated by second sensor  420 . More specifically, in the exemplary embodiment, computing device  500  receives the raw signal from first sensor  418  and the baseline signal from second sensor  420 , and generates a desired signal (not shown) after determining a difference between the raw signal and the baseline signal. That is, in the exemplary embodiment, computing device  500  increases a signal-to-noise ratio of the raw signal by canceling and/or removing the baseline signal, i.e., noise, from the raw signal to generate a desired signal that is indicative of substantially only the biological data. 
     Moreover, in the exemplary embodiment, computing device  500  may be selectively tuned to facilitate increasing the signal-to-noise ratio of the raw signal, the baseline signal, and/or the desired signal. For example, in the exemplary embodiment, computing device  500  is programmed to impedance match, i.e., tune, the raw signal, the baseline signal, and/or the desired signal based on biological data, environmental data, and/or other data. For example, in the exemplary embodiment, the raw signal, the baseline signal, and/or the desired signal may be tuned based on a type of clothing the occupant being monitored is wearing. That is, each clothing type and/or layer can have a respective tune circuit associated with it that enables a desired signal that is indicative of the biological data to be generated. 
     In the exemplary embodiment, the computing device  500  determines a state of the occupant based on the desired signal or, more particularly, the biological data. More specifically, in the exemplary embodiment, computing device  500  creates a parameter matrix (not shown) that includes a plurality of footprints associated with the occupant&#39;s biological data over time. Generally, the plurality of footprints are indicative of the occupant in an operating state. However, when the biological data associated with at least one footprint deviates beyond a predetermined threshold from the biological data associated with the other footprints, computing device  500  may determine that the occupant is in a drowsy state. For example, in the exemplary embodiment, a heart rate and/or blood flow rate that is slower and/or is less than an average heart rate and/or blood flow rate by a predetermined amount may indicate drowsiness of the occupant. 
     In the exemplary embodiment, the computing device  500  includes a memory device  502  and a processor  504  that is coupled to memory device  502  for executing programmed instructions. The memory device  502  and/or the processor  504  can be implemented as the memory  110  and/or the processor  108  shown in  FIG. 1B . Processor  504  may include one or more processing units (e.g., in a multi-core configuration). In one embodiment, executable instructions and/or biological data are stored in memory device  502 . For example, in the exemplary embodiment, memory device  502  stores software (e.g., software modules  116  of  FIG. 1B ) for use in converting a mechanical stress and/or vibration to a signal. Computing device  500  is programmable to perform one or more operations described herein by programming memory device  502  and/or processor  504 . For example, processor  504  may be programmed by encoding an operation as one or more executable instructions and providing the executable instructions in memory device  502 . 
     Similar to the processor  108  of  FIG. 1B , the processor  504  may include, but is not limited to, a general purpose central processing unit (CPU), a graphics processing unit (GPU), a microcontroller, a reduced instruction set computer (RISC) processor, an application specific integrated circuit (ASIC), a programmable logic circuit (PLC), and/or any other circuit or processor capable of executing the functions described herein. The methods described herein may be encoded as executable instructions embodied in a computer readable medium, including, without limitation, a storage device, and/or a memory device. Such instructions, when executed by a processor, cause the processor to perform at least a portion of the methods described herein. The above examples are exemplary only, and thus are not intended to limit in any way the definition and/or meaning of the term processor. 
     Similar to the memory  110  of  FIG. 1B , the memory device  502 , as described herein, is one or more devices that enable information such as executable instructions and/or other data to be stored and retrieved. Memory device  502  may include one or more computer readable media, such as, without limitation, dynamic random access memory (DRAM), static random access memory (SRAM), a solid-state disk, and/or a hard disk. Memory device  502  may be configured to store, without limitation, executable instructions, biological data, and/or any other type of data suitable for use with the systems described herein. 
     In the exemplary embodiment, the computing device  500  includes a presentation interface  506  that is coupled to processor  504 . Presentation interface  506  outputs and/or displays information, such as, but not limited to, biological data and/or any other type of data to a user (not shown). For example, presentation interface  506  may include a display adapter (not shown) that is coupled to a display device (not shown), such as a cathode ray tube (CRT), a liquid crystal display (LCD), a light-emitting diode (LED) display, an organic LED (OLED) display, and/or an “electronic ink” display. In some embodiments, the presentation interface  506  could be implemented on a display of one of the visual devices  140  of  FIG. 1A . 
     In the exemplary embodiment, computing device  500  includes an input interface  508  that receives input from a user. Input interface  508  can be similar to user input devices  152  of  FIG. 1A . For example, input interface  508  receives instructions for controlling an operation of the monitoring system  400  and/or any other type of data suitable for use with the systems described herein. In the exemplary embodiment, input interface  508  is coupled to processor  504  and may include, for example, a keyboard, a pointing device, a mouse, a stylus, a touch sensitive panel (e.g., a touch pad or a touch screen), a gyroscope, an accelerometer, a position detector, and/or an audio input interface. A single component, such as a touch screen, may function as both a display device of presentation interface  506  and as input interface  508   
     In the exemplary embodiment, computing device  500  includes a communication interface  510  coupled to memory device  502  and/or processor  504 . The communication interface  510  can be similar to the communication interface  114  of  FIG. 1B . Communication interface  510  is coupled in communication with a remote device, such as first sensor  418 , second sensor  420 , and/or another computing device  500 . For example, communication interface  510  may include, without limitation, a wired network adapter, a wireless network adapter, and/or a mobile telecommunications adapter. 
     In the exemplary embodiment, computing device  500  may be used to enable first sensor  418  to generate the alert signal. More specifically, in the exemplary embodiment, computing device  500  may be programmed to determine whether the alert signal is generated based on at least the raw signal from first sensor  418 , the baseline signal from second sensor  190 , and/or the desired signal generated by computing device  500 . Moreover, in the exemplary embodiment, computing device  500  may be transmit a signal to first sensor  418  that enables first sensor  418  to transmit a tactile and/or audible signal that may be detected by the occupant. The tactile and/or audible signal could be implemented through the audio devices  144  and/or the tactile devices  148  of  FIG. 1A . As such, in the exemplary embodiment, the occupant may be stimulated by the alert signal. 
     According to the embodiment described above with reference to  FIGS. 4 and 5 , the configuration described herein enables a state of an occupant (e.g., a driver state) to be determined. More specifically, the embodiments described herein facilitate increasing a signal indicative of an occupant&#39;s heart rate or blood flow rate and/or reducing undesired noise. Moreover, the embodiments described herein are generally more ergonomic and/or more comfortable relative to other known monitoring systems. 
     It is appreciated that other exemplary vehicle systems and monitoring systems, including the sensors, sensor placement, sensor configuration, and sensor analysis, described with reference to  FIGS. 4 and 5 , can be implemented with the motor vehicle  100  of  FIG. 1 , the vehicle systems  126  and the monitoring systems of  FIG. 3 . The exemplary systems and methods described with reference to  FIGS. 4 and 5  can be used to monitor the driver  102  in the motor vehicle  100  and determine one or more driver states and/or a combined driver state index, which will be described in more detail herein. 
     b.) System and Method for Determining Changes in a Driver State 
     As discussed above, the heart rate monitoring system  302  can include any devices or systems for monitoring the heart information of a driver. In one embodiment, the heart rate monitoring system  302  includes heart rate sensors  304  that facilitate systems and methods for determining biological changes in a driver state based on parasympathetic and sympathetic activity levels, as discussed in U.S. Pat. No. 9,420,958, entitled System and Method for Determining Changes in a Body State, which is incorporated by reference in its entirety herein. As will be discussed, parasympathetic and sympathetic activity levels determined based on heart rate information can be used to determine one or more driver states and subsequently control vehicle systems based in part on the one or more driver states. The &#39;112 application will now be discussed, however, for brevity, the &#39;112 application will not be discussed in its entirety. 
     Functional or structural variations in cardiac activity (e.g., heart rate information) can indicate biological system activity levels (e.g., parasympathetic and sympathetic activity levels of the autonomic nervous system), which can provide accurate measurements of a driver state or a transition from one driver state to another driver state.  FIG. 6  illustrates an exemplary computer system  600 . In some embodiments, the exemplary computer system  600  can be a heart rate monitoring system  302  ( FIG. 3 ). Further, the computer system  600  can be implemented as part of the ECU  106  shown in  FIG. 1B . Referring again to  FIG. 6 , the computer system  600  includes a computing device  602 , a processor  604 , an input/output device  606 , a memory  608 , a communication module  610 , and a monitoring system  612 . The computer system  600  can include similar components and functionality as the ECU  106  in  FIG. 1B  and the monitoring systems described in  FIG. 3 . The monitoring system  612  can include and/or communicate with a plurality of sensors  614 . The plurality of sensors  614  can include, for example, heart rate sensors  304  ( FIG. 3 ). 
     Referring again to  FIG. 6 , the processor  604  includes a signal receiving module  616 , a feature determination module  618 , an interval determination module  620 , a derivative calculation module  622  and an identification module  624 , which process data signals and execute functions as described in further detail herein. The monitoring system  612  is configured to monitor and measure monitoring information associated with an individual for determining changes in a driver state of the individual and transmit the information to the computing device  602 . The monitoring information can include heart rate information. In other embodiments, the monitoring information can include, but is not limited to, physical characteristics of the individual (e.g., posture, position, movement) and biological characteristics of the individual (e.g., cardiac activity, such as, heart rate, electrocardiogram (EKG), blood pressure, blood flow, oxygen content, blood alcohol content) and other biological systems of the individual (e.g., circulatory system, respiratory system, nervous system, including the autonomic nervous system, or other biological systems). Other types of monitoring information can include, environmental information, such as, physical characteristics of the environment in proximity to the individual (e.g., light, temperature, weather, pressure, sounds). The monitoring system  612  can include any system configured to monitor and measure the monitoring information, such as, optical devices, thermal devices, autonomic monitoring devices (e.g., heart rate monitoring devices) as well as any other kinds of devices, sensors, or systems. 
     In the illustrated embodiment of  FIG. 6 , the monitoring system  612  includes a plurality of sensors  614  for monitoring and measuring the monitoring information. In some embodiments, the sensors  614  can include heart rate sensors  304 , blood pressure sensors  306 , oxygen content sensors  308 , blood alcohol content sensors  310 , EEG sensors  320 , FNIRS sensors  322 , FMRI sensors  324 , and other sensors utilized by the vehicle systems and the monitoring systems of  FIGS. 2 and 3 . The sensors  614  sense a stimulus (e.g., a signal, property, measurement or quantity) using various sensor technologies and generate a data stream or signal representing the stimulus. The computing device  602  is capable of receiving the data stream or signal representing the stimulus directly from the sensors  614  or via the monitoring system  612 . Although particular sensors are described herein, any type of suitable sensor can be utilized. 
     The sensors  614  can be contact sensors and/or contactless sensors and can include electric current/potential sensors (e.g., proximity, inductive, capacitive, electrostatic), subsonic, sonic, and ultrasonic sensors, vibration sensors (e.g., piezoelectric), optical, photoelectric or oxygen sensors, among others. Generally, the sensors  614  can be located in any position proximate to the individual or on the individual, in a monitoring device, such as a heart rate monitor, in a portable device, such as, a mobile device, a laptop or similar devices. The sensors and processing of signals generated by the sensors will be discussed in more detail with reference to  FIG. 7  below. Further, the monitoring system  612  and/or the computing device  602  can receive the monitoring information from the portable device or any other device (e.g., a watch, a piece of jewelry, clothing articles) with computing functionality (e.g., including a processor similar to processor  604 ). The portable device may also contain stored monitoring information or provide access to stored monitoring information on the Internet, other networks, and/or external databases. 
     As mentioned above, in one embodiment, the monitoring system  612  can monitor and measure monitoring information associated with a vehicle occupant (e.g., a driver) in a vehicle, for example, the motor vehicle  100  and the driver  102  of  FIG. 1A . The monitoring system  612  can determine changes in a driver state of the occupant and transmit the monitoring information to the ECU  106 . The monitoring system  612  receives the monitoring information from various sensors. The sensors can include, for example, the optical sensor  162 , the thermal sensor  166 , and the bio-monitoring sensor  180 , which can be included as part of the plurality of sensors  614 . 
     As discussed herein, the sensors could be disposed in any portion of the motor vehicle  100 , for example, in a location proximate to the driver  102 . For example, in a location in or on the surface of the vehicle seat  168 , the headrest  174 , the steering wheel  134 , among others. In another embodiment, the sensors could be located in various positions as shown in  FIG. 4  (e.g., the seat  402 , the seat belt  404 , a lower support  406 , a back support  408 , a seat back surface  412 , a lap belt portion  414 , and a sash belt portion  416 ). In other embodiments, however, the sensors could be located in any other portion of motor vehicle  100 , including, but not limited to an armrest, a seat, a seat belt, dashboard, rear-view mirror as well as any other location. Moreover, in some cases, the sensor can be a portable sensor that is worn by the driver  102 , associated with a portable device located in proximity to the driver  102 , such as a smart phone or similar device (e.g., the portable device  122 ), or associated with an article of clothing worn by the driver  102 . 
     With reference to  FIG. 7 , a computer-implemented method is shown for determining changes in a driver state of an individual. In particular, the method will be described in association with the computer system  600  of  FIG. 6 , though it is to be appreciated that the method could be used with other computer systems. Additionally, the method can be modified for alternative embodiments described herein (e.g., the motor vehicle  100 ,  FIG. 1A ). It is to be appreciated that a driver state herein refers to biological or physiological state of an individual or a transition to another state. For example, a driver state can be one or more of alert, drowsy, distracted, stressed, intoxicated, other generally impaired states, other emotional states and/or general health states. (See discussion of driver state in Section I). Further, cardiac activity or a measurement of cardiac activity, as used herein, refers to events related to the flow of blood, the pressure of blood, the sounds and/or the tactile palpations that occur from the beginning of one heart beat to the beginning of the next heart beat or the electrical activity of the heart (e.g., EKG). Thus, the measurement of cardiac activity can indicate a plurality of cardiac cycles or a plurality of heart beats. 
     At step  702 , the method includes receiving a signal from a monitoring system. The signal indicates a measurement of cardiac activity of the individual over a period of time. In one embodiment, the monitoring system  612  is configured to monitor cardiac activity of an individual from the plurality of sensors  614 . As discussed above, the sensors  614  sense a stimulus (e.g., a signal, property, measurement or quantity) using various sensor technologies and generate a data stream or signal representing the stimulus. Specifically, the data stream or signal representing the stimulus is transmitted from the sensors to the signal receiving module  616 , directly or via the monitoring system  612 . In the illustrated embodiment, the signal receiving module  616  can be further configured to process the signal thereby generating a proxy of the signal in a particular form. It is appreciated that the sensors  614  or the monitoring system  612  can also perform processing functions. Processing can include amplification, mixing, and filtering of the signal as well as other signal processing techniques. In one embodiment, upon receiving the signal, the signal is processed into a plurality of waveforms, where each one of the waveforms indicates one heartbeat. 
     Particular sensors will now be described in operation for sensing monitoring information, specifically, physiological characteristics (e.g., cardiac activity). Although specific sensors and methods of sensing are discussed herein, it will be appreciated that other sensors and methods of sensing cardiac activity can be implemented. The sensors  614  can be contact sensors and/or contactless sensors and can include electric current/potential sensors (e.g., proximity, inductive, capacitive, electrostatic), subsonic, sonic, and ultrasonic sensors, vibration sensors (e.g., piezoelectric), optical, photoelectric or oxygen sensors, among others. 
     Electric current/potential sensors are configured to measure an amount or change in an electric current, electrical charge or an electric field. In one embodiment, electric potential sensors can measure electrical activity of the heart of the individual over a period of time (i.e., an EKG). The electric potential sensors can be contact sensors or contactless sensors located on or in proximity to the individual. 
     Sonic sensors are configured to measure sound waves or vibration at frequencies below human auditory range (subsonic), at frequencies within human auditory range (sonic) or at frequencies above human auditory range (ultrasonic). In one embodiment, sonic sensors can measure sound waves or vibration generated by cardiac activity. In another embodiment, ultrasonic sensors generate high frequency sound waves and evaluate the echo received back by the sensor. Specifically, ultrasonic sensors can measure sounds or vibrations produced by the heart. For example, the ultrasonic sensors can generate sound waves towards the thoracic region (e.g., in front or back of chest area) of an individual and measure an echo received back by the sensor indicating cardiac activity. 
     Optical sensors provide image-based feedback and include machine vision systems, cameras and other optical sensors. Digital signals generated by the optical sensors include a sequence of images to be analyzed. For example, in one embodiment, a camera (e.g., the optical sensor  162 ,  FIG. 1A ) can generate images of eye movement, facial expressions, positioning or posture of the individual. 
     Photoelectric sensors use optics and light (e.g., infrared) to detect a presence, a volume or a distance of an object. In one embodiment, the photoelectric sensors optically obtain a photoplethysmogram (PPG) of cardiac activity, which is a volumetric measurement of pulsatile blood flow. As discussed above with  FIG. 4 , PPG measurements can be sensed at various locations on or near an individual&#39;s body using, for example, optical and/or light sensors (e.g., near-infrared, infrared, laser). As discussed in U.S. application Ser. No. 14/697,593 filed on Apr. 27, 2015 and incorporated here, the optical and/or light sensors can be configured to increase or decrease an intensity of light emitted to emit a plurality of wavelengths based on the location of the sensors and the type of measurement that is output by the sensors. 
       FIG. 8  illustrates a schematic representation of an individual  802  and a PPG analysis computer  804 . PPG measurements can be obtained from different locations of the individual  802 , for example, a left ear  806 , a right ear  808 , a left hand/finger  810 , a right hand/finger  812 , a left foot/toe  814 , and a right foot/toe  816 . In another embodiment, PPG measurements can be obtained from different sensors in the sensor array  422  shown in  FIG. 4 . The measurements can be obtained by photoelectric sensors, optical and/or light sensors near or on the above mentioned locations and transmitted to the PPG analysis computer  804 . The PPG analysis computer  804  includes provisions for analyzing the PPG measurements and comparing PPG measurements obtained from different locations of the individual  802 . In some embodiments, the monitoring system  612  or the processor  604  of  FIG. 6  can perform the functions of the PPG analysis computer  804 . In other embodiments, the methods described with reference to  FIGS. 4 and 5  (e.g., the processor  504 ) and/or the methods described in the &#39;592 application can perform the functions of the PPG analysis computer  804 . Further, in other embodiments, the ECU  106  (e.g., the processor  108 ) shown in  FIG. 1B  can perform the functions of the PPG analysis computer  804 . 
     Referring again to  FIG. 7 , at step  704 , the method includes determining at least one signal feature, wherein the signal feature is a reoccurring event over the period of time. In one embodiment, the feature determination module  618  receives the signal from the signal receiving module  616  and determines the signal feature. The signal feature can be a signal or signal waveform (i.e., shape) characteristic. Exemplary signal features include, but are not limited to, a deflection, a sound, a wave, a duration, an interval, an amplitude, a peak, a pulse, a wavelength or a frequency that reoccurs in the signal over the period of time. 
     As discussed above, the sensors  614  generate a signal representing the stimulus measured. The signal and the signal features vary depending on the property (i.e., the physiological, biological, or environmental characteristic) sensed the type of sensor and the sensor technology. The following are exemplary cardiac waveforms (i.e., signals indicating a measurement of cardiac activity) with signal features reoccurring over a period of time. Although specific waveforms are disclosed with respect to cardiac activity, the methods and systems disclosed herein are applicable to waveforms and signals associated with other physiological or environment characteristics associated with individual for identifying a driver state or a transition to a driver state. 
     Referring now to  FIG. 9A , a cardiac waveform  902  of an electrical signal representing cardiac activity is illustrated. In particular, the cardiac waveform  902  represents an EKG waveform  902 , which is a graphical representation of the electrical activity of a heart beat (i.e., one cardiac cycle). As shown in  FIG. 9B , it is to be appreciated that an EKG can include a plot of the variation of the electrical activity over a period of time (i.e., multiple cardiac cycles). 
     Each portion of a heartbeat produces a difference deflection on the EKG waveform  902 . These deflections are recorded as a series of positive and negative waves, namely, waves P, Q, R, S, and T. The Q, R, and S waves comprise a QRS complex  904 , which indicates rapid depolarization of the right and left heart ventricles. The P wave indicates atrial depolarization and the T wave indicates atrial repolarization. Each wave can vary in duration, amplitude and form in different individuals. In a normal EKG, the R wave can be the peak of the QRS complex  904 . 
     Other signal features include wave durations or intervals, namely, PR interval  906 , PR segment  908 , ST segment  910  and ST interval  912 , as shown in  FIG. 9A . The PR interval  906  is measured from the beginning of the P wave to the beginning of the QRS complex  904 . The PR segment  908  connects the P wave and the QRS complex  904 . The ST segment  910  connects the QRS complex  904  and the T wave. The ST interval  912  is measured from the S wave to the T wave. It is to be appreciated that other intervals (e.g., QT interval) can be identified from the EKG waveform  902 . Additionally, beat-to-beat intervals (i.e., intervals from one cycle feature to the next cycle feature), for example, an R-R interval (i.e., the interval between an R wave and the next R wave), may also be identified.  FIG. 9B  illustrates a series of cardiac waveforms over a period of time indicated by element  914 . In  FIG. 9B  the R waves are indicated by the peaks  916 ,  918  and  920 . Further, R-R intervals are indicated by elements  922  and  924 . 
     Referring again to  FIG. 7 , in one embodiment, determining a signal feature includes determining the signal feature as an R wave of an EKG signal. For example, the R wave of the EKG waveform  902 . It is appreciated that the signal feature could also be one or more waves P, Q, R, S, and T or one or more of the intervals described above. 
       FIG. 10A  illustrates another embodiment of a cardiac waveform  1002  of an acoustic signal representing cardiac activity generated or processed from a sensor, for example, a sonic or vibrational sensor. In particular, the cardiac waveform  1002  represents the sound of aortic blood flow. The cardiac waveform  1002  can include signal features similar to the cardiac waveform  902 . Exemplary signal features can include a peak  1004  or another wave duration, peak, feature of the cardiac waveform  1002 . Specifically, the signal feature reoccurs in the signal over a period of time. For example,  FIG. 10B  illustrates an acoustic signal  1006  having a series of cardiac waveforms (i.e., the cardiac waveform  1002 ) with a series of peaks  1008 ,  1010 ,  1012 . The peaks  1008 ,  1010 , and  1012  are an exemplary signal feature that reoccurs in the acoustic signal  1006  over a period of time. It is appreciated that other characteristics of the cardiac waveform  1002  and/or the acoustic signal  1006  can also be identified as a signal feature. For example, peak intervals  1014  and  1016 . 
       FIG. 10C  illustrates a cardiac waveform  1018  from an optical signal representing a measurement of cardiac activity. The optical signal can be a photoplethsymograph (PPG) signal generated from a photoelectric sensor, an optical sensor or a PPG device. The cardiac waveform  1018  is a PPG signal representing a measurement of pulsatile blood flow. The cardiac waveform  1018  can include signal features similar to the cardiac waveform  902 . Exemplary signal features can include a peak  1020  or another wave duration, peak, feature of the waveform  1018 . Specifically, the signal feature reoccurs in the signal over a period of time. For example,  FIG. 10D  illustrates an optical signal  1022  having a series of cardiac waveforms (i.e., the cardiac waveform  1018 ) with a series of peaks  1024 ,  1026 ,  1028 . The peaks  1024 ,  1026 , and  1028  are an exemplary signal feature that reoccurs in the optical signal  1022  over a period of time. It is appreciated that other characteristics of the cardiac waveform  1018  and/or the optical signal  1022  can also be identified as a signal feature. For example, peak intervals  1030  and  1032 . 
     Referring back to step  704  of  FIG. 7 , determining at least one signal feature may include determining a time occurrence of the signal feature. The time occurrence of each signal feature in the signal may be stored in a memory  608  as a vector. For example, the time occurrence of each R wave of the EKG signal may be stored and expressed in vector form as:
 
 T   0,i   =t   0,0   ,t   0,1 . . .    t   0,i  where  t   0,i  is the time of observance of the  R  wave component of the QRS complex and 0≤ i≤N.   (1)
 
     For simplicity, the expressions (1)-(4) discussed herein are with reference to the R wave of the cardiac waveform  902  (EKG waveform) as a signal feature. It is to be appreciated that the signal feature could be any signal feature identified in other types of signals as discussed above. For example, t 0,i  could also indicate a time observance of a peak  1004  of a cardiac waveform  1002  or a peak  1020  of a cardiac waveform  1018 . It is also appreciated that each expression may contain multiple elements of calculations derived from a signal. The elements can be stored, for example in a memory  608 , in vector form. 
     At step  706 , the method includes determining a first interval between two successive signal features. In another embodiment, a first interval is an interval between two successive features of each one of the heart beats of the signal. Successive features, as used herein, refer to signal features that follow each other or are produced in succession. For example, a first interval can be an interval between a first R wave and a second R wave of the EKG signal (i.e., R-R interval), where the second R wave is the next successive R wave to the first R wave. With reference to  FIG. 9B , a first interval can be an interval  922  measured from the peak  916  and to the peak  918 . A first interval can also be an interval  924  measured from the peak  918  to the peak  920 . Thus, it is appreciated that a signal can include a plurality of first intervals between a plurality of signal features. 
     In another example shown in  FIG. 10B , a first interval can be an interval  1014  measured from the peak  1008  to the peak  1010 . A first interval can also be an interval  1016  measured from the peak  1010  to the peak  1012 . In another example shown in  FIG. 10D , a first interval can be an interval  1030  measured from the peak  1024  to the peak  1026 . A first interval can also be an interval  1032  measured from the peak  1026  and to the peak  1028 . With respect to the expressions (1)-(2), a plurality of first intervals for an EKG signal can be expressed in vector form as:
 
 T   1,i   =t   1,1   ,t   1,2 . . .    t   1,i  where  t   1,i   ≡t   0,1   −t   0,i−1  and 1≤ i≤N.   (2)
 
     At step  708 , the method includes determining a second interval between two successive first intervals. In one embodiment, the interval determination module  620  can determine the first interval and the second interval. In one example, the second interval is an interval, or a difference, between successive R-R intervals. For example, a second interval can be the difference between the absolute value of a first R-R interval and the absolute value of a second R-R interval, where the second R-R interval is the next successive R-R interval to the first R-R interval. With reference to  FIG. 9B , the second interval can be a difference between the interval  922  and the interval  924 . In another example shown in  FIG. 10B , the second interval can be a difference between the interval  1014  and the interval  1016 . In a further example shown in  FIG. 10D , the second interval can be a difference between the interval  1030  and the interval  1032 . It is understood that a signal can include a plurality of second intervals defined by a plurality of first intervals. With respect to expressions (1)-(2), this difference can be expressed in vector form as:
 
 T   2,i   =t   2,2   ,t   2,3 . . .    t   2,i  where  t   2,i   ≡└t   1,i   ┘−└t   1,i−1 ┘ and 2≤ i≤N.   (3)
 
     At step  710 , the method includes calculating a derivative based on the second interval. In one embodiment, the derivative calculation module  6022  is configured to calculate the derivative. The derivative can be calculated as the second interval divided by the period of time. With respect to expressions (1)-(3), the derivative can be expressed in vector form as: 
     
       
         
           
             
               
                 
                   
                     
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     At step  712 , the method includes identifying changes in the driver state based on the derivative. The identification module  6024  can be configured to manipulate the data from expressions (1)-(4) in various ways to identify patterns and metrics associated with the driver state. In one embodiment, identifying the changes in the driver state further includes extracting a series of contiguous heart rate accelerations or decelerations based on the derivative. More specifically, the derivative T 3  of the heart rate can be sorted and flagged according to the sign of the derivative T 3 . The sign of the derivative indicates whether the heart rate is accelerating or decelerating. Where the sign of the derivative is the same for a given number of successive derivatives (T 3 ), contiguous periods of heart rate acceleration or deceleration can be identified. The contiguous periods of heart rate acceleration or deceleration can correlate to a change in a driver state. In particular, a series of contiguous heart rate accelerations and a series of contiguous heart rate decelerations correlate to bursts of sympathetic (S) and parasympathetic (PS) activity respectively. Thus, by sorting and flagging contiguous time periods of heart rate acceleration and deceleration, driver state changes associated with bursts of S and PS activity can be identified and sorted. 
     In another embodiment, identifying changes in the driver state further includes calculating a threshold based on a count of the contiguous heart rate accelerations or decelerations in a particular series. For example, a threshold of 7 is associated with 7 contiguous heart rate accelerations or decelerations. 
     Accordingly, the above described monitoring system  612  can be an exemplary monitoring system as shown in  FIG. 3 . In one embodiment, monitoring system  612  can be a heart rate monitoring system  302 . The monitoring system  612  can provide monitoring information, for example, a series of contiguous heart rate accelerations or decelerations based on the derivative and/or identification of contiguous periods of heart rate acceleration or deceleration, to determine a driver state. These functional or structural variations in heart rate information can indicate biological system activity levels (e.g., parasympathetic and sympathetic activity levels of the autonomic nervous system), which can provide accurate measurements of a driver state or a transition from one driver state to another driver state 
     It is appreciated that other exemplary vehicle systems and monitoring systems, including the sensors, sensor placement, sensor configuration, and sensor analysis, described with reference to  FIGS. 6-10 , can be implemented with the motor vehicle  100  of  FIG. 1 , the vehicle systems  126  and the monitoring systems of  FIG. 3 . The exemplary systems and methods described with reference to  FIGS. 6-10  can be used to monitor the driver  102  in the motor vehicle  100  and determine one or more driver states and/or a combined driver state index, which will be described in more detail herein. 
     c.) System and Method for Biological Signal Analysis 
     In one embodiment, the heart rate monitoring system  302  includes heart rate sensors  304  that facilitate systems and methods to acquire a true biological signal analysis, as discussed in U.S. Pat. No. 9,398,875, entitled A System and Method for Biological Signal Analysis, filed on Nov. 7, 2013, which is incorporated by reference in its entirety herein. As will be discussed, indicators of aortic blood flow, average heart rate, heart rate variability, and beat-to-beat interval can be used to infer levels of sympathetic and parasympathetic nervous system activity. This information can be used to determine one or more driver states. The &#39;710 application will now be discussed, however, for brevity, the &#39;710 application will not be discussed in its entirety. 
     In a vehicle environment, various interfaces exist to determine autonomic tone (e.g., levels of sympathetic and parasympathetic nervous system activity) of a driver. For example, an interface can acquire different biological signals (e.g., indicating aortic blood flow, average heart rate, heart rate variability, and beat-to-beat interval.) from a driver and analyze the biological signals to determine an estimation of autonomic tone. The vehicle environment, specifically, noise and vibrations from engine idling, road travel, among other sources, can interfere with the acquisition and analysis of biological signals in the vehicle and therefore influence the estimation of autonomic tone. 
     In one embodiment, a system for biological signal analysis includes one or more multidimensional sensor arrays. Referring now to  FIG. 11 , a system  1100  for biological signal analysis can be implemented alone or in combination with a computing device  1102  (e.g., a controller, a navigation system, an infotainment system, etc.). Thus, for example, the computing device  1102  can be implemented within the ECU  106  of  FIGS. 1A and 1B , the vehicle systems  126  and/or the monitoring systems of  FIG. 3 . The computing device  1102  includes a processor  1104 , a filter  1106 , a memory  1108 , a disk  1110  and an input/output (I/O) interface  1112 , which are operably connected for computer communication via a bus  1114  and/or other wired and wireless technologies. It is understood that these components can be similar to the components of the ECU  106 , for example, the processor  108 , the memory  110 , the disk  112 , the communication interface  114 , and the data bus  118 . Accordingly, it is understood that the ECU  106  can perform some or all of the functions of the computing device  1102 . 
     In one embodiment, the computing device  1102  also includes a multiplexor  1116 . In one embodiment, the filter  1106  can include the multiplexor  1116 . In another embodiment, the multiplexor  1116  can be implemented externally from the filter  1106  and/or the computing device  1102 . In a further embodiment, the I/O interface  1112  can include the multiplexor  1116 . 
     In the illustrated embodiment of  FIG. 11 , the system  1100  also includes a multidimensional sensor array  1118 . In another exemplary embodiment, the system  1100  includes more than one multidimensional sensor array. For example, in the illustrated embodiment shown in  FIG. 11 , the computing device  1102  can include a second multidimensional sensor array  1120  and a third multidimensional sensor array  1122 . It will be appreciated that the systems and methods discussed herein can be implemented with any number of multidimensional sensor arrays (e.g., two multidimensional sensor arrays or more than three multidimensional sensor arrays). Further, although some embodiments and examples discussed herein refer to the multidimensional sensor array  1118 , it will be appreciated that the second multidimensional sensor array  1120  and the third multidimensional sensor array  1122  provide similar functionality as the multidimensional sensor array  1118 . The multidimensional sensor arrays can include similar functionality and can be implemented similarly to the sensors and sensing devices included in the monitoring systems of  FIG. 3  and other exemplary monitoring systems discussed herein. 
     The multidimensional sensor array  1118  will now be described in further detail and with regard to an embodiment associated with a vehicle (e.g., the motor vehicle  100 ,  FIG. 1A ). It should be noted that another embodiment could be applied to a seat outside a vehicle, such as a chair or a bed. The multidimensional sensor array  1118  is disposed at a position for sensing biological data associated with a driver. For example, the multidimensional sensor array  1118  could be disposed at a position on or within the vehicle seat  168  of  FIG. 1A . The multidimensional sensor array  1118  includes a plurality of sensors each of which are mechanically coupled to a common structural coupling material.  FIG. 12  illustrates a top schematic view of an exemplary multidimensional sensor array generally shown by reference numeral  1200 . Similarly,  FIG. 13  illustrates an orthographic view of the multidimensional sensor array of  FIG. 12   
     As shown in  FIGS. 12 and 13 , the multidimensional sensor array  1200  includes a plurality of sensors M 1 , M 2 , M 3  and M 4 . It will be appreciated that in some embodiments, the multidimensional sensor array  1200  can include other numbers of sensors, for example, two sensors or more than four sensors. In the embodiment illustrated in  FIGS. 12 and 13 , the sensors M 1 , M 2 , M 3 , and M 4  are acoustic sensors, for example, microphones. Accordingly, the sensors M 1 , M 2 , M 3  and M 4  are configured to sense an acoustic measurement (e.g., a stimulus) of biological data associated with a person and generate a data stream or a raw data signal (e.g., output) representing the acoustic measurement. Biological data can include, but is not limited to, data associated with the heart (e.g., aortic blood flow, average heart rate, heart rate variability, and beat-to-beat interval), the lungs (e.g., respiratory rate), and other biological systems of the human body. 
     In the illustrated embodiments of  FIGS. 12 and 13 , the sensors M 1 , M 2 , M 3 , and M 4  are mechanically coupled to a common structural coupling material  1202 . The common structural coupling material  1202  provides a connection in a non-electrical manner between the sensors M 1 , M 2 , M 3 , and M 4 . The mechanical coupling allows for distribution of ambient mechanical vibrations (e.g., engine noise, road noise) equally to each of the sensors M 1 , M 2 , M 3 , and M 4 . In one embodiment, the common structural coupling material  1202  is a circuit board upon which the sensors M 1 , M 2 , M 3  and M 4  are fixed (e.g., via adhesives, bonding, pins). In another embodiment, the common structural coupling material  1202  is a bracket or includes one or more brackets upon which the sensors M 1 , M 2 , M 3  and M 4  are fixed (e.g., via adhesives, bonding, pins). It will be appreciated that other materials can be used as the common structural coupling material  1202 . In particular, other materials with a high modulus of elasticity and a low density can be used as the common structural coupling material  1202 . 
     By mechanically coupling the acoustic sensors M 1 , M 2 , M 3  and M 4  to a common structural coupling material  1202 , ambient mechanical vibrations from, for example, the external environment impacts each sensor M 1 , M 2 , M 3  and M 4  equally. As an illustrative example in the context of a vehicle (e.g.,  FIG. 1A ), vibrations from the vehicle environment (e.g., engine noise, road noise), impact each sensor M 1 , M 2 , M 3  and M 4  equally due to the mechanical coupling provided by the common structural coupling material  1202 . When the output (e.g., raw signals) from sensors M 1 , M 2 , M 3  and M 4  are processed and/or filtered, as will later be discussed), the vibrations can be eliminated from the raw signals as a common mode. 
     As shown in  FIGS. 13 and 14 , the multidimensional sensor array  1200  has a geometric center  1204  and a center of mass  1206 . The center of mass  1206  is located external to an area bounded by the plurality of sensors. Specifically, the sensors M 1 , M 2 , M 3  and M 4 , which are mechanically coupled to the common structural coupling material  1202 , are provided (i.e., positioned) so as to define the center of mass  1206  external to the area bounded by the plurality of sensors. Specifically, the center of mass  1206  is located external to an area  1208 , which is an area bounded by the sensors M 1 , M 2 , M 3  and M 4 . The area  1208  is defined by a position of each of the plurality of sensors M 1 , M 2 , M 3  and M 4  and a geometric center  1210  of the plurality of sensors M 1 , M 2 , M 3 , and M 4 . In one embodiment, the center of mass  1206  is created by a weighted portion  1212  of the multidimensional sensor array  1200 . The weighted portion  1212 , in one embodiment, is implemented by a power source (not shown) positioned on the multidimensional sensor array  1200 . In a further embodiment, the center of mass  1206  is created by providing the multidimensional sensor array in a curved shape configuration (not shown). By providing the center of mass  1206  at a location external to the geometric center  1210  of the plurality of sensors M 1 , M 2 , M 3  and M 4 , the ambient mechanical vibration (i.e., noise) registers in each of the plurality of sensors M 1 , M 2 , M 3  and M 4 , in plane (i.e., in phase) with respect to each other. 
     More specifically, ambient mechanical vibrations are transferred from the vehicle to the multidimensional sensor array  1200 . Generally, the ambient mechanical vibrations manifest as linear motion along a horizontal axis (X) direction and a vertical axis (Y) direction of the multidimensional sensor array  1200 , and in a rotational motion about the horizontal axis (X) and the vertical axis (Y) of the multidimensional sensor array  1200 .  FIG. 13  illustrates a Y, X and Z axes with respect to the multidimensional sensor array  1200  and the center of mass  1206 . The mechanical coupling with respect to each of the sensors M 1 , M 2 , M 3 , and M 4 , causes each of the sensors M 1 , M 2 , M 3 , and M 4  to move in-phase with regards to the vibrational linear motion. 
     With regards to the vibrational rotational motion, the positioning of each of the sensors M 1 , M 2 , M 3 , and M 4  with respect to the center of mass  1206  will now be discussed in more detail. Rotational motion about the horizontal (X) axis is proportional to the magnitude of the vibration multiplied by the moment arm Y. As shown in  FIG. 12 , each of the sensors M 1 , M 2 , M 3 , and M 4  define the geometric center  1210 . The moment arm Y is the vertical distance of the geometric center  1210  from the vertical axis (i.e., Y coordinate) of the center of mass  1206 . Further, a distance y 1  is a vertical distance from an axis of the sensors M 3 , M 4  and the center of mass  1206  and a distance y 2  is a vertical distance from an axis of the sensors M 1 , M 2  and the center of mass  1206 . By positioning each of the sensors M 1 , M 2 , M 3  and M 4  so that the ratio of dy/Y is small, then y 1  is approximately equal to y 2  and the ambient mechanical vibrations registered by each of the sensors M 1 , M 2 , M 3  and M 4  are approximately in phase. The ambient mechanical vibrations can then be processed using filtering techniques that will be discussed in further detail herein. Additionally, rotational motion about the vertical (Y) axis is proportional to the magnitude of the vibration multiplied by a moment arm dx. By positioning each of the sensors M 1 , M 2 , M 3  and M 4  so that dx (i.e. the difference between the geometric center  1210  and the axis of each of the sensors) is small, the ambient mechanical vibrations registered by each of the sensors M 1 , M 2 , M 3  and M 4  can also be processed using filtering techniques that will be discussed in further detail herein. 
     Accordingly, in the embodiment illustrated in  FIGS. 12 and 13 , at least one sensor is positioned along the Y axis with a short and a long moment arm and at least one sensor is positioned along the X axis with an x moment arm on either side of the Y axis. For example, M 1  and M 2  are positioned along the Y axis with a short and a long moment arm and M 3  and M 4  are positioned along the X axis with an x moment arm on either side of the Y axis. According to an embodiment described herein, the processing of the output of each of the sensors is based on the sensor pairs (i.e., M 2 , M 3  and M 1 , M 4 ) described above. Specifically, the sensors are positioned so that during processing, which is discussed herein, operational amplification adds the motions with the moment arm dx in out of phase combinations. Thus, M 1  and M 4  are positioned on opposite sides of the Y axis and M 2  and M 3  are positioned on opposite sides of the Y axis. This allows each additive pair to consist of one sensor moving in each direction about the Y axis with moment arm dx allowing for cancellation using common mode with differential amplification. If both sensors in a pair are on the same side of the Y axis, the rotary noise from rotation about the Y axis with moment X will not cancel with differential amplification but will double instead because they are 180 degrees out of phase before subtraction. 
     Referring again to  FIG. 12 , in one embodiment, the multidimensional sensor array further includes one or more clusters. Each of the plurality of sensors M 1 , M 2 , M 3 , and M 4  of the multidimensional sensor array  1200  can be associated with the one or more clusters. For example, in the illustrated embodiment of  FIG. 12 , the area  1208  can be considered a cluster in which sensors M 1 , M 2 , M 3 , and M 4  are associated. In another embodiment, which will be discussed herein, sensors M 1  and M 3  can be associated with a first cluster and sensors M 3  and M 4  can be associated with a second cluster. It will be appreciated that the multidimensional sensor array  1200  can include any number of clusters (e.g., one cluster or more than two clusters). The clusters may or may not be associated with a specific location (e.g., position) of the sensor on the common structural coupling material  1202 . Further, the clusters can be predefined and associated with any combination of sensors. 
     Non-limiting examples of clusters and sensors associated with said clusters will now be discussed. In one embodiment, a sensor array, including more than one sensor, can be associated with a cluster. In a further embodiment, the clusters can be a pattern of sensors or an array of sensors (as discussed above). In another embodiment, the clusters are predefined based on the position of the sensors or the output of the sensors. In an additional embodiment, which will be described herein, the multiplexor  1116 , can determine the clusters based on a location of the multidimensional sensor array, a location of each sensor in the multidimensional sensor array, and/or the output (e.g., the raw data signal output) of each sensor. Further, a cluster can be determined and/or a sensor can be associated with a cluster based on the positioning of the sensors. In one embodiment, a cluster can include at least one sensor positioned along the Y axis with a short and long moment arm and at least one sensor position along the X axis with an x moment arm on either side of the Y axis. Thus, with reference to  FIG. 12 , a first cluster can include M 2 , M 3  and a second cluster can include M 1 , M 4 . It will be appreciated that other combinations and sensor pairs can be associated with a cluster. 
     As mentioned above, the multidimensional sensor array  1118  and the system  1100  of  FIG. 11  can be implemented within a vehicle, for example, the motor vehicle  100  of  FIG. 1A . In one embodiment, the system  1100  of  FIG. 11  can be used for biological signal analysis of the driver  102  to determine an arousal level or autonomic tone of the driver  102 . The arousal level or autonomic tone can be used to determine one or more driver states.  FIG. 14  illustrates a simplified view of the motor vehicle  100 , the driver  102 , and the vehicle seat  168 . Further,  FIG. 14  illustrates another exemplary embodiment of sensor placement in the vehicle seat  168 . For convenience, like numerals in  FIGS. 1A and 14  represent like elements. As discussed above with  FIG. 1A , the driver  102  is seated in the vehicle seat  168  of the motor vehicle  100 . The vehicle seat  168  includes a lower support  170 , a seat back support  172  (e.g., a backrest) and a headrest  174 , although other configurations of the vehicle seat  168  are contemplated. 
     The vehicle seat  168  can also include a seat belt (See, for example, the seat belt  404  of  FIG. 4  including a lap belt portion  414  and a sash belt portion  416 ). In the embodiment illustrated in  FIG. 14 , the elements  1402   a ,  1402   b ,  1402   c  indicate positions for sensing biological data associated with the driver  102 . Specifically, a multidimensional sensor array or more than one multidimensional sensor array (e.g., the multidimensional sensor array  1118 , the second multidimensional sensor array  1120  and/or the third multidimensional sensor array  1122  can be disposed at said positions  1402   a ,  1402   b ,  1402   c  for sensing biological data associated with the driver  102 . 
     In particular, in  FIG. 101 , the positions  1402   a ,  1402   b ,  1402   c  are located within the seat back support  172 . However, it will be appreciated, the positions can be in other areas of the vehicle seat  168  (e.g., seat belt (not shown)) or around the vehicle seat  168  to allow the multidimensional sensor array disposed at said position to sense biological data associated with the driver  102 . For example, in one embodiment, the multidimensional sensor array is disposed at a position for sensing biological data associated with a thoracic region of the driver occupying the vehicle. In  FIG. 14 , the elements  1404   a ,  1404   b  and  1404   c , indicate thoracic regions of the driver  102 . Specifically, the elements  1404   a ,  1404   b , and  1404   c  indicate an upper cervico-thoracic region, a middle thoracic region and a lower thoraco-lumbar region respectively of the thorax of the driver  102 . Accordingly, in  FIG. 14 , the element  1402   a  indicates a position at which a multidimensional sensor array is disposed, wherein the position is proximate to an upper cervico-thoracic region  1404   a  of the driver  102 . Additionally, the element  1404   b  indicates a position at which a multidimensional sensor array is disposed, wherein the position is proximate to a middle thoracic region  1404   b  of the driver  102 . Further, the element  1402   c  indicates a position at which a multidimensional sensor array is disposed, wherein the position is proximate to a lower thoraco-lumbar region  1404   c  of the driver  102 . 
     It will be appreciated that other positions other than the positions  1404   a ,  1404   b , and  1404   c  can be positions proximate to an upper cervico-thoracic region  1404   a , a middle thoracic region  1404   b , and/or a lower thoraco-lumbar region  1404   c . For example, in one embodiment, the multidimensional sensor array can be located in one or more positions in a seat belt (not shown) that are proximate to an upper cervico-thoracic region  1404   a , a middle thoracic region  1404   b , and/or a lower thoraco-lumbar region  1404   c  of the driver  102 . In another embodiment, the position can be proximate to an axillary region. Other numbers of multidimensional sensor arrays disposed in other positions or combinations of positions can also be implemented. 
     Further, it will be appreciated that one or more multidimensional sensor arrays can be provided and/or disposed at a position for sensing biological data based on the biological data and/or the biological signal. Different positions can correlate with specific biological data or provide the best position for measuring and/or collection of said biological data. For example, a multidimensional sensor array disposed at a position proximate to an upper cervico-thoracic region  1404   a  can be utilized to obtain a signal associated with heart rate, while a position proximate to a lower thoraco-lumbar region  1404   c  can be utilized to obtain a signal associated with aortic pulse wave. Thus, for example, during processing, the multiplexor  1116  ( FIG. 11 ) can selectively retrieve or obtain output from a sensor or a multidimensional sensor array based on the biological data to be obtained, the position of the multidimensional sensor array and/or a cluster associated with each sensor. 
     With regards to processing and analysis, the filter  1106  and the multidimensional sensor array  1118  of  FIG. 11 , will now be will now be described in detail with reference to  FIG. 15 , which illustrates an exemplary electric circuit diagram  1500 . It will be appreciated that other electric circuit configurations can be implemented, however, for purposes of simplicity and illustration, the electric circuit diagram  1500  has been organized into a sensing portion  1502  (e.g., a multidimensional sensor array  1118 ) and a filtering portion  1504  (e.g., a processor  1104  and/or a filter  1106 ). Further, the electric circuit diagram includes a multiplexor  1506  (e.g., the multiplexor  1116  in  FIG. 11 ), which can be implemented with the sensing portion  1502  and/or the filtering portion  1504 . 
     The sensing portion  1502  includes acoustic sensors (i.e., microphones) M 1 , M 2 , M 3  and M 4 . Similar to  FIG. 12 , the sensors M 1 , M 2 , M 3 , and M 4  are mechanically coupled to a common structural coupling material (not shown in  FIG. 15 ). Although four acoustic sensors are illustrated in  FIG. 15 , other embodiments can include any number of sensors (e.g., less than four or more than four). In the embodiment illustrated in  FIG. 15 , each acoustic sensor M 1 , M 2 , M 3  and M 4  is biased at one tenth a supply voltage by a voltage divider circuit formed from resistors R 1  and R 2  via pull-up resistors Rp 1 , Rp 2 , Rp 3 , and Rp 4 . In some embodiments, the voltage is supplied to the multidimensional sensor array by a standard DC power supply (not shown). As discussed above with  FIG. 12 , the standard DC power supply could be implemented as a weighted portion  1212 . The acoustic sensors M 1 , M 2 , M 3 , and M 4  sense an acoustic measurement indicating biological data associated with a driver. The acoustic measurement is determined by the voltage drop between the pull-up resistors Rp 1 , Rp 2 , Rp 3  and R 4  and the associated acoustic sensor to generate an output (e.g., a raw data signal). For example, Vm 1  is an output signal indicating a voltage measurement registered by the voltage drop between M 1  and Rp 1 . Vm 2  is an output signal indicating a voltage measurement registered by the voltage drop between M 2  and Rp 2 . Vm 3  is an output signal indicating a voltage measurement registered by the voltage drop between M 3  and Rp 3 . Vm 4  is an output signal indicating a voltage measurement registered by the voltage drop between M 4  and Rp 4 . It will be appreciated that other configurations of voltage biasing and impedance matching can also be implemented with the methods and systems described herein. Further, other types of microphones and/or acoustic sensors, other than electret condenser microphones, can also be implemented. For example, other microphones can include but are not limited to, cardioids, unidirectional, omnidirectional, micro-electromechanical, and piezoelectric. It will be appreciated that other microphones may require different types of biasing and impedance matching configurations. 
     In one embodiment, each of the plurality of sensors M 1 , M 2 , M 3 , and M 4  are associated with one or more clusters. In particular, in  FIG. 13 , the cluster can include at least one sensor positioned along the Y axis with a short and long moment arm and at least one sensor position along the X axis with an x moment arm on either side of the Y axis. Similarly, another cluster can include at least one sensor positioned along the Y axis with a short and long moment arm and at least one sensor position along the X axis with an x moment arm on either side of the Y axis. 
     In one embodiment, the output signals Vm 1 , Vm 2 , Vm 3  and Vm 4  are processed (e.g., via the filtering portion  1504 ) based on the clusters and/or the positioning of each of the sensors. Specifically, the sensors M 2  and M 3  are connected to one half of an operational amplifier Amp 1  via an RC couple R 1  and C 1 . The output signals Vm 2  and Vm 3  are processed by the Amp  1 . Specifically, in this example, the RC couple provides a single pole of high pass filtering at a frequency of 0.34 Hz. The Amp 1  is coupled through an output lead via a parallel RC circuit to produce a second pole of low pass filtering at 3.4 Hz with a gain of R 2 /R 1 =1 V/V. The output of the Amp 1  is a summation of the output of M 2  and M 3 , equal to Vm 2 +Vm 3  filtered at 0.34-3.4 Hz. 
     Similarly, the sensors M 1  and M 4  are also connected to one half of an operational amplifier Amp 2  via an RC couple R 1  and C 1 . The output signals Vm 1  and Vm 4  are processed by the Amp  2 . Specifically, the RC couple provides a single pole of high pass filtering at a frequency of 0.34 Hz. The Amp 2  is coupled through an output lead via a parallel RC circuit to produce a second pole of low pass filtering at 3.4 Hz with a gain of R 2 /R 1 =1 V/V. The output of Amp 2  is a summation of the output of M 1 , M 4 , equal to Vm 1 +Vm 4  filtered at 0.34-3.4 Hz. 
     Further, the output of each operational amplifier Amp 1 , Amp 2  is fed to a differential bioinstrumentation amplifier Amp 3  configured to deliver a gain of 5000/Rg=50000/10=5000 V/V. The Amp 3  can provide noise cancellation of the output of the sensors M 1 , M 2 , M 3 , and M 4 . In particular, and as discussed above with  FIG. 99 , due to the mechanical coupling of the sensors M 1 , M 2 , M 3  and M 4 , the positioning of the sensors M 1 , M 2 , M 3  and M 4  and the positioning of the center of mass of the multidimensional sensor array, environmental vibrations impact each sensors M 1 , M 2 , M 3  and M 4  equally. Therefore, the Amp 3  can remove the environmental vibrations from the output signal of each operational amplifier Amp 1 , Amp 2 , as a common mode. The output signal of the differential bioinstrumentation amplifier Amp 3  is equal to GX[(Vm 2 +Vm 3 )−(Vm 1 +Vm 4 )] filtered. The output signal of the differential bioinstrumentation amplifier Amp 3  represents a biological signal that can be further analyzed (e.g., by the processor  1104 ) to determine autonomic tone and a level of impairment of the driver  102 . With reference to  FIG. 15 , by adding together sensor pairs containing both a short moment arm y 1  and a long moment arm y 2  (i.e. Vm 2 +Vm 3  and Vm 1 +Vm 4 ), the differential effects of the differences in the moment arm become common mode and cancel with differential amplification. Likewise, in choosing sensor pairs in this fashion, the out of plane motion that occurs with rotation about the Y axis with moment arm dx also becomes common mode and cancels out with differential amplification. 
     As described above, the filter  1106  can include various amplifiers (Amp 1 , Amp 2 , Amp 3 ) for processing. It will be appreciated that other types of filters and amplifiers can be implemented with the systems and methods discussed herein. For example, band pass filters, phase cancelling filters, among others. It addition to amplification, the filter  1106  can include a multiplexor  1116  for selectively receiving the output from each of the plurality of sensors and/or selectively forwarding the output from each of the plurality of sensors for processing. In one embodiment shown in  FIG. 15 , multiplexor  1506  can selectively receive and/or obtain an output of a sensor from the plurality of sensors M 1 , M 2 , M 3 , M 4  of the multidimensional sensor array  1118  for further processing by the Amp 1 , Amp  2  and/or Amp 3  based on a predefined factor. For example, the output can be selected based on a position of a sensor, a position of the multidimensional sensor array, a cluster, a signal to noise ratio of the output, among other factors. In one embodiment, the multiplexor can selectively receive output from a single sensor, more than one sensor from a single cluster or more than one cluster. In another embodiment, the multiplexor  1506  can predefine a cluster based on a predefined factor, for example, a position of a sensor, a position of a multiplexor, a signal to noise ratio of the output, among other factors. In an embodiment including more than one multidimensional sensor array, the multiplexor  1506  can selectively receive and/or forward output of each of the plurality of sensors from each of the multidimensional sensor array for further processing by the Amp 1 , Amp  2  and or Amp 3  based on a predefined factor. For example, a position of the multidimensional sensor array, a position of a sensor, a signal to noise ratio of the output, among other factors. 
     Further, in some embodiments, the multiplexor  1506  can selectively output to, for example, the processor  1104 , a biological signal based on a predefined factor for use in algorithms and processes for determining autonomic tone and/or a level of impairment of the driver  102 . For example, the biological signal can be outputted based on a signal-to-noise ratio, a biological data type, or a position of the multidimensional sensor array, among others. As can be appreciated, various combinations of output from one or more multidimensional sensor arrays and each of the plurality of sensors are contemplated. By providing a multidimensional sensor array with a plurality of sensors mechanically coupled via a common structural coupling material and processing the output of the sensors based on regional differences as discussed above with  FIG. 15 , a high quality biological signal can be obtained in a vehicle while the engine is running. This biological signal can be used to determine one or more driver states as will be discussed herein. 
     It is also appreciated that other exemplary vehicle systems and monitoring systems, including the sensors, sensor placement, sensor configuration and sensor analysis, described with reference to  FIGS. 11-15 , can be implemented with the motor vehicle  100  of  FIG. 1A , the vehicle systems  126  and the monitoring systems of  FIG. 3 . The exemplary systems and methods described with reference to  FIGS. 11-15  can be used to monitor the driver  102  in the motor vehicle  100  and determine one or more driver states and/or a combined driver state index, which will be described in more detail herein. 
     ii. Other Monitoring Systems, Sensors and Signal Processing 
     Referring again to  FIG. 3  other exemplary monitoring systems will now be described. The motor vehicle  100  can also include a respiratory monitoring system  312 . The respiratory monitoring system  312  could include any devices or systems for monitoring the respiratory function (e.g. breathing) of a driver. For example, the respiratory monitoring system  312  could include sensors disposed in a seat for detecting when a driver inhales and exhales. In some embodiments, the motor vehicle  100  could include a perspiration monitoring system  314 . The perspiration monitoring system  314  can include any devices or systems for sensing perspiration or sweat from a driver. In some embodiments, the motor vehicle  100  could include a pupil dilation monitoring system  316  for sensing the amount of pupil dilation, or pupil size, in a driver. In some cases, the pupil dilation monitoring system  316  could include one or more optical sensing devices, for example, the optical sensing device  162 . 
     Additionally, in some embodiments, the motor vehicle  100  can include a brain monitoring system  318  for monitoring various kinds of brain information. In some cases, the brain monitoring system  318  could include electroencephalogram (EEG) sensors  320 , functional near infrared spectroscopy (fNIRS) sensors  322 , functional magnetic resonance imaging (fMRI) sensors  324 , as well as other kinds of sensors capable of detecting brain information. Such sensors could be located in any portion of the motor vehicle  100 . In some cases, sensors associated with the brain monitoring system  318  could be disposed in a headrest. In other cases, sensors could be disposed in the roof of the motor vehicle  100 . In still other cases, sensors could be disposed in any other locations. 
     In some embodiments, the motor vehicle  100  can include a digestion monitoring system  326 . In other embodiments, the motor vehicle  100  can include a salivation monitoring system  328 . In some cases, monitoring digestion and/or salivation could also help in determining if a driver is drowsy. Sensors for monitoring digestion information and/or salivation information can be disposed in any portion of a vehicle. In some cases, sensors could be disposed on a portable device (e.g., the portable device  122 ) used or worn by a driver. 
     It is understood that the monitoring systems for physiological monitoring can include other vehicle systems and sensors discussed herein, for example, the vehicle systems and sensors discussed in Section II (A) and shown in  FIG. 2 , the behavioral monitoring systems discussed in Section III (B)(2), the vehicular monitoring systems discussed in Section III (B)(3), and the identification systems and sensors discussed in Section III (B)(4) can be types of monitoring systems for physiological monitoring. Further, it is appreciated, that any combination of vehicle systems and sensors, physiological monitoring systems, behavioral monitoring systems, vehicular monitoring systems, and identification systems can be implemented to determine and/or assess one or more driver states based on physiological information. 
     2. Behavioral Monitoring Systems and Sensors 
     Generally, behavioral monitoring systems and sensors include, but are not limited to, any automatic or manual systems and sensors that monitor and provide behavioral information related to a driver of the motor vehicle  100  (e.g., related to a driver state). The behavioral monitoring systems can include one or more behavioral sensors for sensing and measuring a stimulus (e.g., a signal, a property, a measurement, and/or a quantity) associated with the driver of the motor vehicle  100 . In some embodiments, the ECU  106  can communicate and obtain a data stream representing the stimulus from the behavioral monitoring system from, for example, a port. In other words, the ECU  106  can communicate and obtain behavioral information from the behavioral monitoring systems of the motor vehicle  100 . 
     Behavioral information includes information about the human body derived extrinsically. Behavioral information is typically observable externally to the human eye. For example, behavioral information can include eye movements, mouth movements, facial movements, facial recognition, head movements, body movements, hand postures, hand placement, body posture, and gesture recognition, among others. 
     Derived extrinsically includes sensors that measure external characteristics or movements of the human body. Typically, these types of sensors are visual and/or camera sensors that observe and measure the external characteristic. However, it is understood that behavioral sensors can be contact sensors and/or contactless sensors and can include electric current/potential sensors (e.g., proximity, inductive, capacitive, electrostatic), acoustic sensors, subsonic, sonic, and ultrasonic sensors, vibration sensors (e.g., piezoelectric), optical sensors, imaging sensors, thermal sensors, temperature sensors, pressure sensors, photoelectric sensors, among others. It is understood that the above-mentioned behavioral monitoring systems and sensors can be located in various areas of the motor vehicle  100 , including, but not limited to: a steering wheel, dashboard, ceiling, rear-view mirror as well as any other location. Moreover, in some cases the sensors can be a portable sensor that is worn by a driver, associated with a portable device located in proximity to the driver, such as a smart phone (e.g., a camera on a smart phone) or similar device, associated with an article of clothing worn by the driver or integrated into the body of the driver (e.g. an implant). 
     In some embodiments, the ECU  106  can include provisions for receiving various kinds of optical information about a behavioral state of a driver. In one embodiment, and as discussed above, the ECU  106  can include a port  160  for receiving information from one or more optical sensing devices, such as an optical sensing device  162 . The optical sensing device  162  could be any kind of optical device including a digital camera, video camera, infrared sensor, laser sensor, as well as any other device capable of detecting optical information. In one embodiment, the optical sensing device  162  can be a video camera. In another embodiment, the optical sensing device  162  can be one or more cameras or optical tracking systems, to monitor behavioral information, for example, gestures, head movement, body movement, eye/facial movement, among others. In addition, in some cases, the ECU  106  could include a port  164  for communicating with a thermal sensing device  166 . The thermal sensing device  166  can be configured to detect thermal information about a behavioral state of a driver. In some cases, the optical sensing device  162  and the thermal sensing device  166  could be combined into a single sensor. 
     Generally, one or more optical sensing devices and/or thermal sensing devices could be associated with any portion of a motor vehicle. In some cases, an optical sensing device could be mounted to the roof of a vehicle cabin. In other cases, an optical sensing device could be mounted in a vehicle dashboard. Moreover, in some cases, multiple optical sensing devices could be installed inside a motor vehicle to provide viewpoints of a driver or occupant from multiple different angles. In one embodiment, the optical sensing device  162  can be installed in a portion of the motor vehicle  100  so that the optical sensing device  162  can capture images of the upper body, face, and/or head of a driver or occupant. Similarly, the thermal sensing device  166  could be located in any portion of the motor vehicle  100  including a dashboard, roof or in any other portion. The thermal sensing device  166  can also be located to provide a view of the upper body, face and/or head of a driver. 
     Referring again to  FIG. 3 , an illustration of an embodiment of various monitoring systems  300  and sensors that could be associated with the motor vehicle  100  is shown. These monitoring systems ascertain, retrieve, and/or obtain information about a driver, and more particularly, a driver state. In some cases, the monitoring systems are autonomic monitoring systems. These monitoring systems could include one or more bio-monitoring sensors  180 . In one embodiment, the monitoring systems and sensors of  FIG. 3  can be part of a physiological monitoring system and/or a behavioral monitoring system. Thus, in some embodiments, the monitoring systems and sensors of  FIG. 3  can monitor and obtain physiological information and/or behavioral information related to state of a driver. In one exemplary embodiment, an optical sensing device could obtain behavioral information related to the head position or eye/facial movement of the driver. The same optical sensing device could also obtain physiological information related to the heart rate of the driver. Other sensors that obtain both behavioral and physiological information about the driver are also possible. 
     In some embodiments, the motor vehicle  100  could include gesture recognition and monitoring system  330 . The gesture recognition and monitoring system  330  could include any devices, sensors, or systems for monitoring and recognizing gestures of a driver. For example, the gesture recognition and monitoring system  330  could include the optical sensing device  162 , the thermal sensing device  166 , and/or other computer vision systems to obtain gesture and body information about the driver and information about the environment of the driver. This information can be in the form of images, motion measurement, depth maps, among others. The gesture recognition and monitoring system  330  can include gesture recognition and tracking software to recognize gestures, objects, and patterns based on the information. In other embodiments, the gesture recognition and monitoring system  330  could also include provisions for facial recognition and monitoring facial features. 
     In some embodiments, the motor vehicle  100  could include an eye/facial movement monitoring system  332 . The eye/facial movement monitoring system  332  could include any devices, sensors, or systems for monitoring eye/facial movements. Eye movement can include, for example, pupil dilation, degree of eye or eyelid closure, eyebrow movement, gaze tracking, blinking, and squinting, among others. Eye movement can also include eye vectoring including the magnitude and direction of eye movement/eye gaze. Facial movements can include various shape and motion features of the face (e.g., nose, mouth, lips, cheeks, and chin). For example, facial movements and parameters that can be sensed, monitored and/or detected include, but are not limited to, yawning, mouth movement, mouth shape, mouth open, the degree of opening of the mouth, the duration of opening of the mouth, mouth closed, the degree of closing of the mouth, the duration of closing of the mouth, lip movement, lip shape, the degree of roundness of the lips, the degree to which a tongue is seen, cheek movement, cheek shape, chin movement, chin shape, etc. 
     In some embodiments, components of the eye/facial movement monitoring system  332  can be combined with components of the gesture recognition and monitoring system  330  and/or the pupil dilation monitoring system  316 . The eye/facial movement monitoring system  332  could include the optical sensing device  162 , the thermal sensing device  166 , and/or other computer vision systems. The eye/facial movement monitoring system  332  can also include provisions for pattern recognition and eye/gaze tracking. 
     In some embodiments, the motor vehicle  100  could include a head movement monitoring system  334 . In some embodiments, the ECU  106  can include provisions for receiving information about a head pose (i.e., position and orientation) of the driver&#39;s head. The head pose can be used to determine what direction (e.g., forward-looking, non-forward-looking) the head of the driver is directed to with respect to the vehicle. In some embodiments described herein, the head pose can be referred to a head look. In one embodiment, the head movement monitoring system  334  provides head vectoring information including the magnitude (e.g., a length of time) and direction of the head pose. In one embodiment, if the head pose is forward-looking the driver is determined to be paying attention to the forward field-of-view relative to the vehicle. If the head pose is non-forward-looking the driver may not be paying attention. Furthermore, the head pose can be analyzed to determine a rotation of the head of the driver and a rotation (e.g., head of driver is turned) direction with respect to the driver and the vehicle (i.e., to the left, right, back, forward). It is appreciated that information related to the head pose and/or head look of the driver received from the head movement monitoring system  334  can be referred to herein as head movement information. Determination of a driver state based on head movement information from, for example the head movement monitoring system  334 , will be discussed in more detail with reference to  FIGS. 16A, 16B, and 17 . 
     For reference,  FIG. 16A  illustrates a side view of a vehicle  1602  with a vehicle coordinate system and indication of vehicle pillars A, B, C and D.  FIG. 16B  is an overhead view of the vehicle  1602  shown in  FIG. 16A  including a driver  1604  with exemplary head looking directions based on the head pose with respect to the driver and the vehicle frame. The vehicle  1602  can be similar to the motor vehicle  100  of  FIG. 1A  and the driver  1604  can be similar to the driver  102  of  FIG. 1A . Accordingly, the references described with  FIGS. 16A, 16B and 17  can be applied to the motor vehicle  100  and the driver  102  of  FIG. 1A . 
     As shown in  FIG. 16B , illustrative head looking directions of the driver are shown with respect to the driver (e.g., the head pose, the body position of the driver, posture) and the vehicle frame (e.g., vehicle coordinate system, pillars) as: forward-looking, forward right side-looking, left side-looking, right side-looking, rear left side-looking, rear right side-looking and rear-looking. It is understood that the head looking directions described herein are exemplary in nature and could include other head looking directions. Additionally, the head looking directions can be based on different elements of the vehicle frame and/or vehicle and can vary based on the driver&#39;s body pose. Further, in some embodiments, the head looking directions can be modified based on the driver. For example, identification of the driver and pattern/learning methods of the driver&#39;s normative head movements. 
     In  FIG. 16B , the forward-looking direction  1606  is between the left A pillar and the left side of the X-axis of the vehicle. The forward right side-looking direction  1608  is between the right side of the X-axis of the vehicle and the right A pillar. The left side-looking direction  1610  is between the left A pillar and a line perpendicular to the driver&#39;s body (e.g., perpendicular to the head of the driver when the head of the driver is in a forward-looking direction). The right side-looking direction  1612  is between the right A pillar and the line perpendicular to the driver&#39;s body (e.g., perpendicular to the head of the driver when the head of the driver is in a forward-looking direction). The rear left side-looking direction  1614  is between the line perpendicular to the driver&#39;s body (e.g., perpendicular to the head of the driver when the head of the driver is in a forward-looking direction) and the left B pillar. The rear right side-looking direction  1616  is between the line perpendicular to the driver&#39;s body (e.g., perpendicular to the head of the driver when the head of the driver is in a forward-looking direction) and the right B pillar. The rear-looking direction  1618  is between the right and left B pillars and can include areas around the C pillars and D pillar. 
     In some embodiments, the head looking directions shown in  FIG. 16B  can be based on a 360 degree axis of rotation between a centroid of the driver&#39;s head and the vehicle frame. Further, it is understood that the head looking directions can include an angular component, for example head tilting up or down (not shown). It is appreciated that the directions shown in  FIG. 16B  are exemplary in nature and other directions with respect to the vehicle frame can be implemented. Further, it is appreciated that the directions shown in  FIG. 16B  can be modified, for example, based on a driver state index and/or characteristics and preferences of an identified driver (e.g., driver profile). 
     The head pose of the driver, a rotation (e.g., head of driver is turned) direction with respect to the driver and the vehicle (i.e., to the left, right, back, forward) will now be discussed in more detail with reference to  FIG. 17 . In  FIG. 17  a head coordinate frame xyz of the driver&#39;s head is defined as element  1702 . Further, a head feature point (e.g., eyes, nose, mouth; not shown) coordinate frame XYZ is defined to a surface having a centroid position at the origin of the coordinate system XYZ, where the surface lies within the head coordinate frame xyz. In one embodiment, to determine a rotation and rotation direction of the head of the driver with respect to the driver, the angular differences (i.e., the rotation and the rotation direction) between the coordinate systems XYZ and xyz are determined as (αβγ). The angular differences in relation to a vehicle coordinate system (e.g., the vehicle coordinate system shown in  FIGS. 16A and 116B ) can determine the rotation and the rotation direction with respect to the driver and the vehicle. Said differently, the offset orientation between the angular differences and the vehicle coordinate system describe the rotation and the rotation direction with respect to the driver and the vehicle. The rotation and the rotation direction can be realized as head looking directions as shown in  FIG. 16B . 
     Referring again to  FIG. 1A , it is understood that in some embodiments, the ECU  106  can include provisions for receiving other types of information about the driver&#39;s head. For example, information related to the distance between a driver&#39;s head and a headrest (e.g., via the proximity sensor  184  in the headrest  174 ). Further, in some embodiments, the motor vehicle  100  can include a body movement monitoring system  336  ( FIG. 3 ). For example, the ECU  106  can include provisions for receiving information about a body pose (i.e., position and orientation) of the driver&#39;s body in relation to the driver and the vehicle. For example, the information can relate to the posture of the driver&#39;s body, a rotation of the driver&#39;s body, movement of the driver&#39;s body, among others. In some embodiments, the body movement monitoring system  336  provides body and/or body part vectoring information including the magnitude (e.g., a length of time) and direction of the body and/or body part. 
     The information about a head pose and the information about a body pose can be received and determined in various ways, for example, from the optical sensing device  162  and/or the thermal sensing device  166 . In some embodiments, the head movement monitoring system  334  can include the optical sensing device  162  and the thermal sensing device  166 . In some embodiments, the body movement monitoring system  336  can include the optical sensing device  162  and the thermal sensing device  166 . 
     As mentioned above, the optical sensing device  162  could be any kind of optical device including a digital camera, video camera, infrared sensor, laser sensor, as well as any other device capable of detecting optical information. In one embodiment, the optical sensing device  162  can be a video camera. In another embodiment, the optical sensing device  162  can be one or more cameras or optical tracking systems. The optical sensing device  162  can sense head movement, body movement, eye movement, facial movement, among others. Moreover, in some cases, multiple optical sensing devices could be installed inside a motor vehicle to provide viewpoints of a driver or occupant from multiple different angles. In one embodiment, the optical sensing device  162  can be installed in a portion of the motor vehicle  100  so that the optical sensing device  162  can capture images of the upper body, face and/or head of a driver or occupant. Similarly, the thermal sensing device  166  could be located in any portion of the motor vehicle  100  including a dashboard, roof or in any other portion. 
     In other cases, information about a position and/or a location of the driver&#39;s head can be received from the proximity sensor  184 . The proximity sensor  184  could be any type of sensor configured to detect the distance between the driver&#39;s head and the headrest  174 . In some cases, the proximity sensor  184  could be a capacitor. In other cases, the proximity sensor  184  could be a laser sensing device. In still other cases, any other types of proximity sensors known in the art could be used for the proximity sensor  184 . Moreover, in other embodiments, the proximity sensor  184  could be used to detect the distance between any part of the driver and any portion of the motor vehicle  100  including, but not limited to: a headrest, a seat, a steering wheel, a roof or ceiling, a driver side door, a dashboard, a central console as well as any other portion of the motor vehicle  100 . 
     In some embodiments, as discussed above, the motor vehicle  100  can include a touch steering wheel system  134 . Specifically, the steering wheel can include sensors (e.g., capacitive sensors, electrodes) mounted in or on the steering wheel. The sensors are configured to measure contact of the hands, or another appendage of the driver (e.g., arm, wrist, elbow, shoulder, knee) with the steering wheel and a location of the contact (e.g., behavioral information). In some embodiments, the sensors are located on the front and back of the steering wheel. Accordingly, the sensors can determine if the driver&#39;s hands are in contact with the back of the steering wheel (e.g., gripped and wrapped around the steering wheel). In one embodiment, the sensors can be configured (e.g., positioned) into zones of the steering wheel to determine where on the steering wheel the appendage is touching. For example, the left side of the steering wheel, the right side of the steering wheel, the left and right side of the steering wheel, the top of the steering wheel, the bottom of the steering wheel, the center of the steering wheel, the front of the steering wheel, the back of the steering wheel, among others. 
       FIG. 18  illustrates an exemplary touch steering wheel  1802 . Capacitive sensors (not shown) can measure the contact and position of the hands  1804  and  1806  with respect to the steering wheel  1802 . Although hands are shown in contact with the steering wheel  1802  in  FIG. 18 , it is understood that the sensors can measure the contact and position of other appendages (e.g., wrist, elbow, shoulder, and knee). In this embodiment, the touch steering wheel  1802  also includes a light bar to provide visual information to the driver. In some embodiments, the sensors can function as a switch wherein the contact of the hands of the driver and the location of the contact are associated with actuating a device and/or a vehicle function of the vehicle. As mentioned above, in some embodiments, the sensors can be configured into zones of the steering wheel. For example, in  FIG. 18 , the steering wheel  1802  includes a left zone  1810 , a right zone  1812 , a top zone  1814 , a bottom zone  1816 , and a center zone  1818 . Other zones and configurations of zones not shown in  FIG. 18  can also be implemented. It is understood that information about contact and position with respect to the touch steering wheel  1802  can be referred to herein as hand contact information. Other examples of touch steering wheel systems that can be implemented herein are described in U.S. application Ser. No. 14/744,247 filed on Jun. 19, 2015, which is incorporated by reference herein. 
     It is understood that the monitoring systems for behavioral monitoring can include other vehicle systems and sensors discussed herein, for example, the vehicle systems and sensors discussed in Section III (A) and shown in  FIG. 2 , the physiological monitoring systems discussed in Section III (B) (1), the vehicular monitoring systems discussed in Section III (B) (3), and the identification systems and sensors discussed in Section III (B) (4) can be types of monitoring systems for behavioral monitoring. Further, it is appreciated, that any combination of vehicle systems and sensors, physiological monitoring systems, behavioral monitoring systems, vehicular monitoring systems, and identification systems can be implemented to determine and/or assess one or more driver states based on behavioral information. 
     3. Vehicular Monitoring Systems and Sensors 
     Generally, vehicular monitoring systems and sensors include, but are not limited to, any automatic or manual systems and sensors that monitor and provide vehicle information related to the motor vehicle  100  of  FIG. 1A  and/or the vehicle systems  126 , including those vehicle systems listed in  FIG. 2 . In some cases, the vehicle information can also be related to a driver of the motor vehicle  100 . The vehicular monitoring systems can include one or more vehicle sensors for sensing and measuring a stimulus (e.g., a signal, a property, a measurement, or a quantity) associated with the motor vehicle  100  and/or a particular vehicle system. In some embodiments, the ECU  106  can communicate and obtain a data stream representing the stimulus from the vehicular monitoring system, the vehicle systems  126  and/or the one or more vehicle sensors via, for example, the port  128 . The data can be vehicle information and/or the ECU  106  can process the data into vehicle information and/or process the vehicle information further. Thus, the ECU  106  can communicate and obtain vehicle information from the motor vehicle  100 , the vehicular monitoring systems and/or sensors themselves, the vehicle systems  126  and/or sensors themselves, and/or other vehicle sensors, for example, cameras, external radar, and laser sensors, among others. 
     Vehicle information includes information related to the motor vehicle  100  of  FIG. 1A  and/or the vehicle systems  126 , including those vehicle systems listed in  FIG. 2 . In some cases, the vehicle information can also be related to a driver of the motor vehicle  100  (e.g., the driver  102 ). Specifically, vehicle information can include vehicle and/or vehicle system conditions, states, statuses, behaviors, and information about the external environment of the vehicle (e.g., other vehicles, pedestrians, objects, road conditions, weather conditions). Exemplary vehicle information includes, but is not limited to, engine info (for example, velocity or acceleration), steering information, lane information, lane departure information, blind spot monitoring information, braking information, collision warning information, navigation information, HVAC information, collision mitigation information and automatic cruise control information. Vehicle information can be obtained by the ECU  106 , the vehicular monitoring systems themselves, the vehicle systems  126  themselves (e.g., vehicle system sensors), or other sensors, for example, cameras, external radar and laser sensors, among others. As will be discussed herein, vehicle information can be used by the ECU  106  to determine a vehicular-sensed driver state and/or a vehicular state. 
     It is understood that the vehicle sensors can include, but are not limited to, vehicular monitoring system sensors, vehicle system sensors of the vehicle systems  126  and other vehicle sensors associated with the motor vehicle  100 . For example, other vehicle sensors can include cameras mounted to the interior or exterior of the vehicle, radar and laser sensors mounted to the exterior of the vehicle, external cameras, radar and laser sensors (e.g., on other vehicles in a vehicle-to-vehicle network, street cameras, surveillance cameras). The sensors can be any type of sensor, for example, acoustic, electric, environmental, optical, imaging, light, pressure, force, thermal, temperature, proximity, among others. 
     Examples of different vehicular monitoring systems, including different vehicle systems  126  illustrated in  FIG. 2  will now be discussed. It should be understood that the systems shown in  FIG. 2  are only intended to be exemplary and in some cases, some other additional systems can be included. In other cases, some of the systems can be optional and not included in all embodiments. Referring again to  FIG. 2 , the vehicular monitoring system can include an electronic stability control system  202  (also referred to as ESC system  202 ). The ESC system  202  can include provisions for maintaining the stability of the motor vehicle  100 . In some cases, the ESC system  202  can monitor the yaw rate and/or lateral g acceleration of the motor vehicle  100  to help improve traction and stability. The ESC system  202  can actuate one or more brakes automatically to help improve traction. An example of an electronic stability control system is disclosed in Ellis et al., U.S. Pat. No. 8,423,257, filed Mar. 17, 2010, the entirety of which is hereby incorporated by reference. In one embodiment, the electronic stability control system can be a vehicle stability system. 
     In some embodiments, the vehicular monitoring systems can include an antilock brake system  204  (also referred to as an ABS system  204 ). The ABS system  204  can include various different components such as a speed sensor, a pump for applying pressure to the brake lines, valves for removing pressure from the brake lines, and a controller. In some cases, a dedicated ABS controller can be used. In other cases, ECU  106  can function as an ABS controller. In still other cases, the ABS system  204  can provide braking information, for example brake pedal input and/or brake pedal input pressure/rate, among others. Examples of antilock braking systems are known in the art. One example is disclosed in Ingaki, et al., U.S. Pat. No. 6,908,161, filed Nov. 18, 2003, the entirety of which is hereby incorporated by reference. Using the ABS system  204  can help improve traction in the motor vehicle  100  by preventing the wheels from locking up during braking. 
     In some embodiments, the vehicular monitoring systems can include a brake assist system  206 . The brake assist system  206  can be any system that helps to reduce the force required by a driver to depress a brake pedal. In some cases, the brake assist system  206  can be activated for older drivers or any other drivers who can need assistance with braking. An example of a brake assist system can be found in Wakabayashi et al., U.S. Pat. No. 6,309,029, filed Nov. 17, 1999, the entirety of which is hereby incorporated by reference. 
     In some embodiments, the vehicular monitoring systems can include an automatic brake prefill system  208  (also referred to as an ABP system  208 ). The ABP system  208  includes provisions for prefilling one or more brake lines with brake fluid prior to a collision. This can help increase the reaction time of the braking system as the driver depresses the brake pedal. Examples of automatic brake prefill systems are known in the art. One example is disclosed in Bitz, U.S. Pat. No. 7,806,486, filed May 24, 2007, the entirety of which is hereby incorporated by reference. 
     In some embodiments, the motor vehicle  100  can include an electric parking brake (EPB) system  210 . The EPB system  210  includes provisions for holding the motor vehicle  100  stationary on grades and flat roads. In particular, the motor vehicle  100  can include an electric park brake switch (e.g., a button) that can be activated by the driver  102 . When activated, the EPB system  210  controls the braking systems discussed above to apply to one or more wheels of the motor vehicle  100 . To release the braking, the driver can engage the electric park brake switch and/or press on the accelerator pedal. Additionally, the EPB system  210  can include an automatic brake hold control feature that maintains brake hold when the vehicle is stopped, even after the brake pedal is released. Thus, when the vehicle comes to a full stop, brake hold is engaged and the brakes continue to hold until the accelerator pedal is engaged. In some embodiments, the automatic brake hold control feature can be manually engaged with a switch. In other embodiments, the automatic brake hold control feature is engaged automatically. 
     As mentioned above, the motor vehicle  100  includes provisions for communicating and/or controlling various systems and/or functions associated with the engine  104 . In one embodiment, the engine  104  includes an idle stop function that can be controlled by the ECU  106  and/or the engine  104  based information from, for example, the engine  104  (e.g., automatic transmission), the antilock brake system  204 , the brake assist system  205 , the automatic brake prefill system  208 , and/or the EPB system  210 . Specifically, the idle stop function includes provisions to automatically stop and restart the engine  104  to help maximize fuel economy depending on environmental and vehicle conditions. For example, the ECU  106  can activate the idle stop feature based on gear information from the engine  104  (e.g., automatic transmission) and brake pedal position information from the braking systems described above. Thus, when the vehicle stops with a gear position in Drive (D) and the brake pedal is pressed, the ECU  106  controls the engine to turn OFF. When the brake pedal is subsequently released, the ECU  106  controls the engine to restart (e.g., turn ON) and the vehicle can begin to move. In some embodiments, when the idle stop function is activated, the ECU  106  can control the visual devices  140  to provide an idle stop indicator to the driver. For example, a visual device  140  on a dashboard of the motor vehicle  100  can be controlled to display an idle stop indicator. Activation of the idle stop function can be disabled in certain situations based on other vehicle conditions (e.g., seat belt is fastened, vehicle is stopped on a steep hill). Further, the idle stop function can be manually controlled by the driver  102  using, for example, an idle stop switch located in the motor vehicle  100 . 
     In some embodiments, the vehicular monitoring systems can include a low speed follow system  212  (also referred to as an LSF system  212 ). The LSF system  212  includes provisions for automatically following a preceding vehicle at a set distance or range of distances. This can reduce the need for the driver to constantly press and depress the acceleration pedal in slow traffic situations. The LSF system  212  can include components for monitoring the relative position of a preceding vehicle (for example, using remote sensing devices such as lidar or radar). In some cases, the LSF system  212  can include provisions for communicating with any preceding vehicles for determining the GPS positions and/or speeds of the vehicles. Examples of low speed follow systems are known in the art. One example is disclosed in Arai, U.S. Pat. No. 7,337,056, filed Mar. 23, 2005, the entirety of which is hereby incorporated by reference. Another example is disclosed in Higashimata et al., U.S. Pat. No. 6,292,737, filed May 19, 2000, the entirety of which is hereby disclosed by reference. 
     In some embodiments, the vehicular monitoring systems can include a cruise control system  214 . Cruise control systems are well known in the art and allow a user to set a cruising speed that is automatically maintained by a vehicle control system. For example, while traveling on a highway, a driver can set the cruising speed to 55 mph. The cruise control system  214  can maintain the vehicle speed at approximately 55 mph automatically, until the driver depresses the brake pedal or otherwise deactivates the cruising function. 
     In some embodiments, the vehicular monitoring systems can include an automatic cruise control system  216  (also referred to as an ACC system  216 ). In some cases, the ACC system  216  can include provisions for automatically controlling the vehicle to maintain a predetermined following distance behind a preceding vehicle or to prevent a vehicle from getting closer than a predetermined distance to a preceding vehicle. The ACC system  216  can include components for monitoring the relative position of a preceding vehicle (for example, using remote sensing devices such as lidar or radar). In some cases, the ACC system  216  can include provisions for communicating with any preceding vehicles for determining the GPS positions and/or speeds of the vehicles. An example of an automatic cruise control system is disclosed in Arai et al., U.S. Pat. No. 7,280,903, filed Aug. 31, 2005, the entirety of which is hereby incorporated by reference. 
     In some embodiments, the vehicular monitoring systems can include a collision warning system  218 . In some cases, the collision warning system  218  can include provisions for warning a driver of any potential collision threats with one or more vehicles, objects, and/or pedestrians. For example, a collision warning system can warn a driver when another vehicle is passing through an intersection as the motor vehicle  100  approaches the same intersection. Examples of collision warning systems are disclosed in Mochizuki, U.S. Pat. No. 8,558,718, filed Sep. 20, 2010, and Mochizuki et al., U.S. Pat. No. 8,587,418, filed Jul. 28, 2010, the entirety of both being hereby incorporated by reference. In one embodiment, the collision warning system  218  could be a forward collision warning system, including warning of vehicles and/or pedestrians. In another embodiment, the collision warning system  218  could be a cross traffic monitoring system, utilizing backup cameras or back sensors to determine if a pedestrian or another vehicle is behind the vehicle. 
     In some embodiments, the vehicular monitoring systems can include a collision mitigation braking system  220  (also referred to as a CMBS  220 ). The CMBS  220  can include provisions for monitoring vehicle operating conditions (including target vehicles, objects, and pedestrians in the environment of the vehicle) and automatically applying various stages of warning and/or control to mitigate collisions. For example, in some cases, the CMBS  220  can monitor forward vehicles using radar or other type of remote sensing device. If the motor vehicle  100  gets too close to a forward vehicle, the CMBS  220  could enter a first warning stage. During the first warning stage, a visual and/or audible warning can be provided to warn the driver. If the motor vehicle  100  continues to get closer to the forward vehicle, the CMBS  220  could enter a second warning stage. During the second warning stage, the CMBS  220  could apply automatic seat belt pretensioning. In some cases, visual and/or audible warnings could continue throughout the second warning stage. Moreover, in some cases, during the second stage automatic braking could also be activated to help reduce the vehicle speed. In some cases, a third stage of operation for the CMBS  220  can involve braking the vehicle and tightening a seat belt automatically in situations where a collision is very likely. An example of such a system is disclosed in Bond, et al., U.S. Pat. No. 6,607,255, and filed Jan. 17, 2002, the entirety of which is hereby incorporated by reference. The term collision mitigation braking system as used throughout this detailed description and in the claims can refer to any system that is capable of sensing potential collision threats and providing various types of warning responses as well as automated braking in response to potential collisions. 
     In some embodiments, the vehicular monitoring systems can include a lane departure warning system  222  (also referred to as an LDW system  222 ). The LDW system  222  can determine when a driver is deviating from a lane and provide a warning signal to alert the driver. Examples of lane departure warning systems can be found in Tanida et al., U.S. Pat. No. 8,063,754, filed Dec. 17, 2007, the entirety of which is hereby incorporated by reference. 
     In some embodiments, the vehicular monitoring systems can include a blind spot indicator system  224  (also referred to as a BSI system  224 ). The blind spot indicator system  224  can include provisions for helping to monitor the blind spot of a driver. In some cases, the blind spot indicator system  224  can include provisions to warn a driver if a vehicle is located within a blind spot. In other cases, the blind spot indicator system  224  can include provisions to warn a driver if a pedestrian or other object is located within a blind spot. Any known systems for detecting objects traveling around a vehicle can be used. 
     In some embodiments, the vehicular monitoring systems can include a lane keep assist system  226  (also referred to as an LKAS system  226 ). The lane keep assist system  226  can include provisions for helping a driver to stay in the current lane. In some cases, the lane keep assist system  226  can warn a driver if the motor vehicle  100  is unintentionally drifting into another lane. In addition, in some cases, the lane keep assist system  226  can provide assisting control to maintain a vehicle in a predetermined lane. For example, the lane keep assist system  226  can control the electronic power steering system  132  by applying an amount of counter-steering force to keep the vehicle in the predetermined lane. In another embodiment, the lane keep assist system  226 , in, for example, an automatic control mode can automatically control the electronic power steering system  132  to keep the vehicle in the predetermined lane based on identifying and monitoring lane markers of the predetermined lane. An example of a lane keep assist system is disclosed in Nishikawa et al., U.S. Pat. No. 6,092,619, filed May 7, 1997, the entirety of which is hereby incorporated by reference. 
     In some embodiments, the vehicular monitoring systems can include a lane monitoring system  228 . In some embodiments, the lane monitoring system  228  could be combined or integrated with the blind spot indicator system  224  and/or the lane keep assist system  226 . The lane monitoring system  228  includes provisions for monitoring and detecting the state of the vehicle, and elements in the environment of the vehicle, for example, pedestrians, objects, other vehicles, cross traffic, among others. Upon detection of said elements, the lane monitoring system  228  can warn a driver and/or work in conjunction with the lane keep assist system  226  to assist in maintaining control of the vehicle to avoid potential collisions and/or dangerous situations. The lane keep assist system  226  and/or the lane monitoring system  228  can include sensors and/or optical devices (e.g., cameras) located in various areas of the vehicle (e.g., front, rear, sides, and roof). These sensors and/or optical devices provide a broader view of the roadway and/or environment of the vehicle. In some embodiments, the lane monitoring system  228  can capture images of a rear region of a vehicle and a blind spot region of the vehicle out of viewing range of a side mirror adjacent to the rear region of the vehicle, compress said images and display said images to the driver. An example of a lane monitoring system is disclosed in Nishiguichi et al., U.S. Publication Number 2013/0038735, filed on Feb. 16, 2011, the entirety of which is incorporated by reference. It is understood that after detecting the state of the vehicle, the lane monitoring system  228  can provide warnings or driver assistances with other vehicles systems, for example, the electronic stability control system  202 , the brake assist system  206 , the collision warning system  218 , the collision mitigation braking system  220 , the blind spot indicator system  224 , among others. 
     In some embodiments, the vehicular monitoring systems can include a navigation system  230 . The navigation system  230  could be any system capable of receiving, sending and/or processing navigation information. The term “navigation information” refers to any information that can be used to assist in determining a location or providing directions to a location. Some examples of navigation information include street addresses, street names, street or address numbers, apartment or suite numbers, intersection information, points of interest, parks, any political or geographical subdivision including town, township, province, prefecture, city, state, district, ZIP or postal code, and country. Navigation information can also include commercial information including business and restaurant names, commercial districts, shopping centers, and parking facilities. In some cases, the navigation system could be integrated into the motor vehicle, for example, as a part of the infotainment system  154 . Navigation information could also include traffic patterns, characteristics of roads, and other information about roads the motor vehicle currently is travelling on or will travel on in accordance with a current route. In other cases, the navigation system could be a portable, stand-alone navigation system, or could be part of a portable device, for example, the portable device  122 . 
     In some embodiments, the vehicular monitoring systems can include an infotainment system. As mentioned above, in some embodiments, the visual devices  140 , the audio devices  144 , the tactile devices  148  and/or the user input devices  152  can be part of a larger infotainment system  154 . In a further embodiment, the infotainment system  154  can facilitate mobile phone and/or portable device connectivity to the vehicle to allow, for example, the playing of content from the mobile device to the infotainment system. Accordingly, in one embodiment, the vehicle can include a hands free portable device (e.g., telephone) system  232 . The hands free portable device system  232  can include a telephone device, for example integrated with the infotainment system, a microphone (e.g., audio device) mounted in the vehicle. In one embodiment, the hands free portable device system  232  can include the portable device  122  (e.g., a mobile phone, a smart phone, a tablet with phone capabilities). The telephone device is configured to use the portable device, the microphone, and the vehicle audio system to provide an in-vehicle telephone feature and/or provide content from the portable device in the vehicle. In some embodiments, the telephone device is omitted as the portable device can provide telephone functions. This allows the vehicle occupant to realize functions of the portable device through the infotainment system without physical interaction with the portable device. 
     In some embodiments, the vehicular monitoring systems can include a climate control system  234 . The climate control system  234  can be any type of system used for controlling the temperature or other ambient conditions in the motor vehicle  100 . In some cases, the climate control system  234  can comprise a heating, ventilation and air conditioning system as well as an electronic controller for operating the HVAC system. In some embodiments, the climate control system  234  can include a separate dedicated controller. In other embodiments, the ECU  106  can function as a controller for the climate control system  234 . Any kind of climate control system known in the art can be used. 
     In some embodiments, the vehicular monitoring systems can include an electronic pretensioning system  236  (also referred to as an EPT system  236 ). The EPT system  236  can be used with a seat belt (not shown) for the motor vehicle  100 . The EPT system  236  can include provisions for automatically tightening, or tensioning, the seat belt. In some cases, the EPT system  236  can automatically pretension the seat belt prior to a collision. An example of an electronic pretensioning system is disclosed in Masuda et al., U.S. Pat. No. 6,164,700, filed Apr. 20, 1999, the entirety of which is hereby incorporated by reference. 
     In some embodiments, the vehicular monitoring systems can include a vehicle mode selector system  238  that modifies driving performance according to preset parameters related to the mode selected. Modes can include, but are not limited to, normal, economy, sport, sport+(plus), auto, and terrain/condition specific modes (e.g., snow, mud, off-road, steep grades). For example, in an economy mode, the ECU  106  can control the engine  104  (or vehicle systems related to the engine  104 ) to provide a more consistent engine speed thereby increasing fuel economy. The ECU  106  can also control other vehicle systems to ease the load on the engine  104 , for example, modifying the climate control system  234 . In a sport mode, the ECU  106  can control the EPS  132  and/or the ESC system  202  to increase steering feel and feedback. In terrain/condition specific modes (e.g., snow, mud, sand, off-road, steep grades), the ECU  106  can control various vehicle systems to provide handling, and safety features conducive to the specific terrain and conditions. In an auto mode, the ECU  106  can control various vehicle systems to provide full (e.g., autonomous) or partial automatic control of the vehicle. It is understood that the modes and features of the modes described above are exemplary in nature and that other modes and features can be implemented. Further it is appreciated that more than one mode could be implemented at the same or substantially the same time. 
     In some embodiments, the vehicular monitoring systems can include a turn signal control system  240  for controlling turn signals (e.g., directional indicators) and braking signals. For example, the turn signal control system  240  can control turn signal indicator lamps (e.g., mounted on the left and right front and rear corners of the vehicle, the side of the vehicle, the exterior side mirrors). The turn signal control system  240  can control (e.g., turn ON/OFF) the turn signal indicator lamps upon receiving a turn signal input from the driver (e.g., input via a user input device  152 , a turn signal actuator, etc.). In other embodiments, the turn signal control system  240  can control a feature and/or a visual cue of the turn signal indicator lamps. For example, a brightness, a color, a light pattern, a mode among others. The feature and/or visual cue control can be based on input received from the driver or can be an automatic control based on input from another vehicle system and/or a driver state. For example, the turn signal control system  240  can control the turn signal indicator lamps based on an emergency event (e.g., receiving a signal from the collision warning system) to provide warnings to other vehicles and/or provide information about occupants in the vehicle. Further, the turn signal control system  240  can control braking signals (e.g., braking indicator lamps mounted on the rear of the vehicle) alone or in conjunction with a braking system discussed herein. The turn signal control system  240  can also control a feature and/or visual cue of the braking signals similar to the turn signal indicator lamps described above. 
     In some embodiments, the vehicular monitoring systems can include a headlight control system  242  for controlling headlamps and/or flood lamps mounted on the vehicle (e.g., located the right and left front corners of the vehicle). The headlight control system  242  can control (e.g., turn ON/OFF, adjust) the headlamps upon receiving an input from the driver. In other embodiments, the headlight control system  242  can control (e.g., turn ON/OFF, adjust) the headlamps automatically and dynamically based on information from one or more of the vehicle systems. For example, the headlight control system  242  can actuate the headlamps and/or adjust features of the headlights based on environmental/road conditions (e.g., luminance outside, weather), time of day, among others. It is understood that the turn signal control system  240  and the headlight control system  242  could be part of a larger vehicle lighting control system. 
     In some embodiments, the vehicular monitoring systems can include a failure detection system  244  that detects a failure in one or more of the vehicle systems  126 . More specifically, the failure detection system  244  receives information from a vehicle system and executes a fail-safe function (e.g., system shut down) or a non-fail-safe function (e.g., system control) based on the information and a level of failure. In operation, the failure detection system  244  monitors and/or receives signals from one or more vehicle systems  126 . The signals are analyzed and compared to pre-determined failure and control levels associated with the vehicle system. Once the failure detection system  244  detects the signals meets a pre-determined level, the failure detection system  244  initiates control of the one or more vehicle systems and/or shuts down the one or more vehicle systems. It is understood that one or more of the vehicle systems  126  could implement an independent failure detection system. In some embodiments, the failure detection system  244  can be integrated with an on-board diagnostic system of the motor vehicle  100 . Further, in some embodiments, the failure detection system  244  could determine failure of a vehicle system based on a comparison of information from more than one vehicle system. For example, the failure detection system  244  can compare information indicating hand and/or appendage contact from the touch steering wheel system  134  and the electronic power steering system  132  to determine failure of a touch sensor as described in U.S. application Ser. No. 14/733,836 filed on Jun. 8, 2015 and incorporated herein by reference. 
     Additionally, the vehicular monitoring systems can include other vehicle systems  126  and other kinds of devices, components, or systems used with vehicles. The vehicular monitoring systems can include one of the vehicle systems  126  or more than one of the vehicle systems  126 . It will be understood that each of vehicular monitoring system can be a standalone system or can be integrated with the ECU  106 . For example, in some cases, the ECU  106  can operate as a controller for various components of one or more vehicular monitoring system. In other cases, some systems can comprise separate dedicated controllers that communicate with the ECU  106  through one or more ports. 
     As mentioned above, in certain embodiments, vehicle systems and monitoring systems can be used alone or in combination for receiving monitoring information. For example, in some embodiments, vehicular monitoring systems, physiological monitoring systems and behavioral monitoring systems can be used in combination for receiving monitoring information. Accordingly, one or more monitoring systems can include one or more vehicle systems ( FIG. 2 ) and/or one or more monitoring systems (e.g., physiological monitoring systems and/or behavioral monitoring systems ( FIG. 3 ). For example, in one embodiment, the heart rate monitoring system  302  including heart rate sensors  304  and vehicle systems  126  including various vehicle sensors facilitate systems and methods for determining information transfer rates between a driver and a vehicle, as discussed in U.S. application Ser. No. 14/573,778 filed on Dec. 17, 2014, entitled System and Method for Determining The Information Transfer Rate Between a Driver and a Vehicle, which is incorporated by reference in its entirety herein. The &#39;020 application will now be discussed, however, for brevity, the &#39;020 application will not be discussed in its entirety. 
     To maintain control of a vehicle, a constant flow of information from a driver to a vehicle is required. A reduction in the flow of information from the driver to the vehicle can results in a reduction or loss of vehicular control. Thus, an accurate determination of flow of information can be used to determine a driver state.  FIG. 19  illustrates a schematic view of a vehicle  1900  having an information transfer rate system  1902  for determining the information transfer rate between a driver  1904  and vehicle  1900  according to an exemplary embodiment. The vehicle  1900  can include similar components and functions as the motor vehicle  100  of  FIG. 1A . Additionally, the information transfer rate system  1902  can be a type of monitoring system and/or obtain information from the vehicle systems  126  and/or the monitoring systems of  FIG. 3 . 
     Referring again to  FIG. 19 , in one embodiment, the vehicle  1900  comprises a driver information sensing device  1906 , a vehicle information sensing device  1908 , a driver alert device  1910 , a GPS  1912 , and optionally an external information sensing device  1914 . To control the vehicle  1900 , the driver  1904  must transmit information by way of one or more driver control input devices to produce appropriate changes in vehicle acceleration, velocity, lane position, and direction. Driver control input devices (not shown) include, but are not limited to, a steering wheel, accelerator pedal, and brake pedal. Thus, a reduction in information transfer from the driver  1904  to the vehicle  1900  can signal a reduction in vehicular control, as could be the case with a driver  1904  who is distracted, drowsy, intoxicated or experiencing a medical emergency. 
     In one embodiment, the driver information sensing device  1906  can measure driver information directly from the driver  1904 , such as biometric data and direct driver control input device data. Driver biometric data can include one or more types of driver biometric data, including, but not limited to, eyelid aperture, pupil diameter, head position, gaze direction, eye blink rate, respiratory rate, heart rate, hand position, aortic blood flow, leg position, and brain electrical activity. Direct driver control input device data can include data from one or more types of driver control input devices, such as, but not limited to, the steering wheel, brake pedal, and gas pedal of vehicle  1900 . Accordingly, the direct driver control input device data, can include, but is not limited to, one or more of the position of the vehicle steering wheel, turn velocity of the steering wheel, turn acceleration of the steering wheel, position of the vehicle gas pedal, velocity of the gas pedal, acceleration of the gas pedal, position of the vehicle brake pedal, velocity of the brake pedal, and acceleration of the brake pedal. 
     It is contemplated that in some embodiments, one driver information sensing device  1906  can be used to measure one or more types of driver information directly from the driver  1904 . In other embodiments, multiple driver information sensing devices  1906  can be used to measure multiple types of driver information directly from the driver  1904 . For example, in one embodiment, driver information sensing device  1906  can include an electroencephalograph for measuring the driver brain electrical activity. In another embodiment, one driver information sensing device  1906  can include a camera for measuring the driver eyelid aperture, the gas pedal for measuring the position of the vehicle gas pedal, and the brake pedal for measuring the position of the vehicle brake pedal, and so forth. 
     Further, in other embodiments, the driver information sensing device  1906  can be a camera for measuring the driver eyelid aperture, another driver information sensing device  1906  can be a driver control input device, such as the vehicle gas pedal, or a component of the gas pedal, for measuring the position of the gas pedal, and an additional driver information sensing device  1906  can be another driver control input device, such as the vehicle brake pedal, or a component of the brake pedal, for measuring the position of the brake pedal. In other embodiments, driver information sensing device  1906  can be comprised of one or more of a contact and/or contactless sensors and can include electric current/potential sensors (e.g., proximity, inductive, capacitive, electrostatic), subsonic, sonic, and ultrasonic sensors, vibration sensors (e.g., piezoelectric) visual, photoelectric, oxygen sensors, as well as any other kinds of devices, sensors, or systems that are capable of measuring driver information directly from the driver  1904 . 
     In one embodiment, the vehicle information sensing device  1908  can measure vehicle information directly from a vehicle system of vehicle  1900 . For example, the vehicle information sensing device  1908  can measure vehicle information directly from the vehicle  1900 , such as the lane position, lane deviation, linear and angular vehicle position, velocity and acceleration, distance from potential obstacles in front of, beside and behind the vehicle  1900 , reliance on cruise control, reliance on assisted steering and reaction to known obstacles, such as construction barricades, traffic signals, and stopped vehicles. 
     As with the driver information sensing device  1906 , in some embodiments, one vehicle information sensing device  1908  can be used to measure one or more types of vehicle information directly from the vehicle  1900 . In other embodiments, multiple vehicle information sensing devices  1908  can be used to measure multiple types of vehicle information. For example, in one embodiment, the vehicle information sensing device  1908  can include a camera for measuring lane position of the vehicle  1900  and an accelerometer for measuring the acceleration of the vehicle  1900 . In further embodiments, the vehicle information sensing device  1908  can be a camera for measuring lane position of the vehicle  1900 , another vehicle information sensing device  1908  of the vehicle  1900  can be an accelerometer for measuring the acceleration of the vehicle  1900 , and a third vehicle information sensing device  1908  can be an ultrasonic detector for measuring the distance from the vehicle  1900  to any potential obstacles located around the vehicle  1900 . 
     The driver alert device  1910  is used to alert the driver  1904  if a reduction in vehicle control occurs, namely if the driver safety factor, discussed below, does not exceed a predetermined driver safety alert threshold, discussed below, due to a low information transfer rate between the driver  1904  and the vehicle  1900 . The driver alert device  1910  can be an output device of the vehicle  1900  that outputs a visual, mechanical, or audio signal to alert the driver  1904  to the reduction in vehicle control, which would allow the driver  1904  to take action, such as pulling the vehicle  1900  over, stopping the vehicle  1900 , or swerving the vehicle  1900 . 
     The external information sensing device  1914  can be used to measure information external to the vehicle  1900 , and thus the flow of information from the driver  1904  to the vehicle  1900  in reaction to the external information. The external information sensing device  1914  can measure external information, such as, but not limited to, adjacent vehicles, road construction barricades, stopped traffic, animals, and pedestrians. It is contemplated that in some embodiments, one external information sensing device  1914  can be used to measure one or more types of external information. In other embodiments, multiple external information sensing devices  1914  can be used to measure multiple types of external information. For example, in one embodiment, the external information sensing device  1914  can include a camera to sense an animal external to the vehicle  1900 , an inter-vehicular communication system for sensing other vehicles adjacent to the vehicle  1900 , and an ultrasonic proximity sensor for sensing objects near the vehicle  1900 . In another embodiment, one external information sensing device  1914  can include a camera to sense an animal external to the vehicle  1900 , another external information system can include an inter-vehicular communication system for sensing other vehicles adjacent to the vehicle  1900 , and another external information system can include an ultrasonic proximity sensor for sensing objects near the vehicle  1900 . 
     The GPS  1912  can optionally be present in the vehicle  1900  and can be used to obtain the location, weather, and time of day traffic conditions at the location of the vehicle  1900  for use during the normalization process of the information transfer rate between the driver  1904  and the vehicle  1900 , in embodiments of the information transfer rate system  1902 , which normalize such information. It is recognized that normalizing the information transfer rate between the driver  1904  and the vehicle  1900  can be necessary due to the fact that a higher information transfer rate is required to maintain control of vehicle  1900  in some driving conditions and a lower information transfer rate is required to maintain control of the vehicle  1900  in other driving conditions. For example, curvy inner city roads during rush hour on snowy days require a higher information transfer rate from the driver  1904  to the vehicle  1900  to maintain control of the vehicle  1900 , than will long straight desolate roads in fair weather. 
     Referring now to  FIG. 20 , there is shown a schematic detailed view of an information transfer rate system  1902  for determining the information transfer rate between a driver  1904  and vehicle  1900  according to an exemplary embodiment, which will be described with reference to the elements of  FIG. 19 . The information transfer rate system B 535  comprises a computer processor  2002  and a memory  2004 . Note that the information transfer rate system  1902  comprises features, such as communication interfaces to the driver information sensing device  1906 , vehicle information sensing device  1908 , driver alert device  1910 , GPS  1912 , and optional external information sensing device  1914 . 
     The memory  2004  includes an information transfer rate module  2006 . In one embodiment, the information transfer rate module  2006  receives driver information measured directly from the driver  1904  from the driver information sensing device  1906  in the form of a driver time series calculated according to the following equation:
 
 D   x   ={d   x1   ,d   x2    . . . d   xN }  (5)
 
where: D x  is a time series, which is an ordered collection of real values of driver information measured directly from the driver  1904  using the driver information sensing device  1906 , and d x  is a time series segment of a real value of driver information measured directly from the driver  1904  using the driver information sensing device  1906 .
 
     Further, the information transfer rate module  2006  receives vehicle information measured directly from the vehicle  1900  from the vehicle information sensing device  1908  in the form of a vehicle time series calculated according to the following equation:
 
 V   y   ={v   y1   ,v   y2    . . . v   yN }  (6)
 
where: V y  is a time series, which is an ordered collection of real values of vehicle information measured directly from the vehicle using the vehicle information sensing device  1908 , and v y  is a time series segment of a real value of vehicle information measured directly from the vehicle using the vehicle information sensing device  1908 .
 
     The information transfer rate module  2006  calculates an information transfer rate between the driver and vehicle using the vehicle information measured directly from the vehicle  1900  by the vehicle information sensing device  1908  and the driver information measured directly from the driver  1904  by the driver information sensing device  1906 . The information transfer rate between the driver  1904  and the vehicle  1900  is calculated using conditional and transfer entropies. Conditional entropy quantifies the amount of information needed to describe the outcome of a random variable Y given that the value of another random variable X is known. Further, transfer entropy is a non-parametric statistic measuring the amount of directed (time-asymmetric) transfer of information between two random processes. Transfer entropy from a process X to another process Y is the amount of uncertainty reduced in future values of Y by knowing the past values of X given past values of Y. Thus, in one embodiment, the information transfer rate system  1902  measures the reduction in uncertainty in V (vehicle) given historical segments of both V and D (driver) with respect to the reduction of uncertainty in V given only historical segments of V. In other words, the information transfer rate system  1902  ascertains how much knowing D assists with determining V. 
     More specifically, in one embodiment, the information transfer rate between the driver  1904  and the vehicle  1900  is calculated according to the following equation:
 
 T   D     x     →V     y     =H ( v   yi   |v   y(i−t)   (l) )− H ( v   yi   |v   y(i−t)   (l)   ,d   x(i−τ)   (k) )  (7)
 
where: T D     x     →V     y    is a transfer entropy from a driver measurement x to a vehicle measurement y, H(v yi |v y(i−t)   (l) ) is the conditional entropy between v yi  and a prior segment of V y  that is l points long and delayed by t points. Specifically,
 
 v   y(i−t)   (l)   ={v   y(i−t−l+1)   ,v   y(i−t−l+2)   , . . . ,v   y(i−t) }, and  H ( v   yi   |v   y(i−t)   (l)   ,d   x(i−τ)   (k) )
 
is the conditional entropy between v i  and a prior segment of v y  further conditioned on a prior segment of D x  that is k points long and delayed by τ time points. Specifically,
 
 d   x(i−τ)   (k)   ={d   x(i−τ−k+1)   ,d   x(i−τ−k+2)   , . . . ,d   x(i−τ) }.
 
Note that further conditioning of v y1  on d x(i−τ)   (k)  cannot increase the uncertainty in v i  so:
 
 H ( v   yi   |v   y(i−t)   (l) )≥ H ( v   yi   |v   y(i−t)   (l)   ,d   x(i−τ)   (k) ) and  T   D     x     →V     y    is always greater than zero.
 
     The information transfer rate module  2006  can be configured to use all of the driver information and vehicle information separately or in combination to form various transfer information sums and calculate an information transfer rate between the driver and vehicle. For example, in one embodiment, a total information transfer T D→V  is calculated by the information transfer rate module  2006  using the following equation:
 
 T   D→V =Σ x=1   X Σ y=1   Y   H ( v   yi   |v   y(i−t)   (l) )− H ( v   yi   |v   y(i−t)   (l)   ,d   x(i−τ)   (k) )  (8)
 
which is the total sum over every possible combination of all driver information measured directly from the driver  1904  (X in total) by the driver information sensing device  1906  and all vehicle measurements measured directly from the vehicle (Y in total) by the vehicle information sensing device  1908  for a total of X*Y individual sums.
 
     In other embodiments, the information transfer rate module  2006  can be configured to use only some of the driver information and vehicle information separately or in combination to form various transfer information sums and calculate an information transfer rate between the driver and vehicle. For example, in one embodiment, a sum of the combinations of driver information measurements  3  through  5  measured directly from the driver  1904  by the driver information sensing device  1906  and vehicle measurements  2  through  6  measured directly from the vehicle  1900  by the vehicle information sensing device  1908 , represented as T D     3−5     →V     2−6   , can be calculated by the information transfer rate module  2006  using the following equation:
 
 T   D     3−5     →V     2−6   =Θ x=3   5 Σ y=2   6   H ( v   yi   |v   y(i−t)   (l) )− H ( v   yi   |v   y(i−t   (l)   ,d   x(i−τ)   (k) )  (9)
 
Thus, as can be seen, the information transfer rate between the driver  1904  and the vehicle  1900  is calculated by the information transfer rate module  2006  using entropy. More specifically, the transfer rate is calculated by information transfer rate module  2006 , using transfer entropy and conditional entropy. Each of equations (5)-(9), discussed above, provide an information transfer rate between the driver  1904  and the vehicle  1900  using transfer entropy and conditional entropy.
 
     In some embodiments, information transfer rate module  2006  also uses the external measurements, measurements of information external to the vehicle  1900 , provided by external information sensing device  1914  to calculate the information transfer rate between the driver and vehicle. 
     In some embodiments, the information transfer rate module  2006  normalizes the calculated information transfer rate based on at least one of the type of driver information measured directly from the driver  1904  and the driving conditions. The driving conditions include at least one of a particular road condition, weather condition, time of day, and traffic condition. Further, in some embodiments, the information transfer rate module  2006  also uses information provided by the GPS  1912  of the vehicle  1900  to normalize the information transfer rate for the driving conditions. In one embodiment, the information transfer rate module  2006  determines the maximum information transfer rate by adjusting the parameters t, τ, k, l of the above discussed equations (5)-(9) to determine the maximum information transfer rate between the driver  545  and the vehicle  100 . Specifically, in one embodiment, the parameters t, τ, k, l are adjusted based on at least one of a type of driver information measured directly from the driver  1904  and the driving conditions. The driving conditions include at least one of a particular road condition, a weather condition, a time of day, and a traffic condition. 
     In some embodiments, the information transfer rates between the driver and vehicle for all driver measurements and all vehicle measurements are calculated by the information transfer rate module  2006 , tracked by the processor  2002 , and stored in the memory  2004  to establish personal normatives for each driver  1904  of the vehicle  1900 . These personal normatives are then stored in a baseline information transfer rate database  2008  as baseline information transfer rate values for the driver  1904 , for retrieval and use by a driver safety factor module  2010 . 
     In one embodiment, the baseline information transfer rate database  2008  contains baseline information transfer rate values for maintaining control of the vehicle  1900 . In some embodiments, the baseline information transfer rate database  2008  only contains one baseline information transfer rate value. In other embodiments, the baseline information transfer rate database  2008  contains at least two different baseline information transfer rate values for the driver  1904 , with each value adjusted for road conditions. Road conditions can include, but are not limited to, one or more of type of road, weather, time of day, and traffic conditions. 
     In one embodiment, the driver safety factor module  2010  calculates a driver safety factor for the driver  1904  of the vehicle  1900  in real time. The driver safety factor is the ratio of the rate of information transfer between the driver and vehicle calculated by the information transfer rate module  2006  and the baseline information transfer rate retrieved from the baseline information transfer rate database  2008  by the driver safety factor module  2010 . In the event that baseline information transfer rate database  2008  contains multiple baseline information transfer rates for the driver  1904  of vehicle  1900 , the driver safety factor module  2010  retrieves the baseline information transfer rate that most closely matches the real time road conditions for the road on which the vehicle  1900  is travelling. 
     In one embodiment, a driver alert module  2012  compares the driver safety factor calculated by the driver safety factor module  2010  to a predetermined driver safety alert threshold. In the event that the calculated driver safety factor does not exceed the predetermined driver safety alert threshold, an alert is issued to the driver  1904  using the driver alert device  1910 , as discussed above. The alert signals to the driver  1904  that the real time information transfer rate between the driver and vehicle has fallen below the information transfer rate necessary for the driver  1904  to maintain suitable control of the vehicle  1900  given the present road conditions. 
     With reference to  FIG. 21 , a process flow diagram of a method  2100  for determining an information transfer rate between a driver  1904  and a vehicle  1900  according to an exemplary embodiment is shown. The method of  FIG. 21  will be described with reference to  FIGS. 19 and 21 , though the method of  FIG. 21  can also be used with other systems and embodiments (e.g., the systems of  FIGS. 1-3 ). 
     In step  2102  of  FIG. 21 , driver information is measured directly from the driver  1904 . In one embodiment, this driver information is measured using the driver information sensing device  1906 , as described above. In step  2104 , vehicle information is measured directly from the vehicle  1900 . In one embodiment, this vehicle information is measured using the vehicle information sensing device  1908 , as described above. 
     In step  2106 , an information transfer rate between the driver  1904  and the vehicle  1900  is calculated using the driver information measured directly from the driver  1904  in step  2102  and the vehicle information measured directly from the vehicle in step  2104 . In one embodiment, this information transfer rate is calculated using the information transfer rate module  2006 , as described above. Thus, as can be seen, the information transfer rate between the driver  1904  and the vehicle  1900  is calculated using entropy. More specifically, in some embodiments, the transfer rate is calculated, using transfer entropy and conditional entropy, as is shown above in each of equations (7) to (9). 
     At step  2108 , a baseline information transfer rate is retrieved from the baseline information transfer rate database  2008  by the driver safety factor module  2010 . As was stated above, in one embodiment, the baseline information transfer rate database  2008  contains baseline information transfer rate values for maintaining vehicular control. In some embodiments, the baseline information transfer rate database  2008  only contains one baseline information transfer rate value. In other embodiments, the baseline information transfer rate database  2008  contains at least two different baseline information transfer rate values for the driver  1904 , with each value adjusted for road conditions. Road conditions can include, but are not limited to, one or more of type of road, weather, time of day, and traffic conditions. In the event that the baseline information transfer rate database  2008  has multiple information transfer rates for the driver  1904  of vehicle  1900 , the driver safety factor module  2010  retrieves the baseline information transfer rate that most closely matches the real time road conditions for the road on which the vehicle  1900  is travelling. 
     In step  2110 , once the baseline information transfer rate is retrieved from the baseline information transfer rate database  2008 , the driver alert module  2012  is armed. Information transfer rate system  1902  arms driver alert module  2012  after a baseline information transfer rate is retrieved from the baseline information transfer rate database  2008  by the driver safety factor module. Upon arming, driver alert module  2012  is prepared to compare a predetermined driver safety alert threshold, stored in memory  2004 , to the driver safety factor calculated by the driver safety factor module  2010 . Driver alert module  2012  performs the comparison when the driver safety factor calculated by the driver safety factor module  2010  is provided to the driver alert module  2012  by driver safety factor module  2010 . 
     At step  2112 , a driver safety factor is calculated. In one embodiment, the driver safety factor is the ratio of the calculated rate of information transfer to a predetermined information transfer rate. In one embodiment, the driver safety factor is calculated by the driver safety factor module  2010 , as described above, using the information transfer rate calculated in step  2106  and the baseline information transfer rate retrieved from the baseline information transfer rate database  2008  in step  2108 . 
     In step  2114 , the driver safety factor calculated in step  2112  is compared to a predetermined driver safety alert threshold. In one embodiment, this comparison is performed by the driver alert module  2012 , as described above. In step  2116 , the driver  1904  is alerted if the driver safety factor value does not exceed the predetermined driver safety alert threshold value. The driver safety factor and predetermined driver safety alert threshold data type can be, but is not limited to, numeric, non-numeric, discrete, or continuous. In one embodiment, if the comparison made by the driver alert module  2012  in step  2114  indicates that the driver safety factor does not exceed the predetermined driver safety alert threshold, then the driver  1904  is alerted using the driver alert device  1910 , as described above. Accordingly, an accurate measurement of information transfer from the driver to the vehicle can be monitored and this measurement can be used to determine a driver state (e.g., a safety factor) to provide accurate warnings to the driver and/or modify control of vehicles according to the driver state. 
     As discussed in conjunction with  FIGS. 1A, 1B, 2 , and the motor vehicle  100 , the vehicle systems  126  and the exemplary monitoring systems can include various sensors and sensing devices. Exemplary sensors and sensing devices will now be discussed in more detail. These exemplary sensors and sensing devices are applicable to the vehicle systems of  FIG. 2  and the monitoring systems of  FIG. 3 , as well as the other monitoring systems discussed herein. As discussed in more detail above, the sensors can be contact sensors and/or contactless sensors and can include electric current/potential sensors (e.g., proximity, inductive, capacitive, electrostatic), subsonic, sonic, and ultrasonic sensors, vibration sensors (e.g., piezoelectric) visual, photoelectric or oxygen sensors, among others. The sensors can be configured to sense, physiological, biometric, behaviors parameters of the driver and or parameters related to the vehicle and vehicle systems. 
     Additionally, the sensors and/or sensing devices can be organized in different configurations and/or disposed in one or more positions. For example, the sensors could be integrated into a seat, door, dashboard, steering wheel, center console, roof, or any other portion of the motor vehicle  100 . In other cases, however, the sensors could be portable sensors worn by a driver, integrated into a portable device carried by the driver, integrated into an article of clothing worn by the driver (e.g., a watch, a piece of jewelry, clothing articles) or integrated into the body of the driver (e.g. an implant). Additionally, the sensors can be located in any position proximate to the individual or on the individual, in a monitoring device, such as a heart rate monitor, in a portable device, such as, a mobile device, a laptop or similar devices. Further, the monitoring device (e.g., a portable device) may also contain stored monitoring information or provide access to stored monitoring information on the Internet, other networks, and/or external databases. 
     As discussed above, the sensors could be disposed in any portion of the motor vehicle  100 , for example, in a location proximate to the driver  102 . For example, a proximity sensor  184  is located in the headrest  174 . In another embodiment, the bio-monitoring sensor  180  is located in the vehicle seat  168 . In a further embodiment, a sensor (not shown) could be located on or in the steering wheel  134 . In other embodiments, however, the sensors could be located in any other portion of motor vehicle  100 , including, but not limited to an armrest, dashboard, seat, seat belt, rear-view mirror, as well as any other location. 
     Further, the sensors, the sensing devices and/or the vehicle systems and monitoring systems, can process and analyze the stimulus sensed from the sensor and/or the sensing device in various ways to generate a data stream or signal representing the sensed stimulus. In some embodiments, the stimulus sensed is processed according to the location of the sensors and/or the sensing device. In other embodiments, the stimulus sensed is processed based on the quality of the data or processed based on what type of stimulus is being sensed. Other configurations of processing and analysis can also be implemented. 
     It is understood that monitoring systems for vehicular monitoring can include other vehicle systems and sensors discussed herein, for example, the vehicle systems and sensors discussed in Section III (A) and shown in  FIG. 2 , the physiological monitoring systems discussed in Section III (B)(1), the behavioral monitoring systems discussed in Section III (B)(2), and the identification systems and sensors discussed in Section III (B)(4) can be types of monitoring systems for physiological monitoring. Further, it is appreciated, that any combination of vehicle systems and sensors, physiological monitoring systems, behavioral monitoring systems, vehicular monitoring systems, and identification systems can be implemented to determine and/or assess one or more driver states based on vehicle information. 
     4. Identification Systems and Sensors 
     In some embodiments, the systems and sensors discussed above as well as the methods and systems for responding to driver state discussed herein can identify a particular driver to monitor information about the driver. Further, identification of the driver can provide customized or normative baseline data for a particular driver. Thus, in one embodiment, the monitoring systems of  FIG. 3  can be used for personal identification of the driver. In particular, the heart rate monitoring system  302  can include any devices or systems for monitoring the heart information of a driver. In one embodiment, the heart rate monitoring system  302  includes heart rate sensors  304  that facilitate systems and methods for personal identification of a driver, as discussed in U.S. Pat. No. 9,272,689, entitled System and Method for Biometric Identification in a Vehicle, which is incorporated by reference in its entirety herein. The &#39;899 application will now be discussed, however, for brevity, the &#39;899 application will not be discussed in its entirety. 
     Referring now to  FIG. 22 , a computer system  2200  for personal identification of an individual, specifically, of a vehicle occupant (e.g., a driver, one or more passengers) is shown. As will be described in further detail below, the biometric identification systems and methods described herein can be utilized in conjunction with said vehicle systems to provide entry, access, activation, control and personalization or modification of said vehicle systems and associated data. 
     The computer system  2200  includes a computing device  2202  communicatively coupled to a monitoring system  2204  and a plurality of vehicle systems  2206 . It is appreciated that the ECU  106  of  FIGS. 1A and 1B  can include similar components and executed functions similar to the computing device  2202 . For example, the ECU  106  includes a plurality of vehicle systems  126  and monitoring systems  300  ( FIG. 3 ). Further, the computer system  2200  can be implemented within a vehicle for example, the motor vehicle  100  of  FIG. 1A , and can include and/or communicate with similar components and systems of the motor vehicle  100  (e.g., the vehicle system  126 ). 
     The monitoring system  2204  can include and/or communicate with various sensors. Specifically, with reference to  FIG. 1A , the sensors can include a first sensor (e.g., a proximity sensor  184 ) in a headrest  174 , a second sensor (e.g., a bio-monitoring sensor  180 ) in a vehicle seat  168 . A touch steering wheel  134  may also include sensors (not shown) for identifying driver state changes. Further, the monitoring system  2204  can include and/or communicate with optical and image sensors, for example, a camera (e.g., an optical sensor  162 ). 
     The vehicle systems  2206  can also include data storage mechanism (e.g., memory) for storing data utilized by said vehicle systems, for example, sensitive data such as contact data, route data, password data, vehicle occupant profiles, driver behavior profiles, email, among others. As will be described in further detail below, the biometric identification systems and methods described herein can be utilized in conjunction with said vehicle systems to provide entry, access, activation, control and personalization or modification of said vehicle systems and associated data. 
     Referring again to  FIG. 22 , the monitoring system  2204  is configured to monitor and measure monitoring information associated with an individual and transmit the information to the computing device  2202 . The monitoring information can be used to determine biometric identification of a vehicle occupant and thereby control the vehicle (i.e., entry, access, activation, personalization, and modification of vehicle systems) based on biometric identification. It is appreciated that the monitoring information and the biometric identification disclosed herein can be utilized with other systems associated with the vehicle and the vehicle occupant, including, but not limited to, vehicle systems  126 , wellness and distraction systems or modifications of such systems based on the biometric identification. 
     In the illustrated embodiment, the monitoring system  2204  includes a plurality of sensors  2208  for monitoring and measuring the monitoring information. The sensors  2208 , sense a stimulus (e.g., a signal, property, measurement or quantity) using various sensor technologies and generate a data stream or signal representing the stimulus. The computing device  2202  is capable of receiving the data stream or signal representing the stimulus directly from the sensors  2208  or via the monitoring system  2204 . As discussed above, various types of sensors, sensor configurations, sensor placement and analysis can be utilized. In one embodiment, the monitoring system  2204  and/or the sensors  2208  can include a transceiver (not shown) for transmitting a signal towards a vehicle occupant and receiving a reflected signal after transmitting the signal from the vehicle occupant. The transceiver can include one or more antennas (not shown) to facilitate transmission of the signal and reception of the reflected signal. 
     With reference to  FIG. 23 , a computer implemented method is shown for identifying a vehicle occupant (e.g., a driver  102  of  FIG. 1A ). In different embodiments, the various steps of the method can be accomplished by one or more different systems, devices or components. In some cases, the steps may be accomplished by the ECU  106  of  FIG. 1B  including the processor  108 . For each method discussed and illustrated in the figures, it will be understood that in some embodiments one or more of the steps could be optional. For purposes of reference, the method of  FIG. 23  will be discussed with components shown in  FIGS. 1A, 1B, 2, 3, and 22 . Moreover, cardiac activity or a measurement of cardiac activity, as used herein, refers to events related to the flow of blood, the pressure of blood, the sounds and/or the tactile palpations that occur from the beginning of one heart beat to the beginning of the next heart beat or the electrical activity of the heart (e.g., EKG). 
     At step  2302 , the method includes receiving a signal from a plurality of sensors. The signal can indicate a measurement of cardiac activity, for example, the signal can be a cardiac signal representing one or more of a heart beat or a heart rate of the vehicle occupant. In one embodiment, discussed in detail below, the method includes transmitting a signal towards the vehicle occupant and receiving a reflected signal, the reflected signal indicating a measurement of cardiac activity. It is appreciated that the monitoring system  2204  can be configured to monitor cardiac activity of a vehicle occupant from the plurality of sensors  1088  and facilitate transmission of signals to the computing device  2202 . 
     The plurality of sensors  2208  are operative to sense a biological characteristic (e.g., cardiac activity) of the vehicle occupant in the vehicle utilizing contact sensors, contactless sensors, or both contact and contactless sensors. As discussed above, in one embodiment, a sensor can receive a signal indicating a measurement of cardiac activity produced by the vehicle occupant upon direct contact of the sensor to the vehicle occupant. In another embodiment, a sensor can sense a field change (e.g., magnetic, radio frequency) and/or receive a signal (e.g., signal reflection) indicating a measurement of cardiac activity produced by the vehicle occupant without direct contact of the sensor to the vehicle occupant. I 
     In particular, the method for identifying a vehicle occupant can further include a sensor that produces a field or transmits a signal towards the vehicle occupant. The sensors can sense a change in the field produced by the vehicle occupant or receive a reflected signal produced by the vehicle occupant after the signal reflects from the vehicle occupant. Specifically, a sensor can be configured to transmit a signal towards a thoracic region (i.e., general chest and/or back area near the heart) of the vehicle occupant. The reflected signal can indicate cardiac activity, for example, a cardiac signal. Signal reflection and magnetic and/or electric field sensing sensor technology can be utilized with different types of signals and sensors, as discussed above, and include, but are not limited to, electric current/potential sensors and/or sonic sensors, among others. 
     In the illustrated embodiment, the receiving module  2218  can be further configured to process the signal thereby generating a proxy of the signal in a particular form. It is appreciated that the sensors  2208  or the monitoring system  2204  can also perform processing functions. Processing can include amplification, mixing, and filtering of the signal as well as other signal processing techniques known in the art. Processing can also include modifying or converting the signal into a form allowing identification of biometric features. For example, the signal can be processed into a cardiac waveform, an electrocardiograph (EKG) waveform, or a proxy of an EKG waveform for identification analysis. 
     As discussed above, the sensors  2208  generate a signal representing the stimulus measured. The signal and the signal features vary depending on the property (i.e., the physiological, biological, or environmental characteristic) sensed the type of sensor and the sensor technology.  FIGS. 9A, 9B, 10A, 10B, 10C, 10D , discussed above, are exemplary cardiac waveforms with signal features reoccurring over a period of time. 
     Referring specifically to  FIGS. 9A and 9B , it is shown that each portion of a heartbeat produces a difference deflection on the EKG waveform A 400 . These deflections are recorded as a series of positive and negative waves, namely, waves P, Q, R, S, and T. The Q, R, and S waves comprise a QRS complex  904 , which indicates rapid depolarization of the right and left heart ventricles. The P wave indicates atrial depolarization and the T wave indicates atrial repolarization. Each wave can vary in duration, amplitude and form in different individuals. In  FIG. 9B  the R waves are indicated by the peaks  916 ,  918  and  920 . These waves and wave characteristics, or a combination thereof, can be identified as signal features for biometric identification. 
     Other signal features include wave durations or intervals, namely, PR interval  906 , PR segment  908 , ST segment  910  and ST interval  912 , as shown in  FIG. 9A . The PR interval  906  is measured from the beginning of the P wave to the beginning of the QRS complex  904 . The PR segment  908  connects the P wave and the QRS complex  904 . The ST segment  910  connects the QRS complex  904  and the T wave. The ST interval  912  is measured from the S wave to the T wave. It is to be appreciated that other intervals (e.g., QT interval) can be identified from the EKG waveform  902 . Additionally, beat-to-beat intervals (i.e., intervals from one cycle feature to the next cycle feature), for example, an R-R interval (i.e., the interval between an R wave and the next R wave), may also be identified.  FIG. 9B  illustrates a series of cardiac waveforms over a period of time indicated by element  914 . In  FIG. 9B  the R waves are indicated by the peaks  916 ,  918  and  920 . Further, R-R intervals are indicated by elements  922  and  924 . 
     Referring back to  FIG. 23  and step  2304 , the method further includes determining a biomarker based on biometric features of the signal. The biometric features can include characteristics (i.e. signal features) analyzed, identified, and/or extracted from the signal. The biomarker module  2220  can be configured to determine the biomarker. For example, biometric features of a cardiac waveform (e.g., the cardiac waveforms illustrated in  FIGS. 9A, 9B, 10A, 10B, 10C, 10  can include waves P, Q, R, S and T or a series of said waves. Other characteristics can include intervals, time duration of characteristics, and wave amplitude among others. The biomarker uniquely identifies the vehicle occupant and can be any combination of biometric features extracted from the signal. The biomarker may include comparisons of one or more of wave amplitude, form, and duration as well as ratios of these features for one wave compared to another wave. The biomarker is a unique identification feature of a vehicle occupant and thereby provides ultra-security and authorization when used in conjunction with vehicle systems described herein. It is appreciated that other information can be used alone or in combination with the biometric features of the signal to determine a biomarker. For example, other information can include, but is not limited to, the psychological and environmental information received and or monitored by the monitoring system  1084 . For example, facial feature extraction data (acquired by and optical sensor  162 ). 
     Further, in the case where multiple cardiac waveforms are obtained for a vehicle occupant, analysis of the heartbeat over time (i.e., beat-to-beat analysis, heart rate variability) can be performed and used to obtain the biometric features and/or a biomarker. For example, heart rate variability analysis methods known in the art include time-domain methods, geometric methods, frequency-domain methods, non-linear methods, and long term correlations. Different metrics can be derived using these methods. For example, a beat-to-beat standard deviation (SDNN), a square root of the mean squared difference of successive beat-to-beat intervals (RMSSD), a set of R-R intervals, among others. 
     At step  2306 , the method includes identifying the vehicle occupant. For example, the identification module  2222  can compare the biomarker identified at step  2304  to a stored biomarker in the memory  2214  associated with the vehicle occupant. The biomarker may also be stored and accessed via the portable device  122  ( FIG. 1A ). In another embodiment, the identification module  2222  can identify the vehicle occupant by comparing the biometric features with stored biometric features stored in a personal identification profile associated with the vehicle occupant in the memory  2214  or accessed via the communication module  2216  (e.g., an external database via a network). The stored biometric features or the biomarker can be based on the signal and acquired prior to using the system for personal identification. For example, the biomarker module  2220  can collect baseline metrics from the vehicle occupant during a vehicle learning mode. A biomarker or biometric features that uniquely identify the vehicle occupant, as discussed above, can be determined and stored in the memory  2214  for future use with the above described methods and systems. For example, the biomarker module  22220  can then save the biomarker in a personal identification profile associated with the vehicle occupant. 
     At step  2308 , the identification can be transmitted by the communication module  2216  to one of the plurality of vehicle systems  2206  and access, entry, activation, control, and personalization or modification of the vehicle systems  2206  can be implemented based on the identification. In another embodiment, the communication module  2216  can transmit the identification to an external database or to a portable device. In one exemplary use of biometric identification, entry to a vehicle (e.g., vehicle door lock/unlock) is granted to a driver based on the biometric identification. For example, the computer system  2200 , and in particular the computing device  2202  and the monitoring system  2204  and/or the sensors  2208  can be integrated with a portable device (e.g., the portable device  122 ) or a key fob. The sensors  2208  can detect a change in an electric field produced by the vehicle occupant indicating a measurement of cardiac activity (e.g., an EKG) via the key fob outside of the vehicle. In another embodiment, the sensors  2208  in the key fob could transmit and receive a reflected signal from a driver in proximity to the portable device or the key fob outside of the vehicle. The computing device  2202  can determine a biomarker based on the signal and identify the driver based on the biomarker as described above in relation to the method of  FIG. 23 . Once the identity of the driver is known, entry to the vehicle can be granted or denied (e.g., vehicle door lock/unlock). 
     Once an identification of the driver and/or vehicle occupant is determined, the identification can be utilized in conjunction with other vehicle systems for activation of the vehicle systems or personalization and modification of the vehicle systems. In one example, collision mitigation, braking systems, driver assistance systems and algorithms used therein, can be modified based on the identification to provide a tailored driving experience to the driver and/or the vehicle occupant. Further, pattern learning machine algorithms can be used to track data associated with an identified driver and the pattern learning can be used to modify different vehicle systems and parameters as discussed herein. In some embodiments, the driver can be associated with a user (e.g., driver) profile including parameters, data, and data tracked overtime specific to the driver. This user profile can be used by the vehicle systems for operation based on the identified user. In one embodiment, the ECU  106  can store the user profile at the memory  110  and/or disk  112  shown in  FIG. 1A . 
     In another embodiment, identification of a driver can be used to determine a driver state as will be discussed herein. For example, information stored in the identified driver&#39;s user profile can be compared to monitoring information to determine a driver state. As an illustrative example, stored steering information in the user profile can be compared to steering information received from the touch steering wheel system  134 . This comparison can provide an indication of driver state. 
     Other known driver identification methods can also be used to identify a driver and thus enable the customization and personalization of one or more vehicle systems. For example, methods such as facial recognition, iris recognition, and fingerprint recognition could be used. Further, the data used for driver identification can be stored and/or received from external devices such as a portable device  122  (e.g., a smartphone, a smart watch). Further, it is appreciated that other vehicle systems and data associated with said vehicle systems can be controlled and/or operated based on the identification. Moreover, the identification could be transmitted to an application (i.e., a telematics application, a portable device application). Biometric identification, as discussed herein, provides a unique, accurate, and secure measurement for entry, access, control, activation, personalization and modification of various vehicle systems and vehicle system data. In addition, by identifying the driver, the physiological information, behavioral information and vehicle information can be collected for that particular driver to modify control parameters, control coefficients and thresholds as will be discussed in more detail in Section IV (B) (2). 
     It is appreciated that the systems, sensors, and sensor analysis discussed above can be used alone and/or in combination to obtain and assess information about a vehicle and a driver state. The systems and methods described below for determining one or more driver states can utilized one or more of the above mentioned systems, sensors and sensor analysis to obtain information to determine the one or more driver states, including vehicle information, physiological information and behavioral information, among others. 
     It is understood that identification systems and sensors can include other vehicle systems and sensors discussed herein, for example, the vehicle systems and sensors discussed in Section III (A) and shown in  FIG. 2 , the physiological monitoring systems discussed in Section III (B) (1), the behavioral monitoring systems discussed in Section III (B) (2), and the vehicular monitoring systems discussed in Section III (B) (3) can be types of identification systems. Further, it is appreciated, that any combination of vehicle systems and sensors, physiological monitoring systems, behavioral monitoring systems, vehicular monitoring systems, and identification systems can be implemented to determine and/or assess one or more driver states based on identification information. 
     IV. Determine One or More Driver States 
     A motor vehicle can include provisions for assessing the state of a driver and automatically adjusting the operation of one or more vehicle systems in response to the driver state or a level of the driver state. As discussed above in detail in Section I above, a “driver state,” can refer to a measurement of a state of the biological being and/or a state of the environment of the biological being (e.g., a vehicle). A driver state or alternatively a “being state” can be one or more of alert, vigilant, drowsy, inattentive, distracted, stressed, intoxicated, other generally impaired states, other emotional states and/or general health states, among others. Throughout this specification, drowsiness and/or distractedness will be used as the example driver state being assessed. However, it is understood that any driver state could be determined and assessed, including but not limited to, drowsiness, attentiveness, distractedness, vigilance, impairedness, intoxication, stress, emotional states and/or general health states, among others. 
     In some embodiments, the motor vehicle can include provisions for assessing one or more states of a driver and automatically adjusting the operation of one or more vehicle systems in response to the one or more driver states or one or more levels of the driver states. Specifically, the systems and methods for responding to driver state discussed herein can include determining and/or assessing one or more driver states based on information from the systems and sensors discussed in Section II and/or III above. 
     In one embodiment, a response system can receive information about the state of a driver and automatically adjust the operation of one or more vehicle systems. As mentioned above with reference to  FIG. 1A , for purposes of convenience, various components, alone or in combination, discussed above, can be referred to herein as the response system  188 . In some cases, the response system  188  comprises the ECU  106  as well as one or more sensors, components, devices or systems discussed above. In some cases, the response system  188  can receive input from various devices related to the state of a driver. In some cases, this information is monitoring information as discussed above in Section III (B). The response system  188  can use this information to modify the operation of one or more of the vehicle systems  126 . Moreover, it will be understood that in different embodiments, the response system  188  could be used to control any other components or systems utilized for operating the motor vehicle  100 . 
     As mentioned briefly above, the response system  188  can include provisions for determining one or more driver states. The driver state can be based on physiological information, behavioral information and/or vehicle information. For example, the response system  188  could detect a driver state for a driver by analyzing heart information, breathing rate information, brain information, perspiration information, as well as any other kinds of autonomic information. Additionally, the response system  188  could detect a driver state for a driver by analyzing information from one or more vehicle systems and/or one or more monitoring systems. Further, in some embodiments, the response system  188  could determine one or more driver states and a combined driver state based on the one or more driver states. 
     The following detailed description discusses a variety of different methods for operating vehicle systems in response to a driver state. In different embodiments, the various different steps of these processes can be accomplished by one or more different systems, devices or components. In some embodiments, some of the steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the steps can be accomplished by the ECU  106  of a motor vehicle  100 . In other embodiments, some of the steps could be accomplished by other components of a motor vehicle, including but not limited to, the vehicle systems  126 . For each process discussed below and illustrated in the Figures it will be understood that in some embodiments one or more of the steps could be optional. Additionally, it will be appreciated that each system and method discussed below is applicable to embodiments that determine one or more driver states or combine driver states as will be discussed in further detail herein. 
       FIG. 24A  illustrates an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on the state of the driver. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  2402 , the response system  188  can receive monitoring information. In some cases, the monitoring information can be received from one or more sensors. In other cases, the monitoring information can be received from one or more monitoring systems. In still other cases, the monitoring information can be received from one or more vehicle systems. In still other cases, the monitoring information can be received from any other device of the motor vehicle  100 . In still other cases, the monitoring information can be received from any combination of sensors, monitoring systems (e.g., the monitoring systems  300 ), vehicles systems, or other devices. For example, and as discussed above, the monitoring information can be received from physiological monitoring systems and sensors, behavioral monitoring systems and sensors, vehicular monitoring systems and sensors, identification systems and sensors, or any combination thereof. 
     In step  2404 , the response system  188  can determine the driver state. In some cases, the driver state can be normal or drowsy. In other cases, the driver state can range over three or more states ranging between normal and very drowsy (or even asleep). In still other cases, the driver state can be normal or distracted. In other cases, the driver state can be alert, normal, distracted, or drowsy. In other cases, the driver state can range over three or more states ranging between normal and very distracted. In this step, the response system  188  can use any information received during step  2402 , including information from any kinds of sensors or systems. For example, in one embodiment, response system  188  can receive information from an optical sensing device that indicates the driver has closed his or her eyes for a substantial period of time. In another embodiment, response system  188  can receive information from an optical sensing device that indicates the driver is not looking forward. Other examples of determining the state of a driver are discussed in detail below. 
     In step  2406 , the response system  188  can determine whether the driver is distracted or other diminished state, for example drowsy. If the driver is not distracted, the response system  188  can proceed back to step  2402  to receive additional monitoring information. If, however, the driver is distracted, the response system  188  can proceed to step  2408 . In step  2408 , the response system  188  can automatically modify the control of one or more vehicle systems, including any of the vehicle systems discussed above. By automatically modifying the control of one or more vehicle systems, the response system  188  can help to avoid various hazardous situations that can be caused by a drowsy and/or distracted driver. 
     As discussed above, at step  2408 , if the driver is distracted the response system  188  can automatically modify the control of one or more vehicle systems, including any of the vehicle systems discussed above. However, in some embodiments, a user may not want any vehicle systems modified or adjusted. In these cases, the user can switch a user input device  152 , or a similar kind of input device, to the OFF position. This could have the effect of turning off all driver state monitoring and would further prevent the response system  188  from modifying the control of any vehicle systems. Moreover, the response system  188  could be reactivated at any time by switching user input device  152  to the ON position. In other embodiments, additional switches or buttons could be provided to turn on/off individual monitoring systems. 
     In a further embodiment, the response system  188  can automatically override, cancel, or turn OFF the modification or adjustment of one or more vehicle systems based on the driver state. For example, if at step  2406  it is determined the driver state is not distracted (e.g., alert, vigilant), the response system  188  can automatically turn off all driver state monitoring and prevent the response system  188  from modifying the control of any vehicle systems. The response system  188  can automatically reactivate the driver state monitoring upon detecting a driver state that is distracted (e.g., not alert, not vigilant, drowsy). In another embodiment, the response system  188  can automatically override and/or cancel the modification or adjustment of one or more vehicle systems based on the driver state and information from one or more vehicle systems  126  (e.g., a vehicular state). As an illustrative example, if the driver state is vigilant (e.g., alert, not drowsy) and the blind spot indicator system  224  indicates a target vehicle is not present in a blind spot monitoring zone, the response system  188  can turn off warnings and modifications from the lane departure warning system  222  for lane departures toward said blind spot monitoring zone. These embodiments will be described in more detail herein. 
       FIG. 24B  illustrates an embodiment of a process for controlling one or more vehicle systems in a motor vehicle depending on the state of the driver similar to  FIG. 24A  but with identification of a driver. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  2410 , the response system  188  can receive monitoring information. In some cases, the monitoring information can be received from one or more sensors. In other cases, the monitoring information can be received from one or more monitoring systems. In still other cases, the monitoring information can be received from one or more vehicle systems. In still other cases, the monitoring information can be received from any other device of the motor vehicle  100 . In still other cases, the monitoring information can be received from any combination of sensors, monitoring systems (e.g., the monitoring systems  300 ), vehicles systems, or other devices. For example, and as discussed above, the monitoring information can be received from physiological monitoring systems and sensors, behavioral monitoring systems and sensors, vehicular monitoring systems and sensors, identification systems and sensors, or any combination thereof. 
     In step  2412 , the response system  188  can determine the driver state. In some cases, the driver state can be normal or drowsy. In other cases, the driver state can range over three or more states ranging between normal and very drowsy (or even asleep). In still other cases, the driver state can be normal or distracted. In other cases, the driver state can be alert, normal, distracted, or drowsy. In other cases, the driver state can range over three or more states ranging between normal and very distracted. In this step, the response system  188  can use any information received during step  2410 , including information from any kinds of sensors or systems. For example, in one embodiment, response system  188  can receive information from an optical sensing device that indicates the driver has closed his or her eyes for a substantial period of time. In another embodiment, response system  188  can receive information from an optical sensing device that indicates the driver is not looking forward. Other examples of determining the state of a driver are discussed in detail below. 
     In the embodiment shown in  FIG. 24B , determining the driver state at step  2412  can include identifying the driver at step  2414 . Any of the systems and methods described above to identify the driver in Section III (B) (4) can be used for personal identification of the driver. In some embodiments, the monitoring information received at step  2410  can be used at step  2414  to identify the driver. As discussed above, once identification of the driver is determined, the identified driver can be associated with a user (e.g., driver) profile including parameters, data, and data (e.g., monitoring information) tracked overtime specific to the driver. The ECU  106  can store the user profile (not shown) at the memory  110  and/or the disk  112  shown in  FIG. 1A . 
     Accordingly, the data stored in the user profile can provide normative and baseline data of the driver, which can be used to determine a driver state. More specifically, at step  2416 , determining the driver state can include comparing stored information (e.g., the stored data/monitoring information) in the user profile with the monitoring information received at step  2410 . In some embodiments, the stored information and the monitoring information compared at step  2416  can both be associated with the same parameter, type of monitoring information, and/or vehicle system. 
     As an illustrative example, at step  2410 , the response system  188  can receive steering information from the electronic power steering system  132  and/or the touch steering wheel system  134 . The steering information can include a steering input signal, which may indicate whether the driver&#39;s steering is smooth, erratic, and/or jerky. The steering information may also include the hand position of the driver. For example, the response system  188  can determine whether the driver has zero, one or two hands on the steering wheel. The steering information received at step  2410  can be compared to stored steering information retrieved by the response system  188  from the user profile. The stored steering information can indicate a normative and/or a baseline steering input signal. The stored steering information can also indicate how many hands the user has in contact with the steering wheel  134  when the information is stored. In other words, the response system  188  can store a normative and/or baseline steering input signal for the driver when the driver is using one hand and also when the driver is using two hands. Accordingly, if the stored steering information is a steering input signal that indicates, while using one hand, the driver&#39;s steering is normally smooth and the steering information received at step  2410  indicates, while using one hand, the driver&#39;s steering is erratic, the driver state may be determined to be distracted at step  2412 . Said differently, if the stored steering information is inconsistent with the steering information received at step  2410 , the driver state may be determined to be distracted at step  2412 . This can also apply to steering input signals where the driver is using two hands on the steering wheel  134 . In addition, if the driver&#39;s stored steering information indicates that the driver&#39;s one-handed use of the steering wheel is smoother and less erratic than the driver&#39;s two-handed use of the steering wheel, then the system can adjust any vehicle system modifications discussed in Section VI accordingly. 
     At step  2418 , the response system  188  can determine whether the driver is distracted or other diminished state, for example drowsy. If the driver is not distracted, the response system  188  can proceed back to step  2410  to receive additional monitoring information. If, however, the driver is distracted, the response system  188  can proceed to step  2420 . In step  2420 , the response system  188  can automatically modify the control of one or more vehicle systems, including any of the vehicle systems discussed above. By automatically modifying the control of one or more vehicle systems, the response system  188  can help to avoid various hazardous situations that can be caused by a drowsy and/or distracted driver. 
     As discussed above, at step  2420 , if the driver is distracted the response system  188  can automatically modify the control of one or more vehicle systems, including any of the vehicle systems discussed above. Referring to the illustrative example discussed above, if it is determined the driver is distracted based on the comparison of steering information, the response system  188  can modify the electronic power steering system  132  to provide more assistance based on the driver state. 
       FIG. 25  is a table emphasizing the response system  188  impact on various vehicle systems due to changes in the driver&#39;s state, as well as the benefits to the driver for each change according to one embodiment. In particular, column  2502  lists the various vehicle systems, which include many of the vehicle systems  126  discussed above and shown in  FIG. 2 . Column  2504  describes how response system  188  affects the operation of each vehicle system when the driver&#39;s state is such that the driver can be distracted, drowsy, less attentive, and/or impaired. Column  2506  describes the benefits for the response system impacts described in column  2504 . Column  2508  describes the type of impact performed by response system  188  for each vehicle system. In particular, in column  2508  the impact of response system  188  on each vehicle system is described as either “control” type or “warning” type. The control type indicates that the operation of a vehicle system is modified by the control system. The warning type indicates that the vehicle system is used to warn or otherwise alert a driver. 
     As indicated in  FIG. 25 , upon detecting that a driver is drowsy or otherwise inattentive, the response system  188  can control the electronic stability control system  202 , the antilock brake system  204 , the brake assist system  206 , and the brake prefill system  208  in a manner that compensates for the potentially slower reaction time of the driver. For example, in some cases, response system  188  can operate the electronic stability control system  202  to improve steering precision and enhance stability. In some cases, response system  188  can operate the antilock brake system  204  so that the stopping distance is decreased. In some cases, response system  188  can control the brake assist system  206  so that an assisted braking force is applied sooner. In some cases, response system  188  can control the brake prefill system  208  so the brake lines are automatically prefilled with brake fluid when a driver is drowsy. These actions can help to improve the steering precision and brake responsiveness when a driver is drowsy. 
     Additionally, upon detecting that a driver is distracted, drowsy or otherwise inattentive, the response system  188  can control the low speed follow system  212 , the cruise control system  214 , the automatic cruise control system  216 , the collision warning system  218 , the collision mitigation braking system  220 , the lane departure warning system  222 , the blind spot indicator system  224  and the lane keep assist system  226  to provide protection due to the driver&#39;s lapse of attention. For example, the low speed follow system  212 , the cruise control system  214 , and the lane keep assist system  226  could be disabled when the driver is distracted and/or drowsy to prevent unintended use of these systems. Likewise, the collision warning system  218 , the collision mitigation braking system  220 , the lane departure warning system  222 , and the blind spot indicator system  224  could warn a driver sooner about possible potential hazards. In some cases, the automatic cruise control system  216  could be configured to increase the minimum gap distance between the motor vehicle  100  and the preceding vehicle. 
     In some embodiments, upon detecting that a driver is drowsy or otherwise inattentive, the response system  188  can control the electronic power steering system  132 , the visual devices  140 , the audio devices  144 , the tactile devices  148 , the climate control system  234  (such as HVAC), and the electronic pretensioning system  236  for a seat belt to supplement the driver&#39;s alertness. For example, the electronic power steering system  132  can be controlled to decrease power steering assistance. This requires the driver to apply more effort and can help improve awareness or alertness. The visual devices  140  and the audio devices  144  can be used to provide visual feedback and audible feedback, respectively. The tactile devices  148  and the electronic pretensioning system  236  can be used to provide tactile feedback to a driver. In addition, the climate control system  234  can be used to change the cabin or driver temperature to effect the drowsiness of the driver. For example, by changing the cabin temperature the driver can be made more alert. 
     The various systems listed in  FIG. 25  are only intended to be exemplary and other embodiments could include additional vehicle systems that can be controlled by the response system  188 . Moreover, these systems are not limited to a single impact or function. In addition, these systems are not limited to a single benefit. Instead, the impacts and benefits listed for each system are intended as examples. A detailed explanation of the control of many different vehicle systems is discussed in detail below and shown in the Figures. 
     A response system can include provisions for determining a level of drowsiness for a driver and/or a level of distraction for a driver. The term “level of drowsiness” as used throughout this detailed description and in the claims refers to any numerical or other kind of value for distinguishing between two or more states of drowsiness. For example, in some cases, the level of drowsiness can be given as a percentage between 0% and 100%, where 0% refers to a driver that is totally alert and 100% refers to a driver that is fully drowsy or even asleep. In other cases, the level of drowsiness could be a value in the range between 1 and 10. In still other cases, the level of drowsiness is not a numerical value, but could be associated with a given discrete state, such as “not drowsy,” “slightly drowsy,” “drowsy,” “very drowsy” and “extremely drowsy.” Moreover, the level of drowsiness could be a discrete value or a continuous value. In some cases, the level of drowsiness can be associated with a driver state index, which is discussed in further detail below. 
     The term “level of distraction” as used throughout this detailed description and in the claims refers to any numerical or other kind of value for distinguishing between two or more states of distraction. For example, in some cases, the level of distraction can be given as a percentage between 0% and 100%, where 0% refers to a driver that is totally attentive and 100% refers to a driver that is fully distracted. In other cases, the level of distraction could be a value in the range between 1 and 10. In still other cases, the level of distraction is not a numerical value, but could be associated with a given discrete state, such as “not distracted,” “slightly distracted,” “distracted”, “very distracted” and “extremely distracted”. Moreover, the level of distraction could be a discrete value or a continuous value. In some cases, the level of distraction can be associated with a driver state index, which is discussed in further detail below. In further cases, the level of distraction can indicate the driver is engaged in a secondary task (e.g., other than the primary task of driving). 
       FIG. 26  illustrates an embodiment of a process of modifying the operation of a vehicle system according to the level of distraction detected. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  2602 , response system  188  can receive monitoring information. In some cases, the monitoring information can be received from one or more sensors. In other cases, the monitoring information can be received from one or more autonomic monitoring systems. In still other cases, the monitoring information can be received from one or more vehicle systems. In still other cases, the monitoring information can be received from any other device of the motor vehicle  100 . In still other cases, the monitoring information can be received from any combination of sensors, monitoring systems, vehicles systems or other devices. For example, and as discussed above, the monitoring information can be received from physiological monitoring systems and sensors, behavioral monitoring systems and sensors, vehicular monitoring systems and sensors, identification systems and sensors, or any combination thereof. 
     In step  2604 , the response system  188  can determine if the driver is distracted (e.g., not alert, drowsy). If the driver is not distracted, the response system  188  can return back to step  2602 . If the driver is distracted, the response system  188  can proceed to step  2606 . In step  2606 , the response system  188  can determine the level of distraction (e.g., drowsiness). As discussed above, the level of distraction could be represented by a numerical value or could be a discrete state labeled by a name or variable. In step  2608 , the response system  188  can modify the control of one or more vehicle systems according to the level of distraction. 
     Examples of systems that can be modified according to the level of distraction include, but are not limited to: the electronic stability control system  202 , the antilock brake system  204 , the brake assist system  206 , the brake prefill system  208 , the EPB system  210 , the low speed follow system  212 , the automatic cruise control system  216 , the collision warning system  218 , the lane keep assist system  226 , the blind spot indicator system  224 , the climate control system  234 , and the electronic pretensioning system  236 . In addition, the electronic power steering system  132  could be modified according to the level of distraction, as could the visual devices  140 , the audio devices  144 , and the tactile devices  148 . In some embodiments, the timing and/or intensity associated with various warning indicators (visual indicators, audible indicators, haptic indicators, etc.) could be modified according to the level of distraction. For example, in one embodiment, the electronic pretensioning system  236  could increase or decrease the intensity and/or frequency of automatic seat belt tightening to warn the driver at a level appropriate for the level of distraction. 
     As an example, when a driver is extremely distracted (e.g., extremely drowsy), the antilock brake system  204  can be modified to achieve a shorter stopping distance than when a driver is somewhat distracted. The level of brake assistance provided by the brake assist system  206  could be varied according to the level of drowsiness, with assistance increased with distraction. As another example, the brake prefill system  208  could adjust the amount of brake fluid delivered during a prefill or the timing of the prefill according to the level of distraction. In addition, the headway distance for the automatic cruise control system  216  could be increased with the level of distraction. In addition, the error between the yaw rate and the steering yaw rate determined by electronic stability control system  202  could be decreased in proportion to the level of distraction. In some cases, the collision warning system  218  and the lane departure warning system  222  could provide earlier warnings to a distracted driver, where the timing of the warnings is modified in proportion to the level of distraction. Likewise, the detection area size associated with the blind spot indicator system  224  could be varied according to the level of distraction. In some cases, the strength of a warning pulse generated by the electronic pretensioning system  236  can vary in proportion to the level of drowsiness. 
     In addition, the climate control system  234  can vary the number of degrees that the temperature is changed according to the level of distraction. Moreover, the brightness of the lights activated by the visual devices  140  when a driver is distracted could be varied in proportion to the level of distraction. In addition, the volume of sound generated by the audio devices  144  could be varied in proportion to the level of distraction. In addition, the amount of vibration or tactile stimulation delivered by the tactile devices  148  could be varied in proportion to the level of distraction. In some cases, the maximum speed at which the low speed follow system  212  operates could be modified according to the level of distraction. Likewise, the ON/OFF setting or the maximum speed at which the cruise control system  214  can be set can be modified in proportion to the level of distraction. Additionally, the degree of power steering assistance provided by the electronic power steering system  132  could be varied in proportion to the level of distraction. In addition, the distance that the collision mitigation braking system  220  begins to brake can be lengthened or the lane keep assist system  226  could be modified so that the driver must provide more input to the system. 
       FIG. 27  illustrates another embodiment of a process of modifying the operation of a vehicle system according to the level of drowsiness detected. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , the including response system  188 . 
     In step  2702 , the response system  188  can receive monitoring information, as discussed above and with respect to step  2602  of  FIG. 26 . In step  2704 , the response system  188  can receive any kind of vehicle operating information from one or more vehicle systems. The type of operating information received during step  2704  can vary according to the type of vehicle system involved. For example, if the current process is used for operating a brake assist system, the operating information received can be brake pressure, vehicle speed and other operating parameters related to a brake assist system. As another example, if the current process is used for operating an electronic stability control system, the operation information can include yaw rate, wheel speed information, steering angle, lateral G, longitudinal G, road friction information as well as any other information used for operating an electronic stability control system. 
     Next, in step  2706 , the response system  188  can determine a driver state index of the driver. The term “driver state index” refers to a measure of the drowsiness and/or distractedness of a driver. In some cases, the driver state index could be given as a numerical value. In other cases, the driver state index could be given as a non-numerical value. Moreover, the driver state index can range from values associated with complete alertness to values associated with extreme drowsiness or even a state in which the driver is asleep. In one embodiment, the driver state index could take on the values 1, 2, 3 and 4, where 1 is the least drowsy and 4 is the most drowsy. In another embodiment, the driver state index could take on values from 1-10. Further, the driver state index can range from values associated with complete attentiveness to values associated with extreme distraction. In one embodiment, the driver state index could take on the values 1, 2, 3 and 4, where 1 is the least distracted and 4 is the most distracted. 
     In step  2708 , the response system  188  can determine a control parameter. The term “control parameter” as used throughout this detailed description and in the claims refers to a parameter used by one or more vehicle systems. In some cases, a control parameter can be an operating parameter that is used to determine if a particular function should be activated for a given vehicle system. For example, in situations where an electronic stability control system is used, the control parameter can be a threshold error in the steering yaw rate that is used to determine if stability control should be activated. As another example, in situations where automatic cruise control is used, the control parameter can be a parameter used to determine if cruise control should be automatically turned off. Further examples of control parameters are discussed in detail below and include, but are not limited to: stability control activation thresholds, brake assist activation thresholds, blind spot monitoring zone thresholds, time to collision thresholds, road crossing thresholds, lane keep assist system status, low speed follow status, electronic power steering status, automatic cruise control status as well as other control parameters. 
       FIGS. 28 and 29  illustrate schematic views of a general method for determining a control parameter using the driver state index of the driver as well as vehicle operating information. In particular,  FIG. 28  illustrates a schematic view of how the driver state index can be used to retrieve a control coefficient. A control coefficient can be any value used in determining a control parameter. In some cases, the control coefficient varies as a function of driver state index and is used as an input for calculating the control parameter. Examples of control coefficients include, but are not limited to electronic stability control system coefficients, brake assist coefficients, blind spot zone warning coefficients, warning intensity coefficients, forward collision warning coefficients, lane departure warning coefficients and lane keep assist coefficients. Some systems cannot use a control coefficient to determine the control parameter. For example, in some cases, the control parameter can be determined directly from the driver state index. 
     In one embodiment, the value of the control coefficient  2802  increases from 0% to 25% as the driver state index increases from 1 to 4. In some cases, the control coefficient can serve as a multiplicative factor for increasing or decreasing the value of a control parameter. For example, in some cases when the driver state index is 4, the control coefficient can be used to increase the value of a control parameter by 25%. In other embodiments, the control coefficient could vary in any other manner. In some cases, the control coefficient could vary linearly as a function of driver state index. In other cases, the control coefficient could vary in a nonlinear manner as a function of driver state index. In still other cases, the control coefficient could vary between two or more discrete values as a function of driver state index. 
       FIG. 29  illustrates a calculation unit  2902  for determining a control parameter. The calculation unit  2902  receives a control coefficient  2904  and vehicle operating information  2906  as inputs. The calculation unit  2902  outputs the control parameter  2908 . The vehicle operating information  2906  can include any information necessary to calculate a control parameter. For example, in situations where the vehicle system is an electronic stability control system, the system can receive wheel speed information, steering angle information, roadway friction information, as well as other information necessary to calculate a control parameter that is used to determine when stability control should be activated. Moreover, as discussed above, the control coefficient  2904  can be determined from the driver state index using, for example, a look-up table. The calculation unit  2902  then considers both the vehicle operating information  2906  and the control coefficient  2904  in calculating the control parameter  2908 . 
     It will be understood that the calculation unit  2902  is intended to be any general algorithm or process used to determine one or more control parameters. In some cases, the calculation unit  2902  can be associated with the response system  188  and/or the ECU  106 . In other cases, however, the calculation unit  2902  could be associated with any other system or device of the motor vehicle  100 , including any of the vehicle systems discussed previously. 
     In some embodiments, a control parameter can be associated with a status or state of a given vehicle system.  FIG. 30  illustrates an embodiment of a general relationship between the driver state index of the driver and a system status  3002 . The system shown here is general and could be associated with any vehicle system. For low driver state index (1 or 2), the system status  3002  is ON. However, if the driver state index increases to 3 or 4 the system status  3002  is turned OFF. In still other embodiments, a control parameter could be set to multiple different “states” according to the driver state index. Using this arrangement, the state of a vehicle system can be modified according the driver state index of a driver. 
     Generally, the driver state index can be determined using any of the methods discussed throughout this detailed description for detecting driver state as it relates to distraction and/or drowsiness. In particular, the level of drowsiness and/or level of distraction can be detected by sensing different degrees of driver state. For example, as discussed below, drowsiness and/or distraction in a driver can be detected by sensing eyelid movement and/or head movement. In some cases, the degree of eyelid movement (the degree to which the eyes are open or closed) or the degree of head movement (how tilted the head is) could be used to determine the driver state index. In other cases, the monitoring systems  300  could be used to determine the driver state index. In still other cases, the vehicle systems could be used to determine the driver state index. For example, the degree of unusual steering behavior or the degree of lane departures, alone or in combination, can indicate a certain driver state index. 
     A. Types of Driver States 
     As discussed above, a motor vehicle can include provisions for assessing the state of a driver and automatically adjusting the operation of one or more vehicle systems in response to one or more driver states. In Section I, a “driver state” is defined in detail and can refer to a measurement of a state of the biological being and/or a state of the environment of the biological being (e.g., a vehicle). The following description discusses specific driver states based on specific types of monitoring systems and/or monitoring information, namely, a physiological driver state, a behavioral driver state and a vehicular-sensed driver state. 
     1. Physiological Driver State 
     A physiological driver state is based on physiological information from physiological monitoring systems and sensors, as discussed above in section III (B) (2). Physiological information includes information about the human body (e.g., a driver) derived intrinsically. Said differently, physiological information is measured by medical means and quantifies an internal characteristic of a human body. Physiological information is typically not externally observable to the human eye. However, in some cases, physiological information is observable by optical means, for example, heart rate measured by an optical device. Physiological information can include, but is not limited to, heart rate, blood pressure, oxygen content, blood alcohol content, respiratory rate, perspiration rate, skin conductance, brain wave activity, digestion information, salivation information, among others. Physiological information can also include information about the autonomic nervous systems of the human body derived intrinsically. 
     The following examples describe a variety of different methods for determining a physiological driver state, for example a physiological driver state based on respiratory rate information and autonomic information. It is understood that the methods for determining a physiological driver state can also include physiological driver states based on other types of physiological information. 
       FIG. 31  illustrates a schematic view of an embodiment of the motor vehicle  100 , in which the response system  188  is capable of detecting respiratory rate information (e.g., physiological information). In particular, using a bio-monitoring sensor  180 , the ECU  106  can determine the number of breaths per minute taken by driver  102 . In one embodiment, the response system  188  can receive respiratory rate information from respiratory monitoring system  312 . The respiratory rate information can be analyzed to determine if the measured breaths per minute coincides with a normal state or a distracted (e.g., drowsy) state. Breaths per minute is given as an example. 
     Although  FIG. 31  schematically describes detecting respiratory rate information to determine a physiological driver state, it is understood that other types of physiological information can be monitored and used to determine one or more physiological driver states. For example, the response system  188  can detect and/or receive heart rate information from a heart rate monitoring system  302 . As discussed above, the heart rate monitoring system  302  can include heart rate sensors  304 , blood pressure sensors  306 , oxygen content sensors  308  and blood alcohol content sensors  310 , as well as any other kinds of sensors for detecting heart information and/or cardiovascular information. These sensors could be disposed in a dashboard, steering wheel (e.g., touch steering wheel system  134 ), seat, seat belt, armrest or other component to detect the heart information of a driver. 
     The heart information and/or cardiovascular information can be analyzed to determine a physiological driver state. For example, the heart information can be analyzed to determine if a heart rate (e.g., beats per minute) coincides with a particular physiological driver state. For example, a high heart rate can coincide with a stressed driver state. A low heart rate can coincide with a drowsy driver state. In one example, a physiological driver state and changes in a physiological driver state can be based on parasympathetic and sympathetic activity levels by analyzing heart rate information as discussed in in U.S. Pat. No. 9,420,958, entitled System and Method for Determining Changes in a Body State, which is incorporated by reference in its entirety herein. 
     In another embodiment, the ECU  106  can determine the blood pressure of the driver from information received by the blood pressure sensors  306 . The blood pressure can be analyzed to determine if the blood pressure coincides with a particular physiological driver state. For example, a high blood pressure level can coincide with a stressed driver state. In a further embodiment, the ECU  106  can determine the blood oxygen content of the driver based on information received by the oxygen content sensors  308 . The blood oxygen content can be analyzed to determine if the blood oxygen content coincides with a particular physiological driver state. For example, low blood oxygen levels can coincide with a drowsy driver state. 
     In another embodiment, the ECU  106  can determine blood alcohol content (BAC) (e.g., blood alcohol levels) of the driver from information received by the blood alcohol content sensors  310 . For example, an optical sensor can emit light towards the driver&#39;s skin and measure a tissue alcohol concentration based on the amount of light that is reflected back by the skin. The BAC can be analyzed to determine if the BAC coincides with a particular physiological driver state. For example, high BAC can coincide with an impaired/distracted driver state (e.g., an intoxicated driver). 
     In some embodiments, the response system  188  can detect and/or receive perspiration information from a perspiration monitoring system  314 . The perspiration monitoring system  314  can include any devices or systems for sensing perspiration or sweat from a driver. Accordingly, the ECU  106  can determine a level of perspiration from the driver to determine if the perspiration coincides with a particular physiological driver state. For example, if the driver&#39;s perspiration rate is high, this can coincide with a stressed driver state. 
     In some embodiments, the response system  188  can detect and/or receive pupil dilation information from a pupil dilation monitoring system  316  for sensing the amount of pupil dilation, or pupil size, in a driver. Accordingly, the ECU  106  can analyze the pupil size to determine particular physiological driver state. For example, enlarged (e.g., dilated pupils) can coincide with a drowsy or stressed driver state. 
     Additionally, in some embodiments, the response system  188  can detect and/or receive brain information from a brain monitoring system  318 . In some cases, the brain monitoring system  318  could include electroencephalogram (EEG) sensors  320 , functional near infrared spectroscopy (fNIRS) sensors  322 , functional magnetic resonance imaging (fMRI) sensors  324  as well as other kinds of sensors capable of detecting brain information. Such sensors could be located in any portion of the motor vehicle  100 . In some cases, sensors associated with the brain monitoring system  318  could be disposed in a headrest. In other cases, sensors could be disposed in the roof of the motor vehicle  100 . In still other cases, sensors could be disposed in any other locations. Accordingly, the ECU  106  can analyze the brain information to determine a particular physiological driver state. For example, abnormal brain waves can coincide with a health state, for example, a seizure. 
     In some embodiments, the response system  188  can detect and/or receive digestion information from a digestion monitoring system  326 . In other embodiments, the response system  188  can detect and/or receive salivation information from a salivation monitoring system  328 . In some cases, monitoring digestion and/or salivation could also help in determining a physiological driver state. For example, the ECU  106  can analyze the digestion information to determine that the body is digesting food and blood is being directed toward the stomach that can lead to a drowsy driver state. In another example, if the ECU  106  determines the body is poorly digesting food, the ECU  106  can determine the driver is in an inattentive or drowsy driver state. 
     Referring now to  FIG. 32 , an embodiment of a process for detecting distraction (e.g., drowsiness) by monitoring the physiological information (e.g., autonomic information) of a driver is shown. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as the vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  3202 , the response system  188  can receive physiological information related to the autonomic nervous system of the driver. In some cases, the information can be received from a sensor. The sensor could be associated with any portion of the motor vehicle  100  including a seat, armrest, or any other portion. Moreover, the sensor could be a portable sensor in some cases. Furthermore, the physiological information could be received from any physiological monitoring systems and/or sensors described in Section III (B) (1). 
     In step  3204 , the response system  188  can analyze the autonomic information. Generally, any method of analyzing autonomic information to determine if a driver is drowsy could be used. It will be understood that the method of analyzing the autonomic information can vary according to the type of autonomic information being analyzed. In step  3206 , the response system  188  can determine the driver state index (e.g., a physiological driver state index) of the driver based on the analysis conducted during step  3204 . In some embodiments discussed herein, one or more vehicle systems can be modified based on the driver state index determined at step  3206 . 
     2. Behavioral Driver State 
     A behavioral driver state is based on behavioral information from behavioral monitoring systems and sensors, as discussed above in section III (B) (3). Behavioral information includes information about the human body derived extrinsically. Behavioral information is typically observable externally to the human eye. For example, behavioral information can include eye movements, mouth movements, facial movements, facial recognition, head movements, body movements, hand postures, hand placement, body posture, gesture recognition, among others. The following examples describe a variety of different methods for determining a behavioral driver state, for example a behavioral driver state based on eye movement, head movement and head position. It is understood that the methods for operating vehicle systems in response to a behavioral driver state can also include behavioral driver states based on other types of behavioral information. 
     As discussed above, a response system can include provisions for detecting the state of a driver, for example a behavioral state of a driver. In one example, the response system can detect the state of a driver by monitoring the eyes of a driver.  FIG. 33  illustrates a schematic view of a scenario in which the response system  188  is capable of monitoring the state or behavior of a driver. Referring to  FIG. 33 , the ECU  106  can receive information from an optical sensing device  162 . In some cases, the optical sensing device  162  can be a video camera that is mounted in the dashboard of the motor vehicle  100 . The information can comprise a sequence of images  3300  that can be analyzed to determine the state of driver  102 . A first image  3302  shows a driver  102  in a fully awake (e.g., attentive) state, with eyes  3304  wide open. However, a second image  3306  shows the driver  102  in a drowsy (e.g., distracted) state, with eyes  3304  half open. Finally, a third image  3308  shows the driver  102  in a very drowsy (distracted) state with eyes  3304  fully closed. In some embodiments, the response system  188  can be configured to analyze various images of the driver  102 . More specifically, the response system  188  can analyze the movement of eyes  3304  to determine if a driver is in a normal state or a drowsy (e.g., distracted) state. 
     It will be understood that any type of algorithm known in the art for analyzing eye movement from images can be used. In particular, any type of algorithm that can recognize the eyes and determine the position of the eyelids between a closed and open position can be used. Examples of such algorithms can include various pattern recognition algorithms known in the art. 
     In other embodiments, a thermal sensing device  166  can be used to sense eyelid movement. For example, as the eyelids move between opened and closed positions, the amount of thermal radiation received at a thermal sensing device  166  can vary. In other words, the thermal sensing device  166  can be configured to distinguish between various eyelid positions based on variations in the detected temperature of the eyes. 
       FIG. 34  illustrates an embodiment of a process for detecting drowsiness by monitoring eye movement in the driver. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  3402 , the response system  188  can receive optical/thermal information. In some cases, optical information could be received from a camera or from an optical sensing device  162 . In other cases, thermal information could be received from a thermal sensing device  166 . In still other cases, both optical and thermal information could be received from a combination of optical and thermal devices. 
     In step  3404 , the response system  188  can analyze eyelid movement. By detecting eyelid movement, the response system  188  can determine if the eyes of a driver are open, closed or in a partially closed position. The eyelid movement can be determined using either optical information or thermal information received during step  3402 . Moreover, as discussed above, any type of software or algorithm can be used to determine eyelid movement from the optical or thermal information. Although the current embodiment comprises a step of analyzing eyelid movement, in other embodiments the movement of the eyeballs could also be analyzed. 
     In step  3406 , the response system  188  determines the driver state index (e.g., the behavioral driver state index) of the driver according to the eyelid movement. The driver state index can have any value. In some cases, the value ranges between 1 and 4, with 1 being the least drowsy and 4 being the drowsiest state. In some cases, the value ranges between 1 and 4, with 1 being the least distracted and 4 being the most distracted state. In some cases, to determine the driver state index the response system  188  determines if the eyes are closed or partially closed for extended periods. In order to distinguish drooping eyelids due to drowsiness (e.g., distraction) from blinking, the response system  188  can use a threshold time that the eyelids are closed or partially closed. If the eyes of the driver are closed or partially closed for periods longer than the threshold time, the response system  188  can determine that this is due to drowsiness (e.g., distraction). In such cases, the driver can be assigned a driver state index that is greater than 1 to indicate that the driver is drowsy (e.g., distracted). Moreover, the response system  188  can assign different driver state index values for different degrees of eyelid movement or eyelid closure. 
     In some embodiments, the response system  188  can determine the driver state index based on detecting a single instance of prolonged eyelid closure or partial eyelid closure. Of course, it can also be the case that the response system  188  analyzes eye movement over an interval of time and looks at average eye movements. 
     In a further example, a response system can include provisions for detecting the state of a driver (e.g., the behavioral state of a driver) by monitoring the head of a driver.  FIG. 35  illustrates a schematic view of a scenario in which the response system  188  is capable of monitoring the state or behavior of a driver. Referring to  FIG. 35 , the ECU  106  can receive information from an optical sensing device  162  (e.g., as part of a head movement monitoring system  334 ). In some cases, the optical sensing device  162  can be a video camera that is mounted in the dashboard of the motor vehicle  100 . In other cases, a thermal sensing device could be used. The information can comprise a sequence of images  3500  that can be analyzed to determine the state of the driver  102 . A first image  3502  shows the driver  102  in a fully awake state, with head  3504  in an upright position. However, a second image  3506  shows the driver  102  in a drowsy state, with head  3504  leaning forward. Finally, a third image  3508  shows the driver  102  in a drowsier state with head  3504  fully tilted forward. In some embodiments, the response system  188  can be configured to analyze various images of the driver  102 . More specifically, the response system  188  can analyze the movement of head  3504  to determine if a driver is in a normal state or a drowsy (e.g., distracted) state. 
     It will be understood that any type of algorithm known in the art for analyzing head movement from images can be used. In particular, any type of algorithm that can recognize the head and determine the position of the head can be used. Examples of such algorithms can include various pattern recognition algorithms known in the art. 
     It is appreciated that the response system  188  can recognize other head movements and the direction of said movements other than those described above. For example, as discussed above, the ECU  106  can include provisions for receiving information about a head pose (i.e., position and orientation) of the driver&#39;s head. The head pose can be used to determine what direction (e.g., forward-looking, non-forward-looking) the head of the driver is directed to with respect to the vehicle. In one embodiment, the head movement monitoring system  334  provides head vectoring information including the magnitude (e.g., a length of time) and direction of the head look. In one embodiment, if the head pose is forward-looking, the driver is determined to be paying attention to the forward field-of-view relative to the vehicle. If the head pose is non-forward-looking, the driver may not be paying attention. Furthermore, the head pose can be analyzed to determine a rotation of the head of the driver (e.g., head of driver is turned) and a rotation direction with respect to the driver and the vehicle (i.e., to the left, right, back, forward). For example,  FIG. 16B , discussed above, illustrates exemplary head looking directions of the driver with respect to the driver and the vehicle. Further, the detection of a rotation and a rotation direction can be used to recognize an eye gaze direction of the driver  102  as is known in the art. 
     It is also appreciated that the response system  188  can recognize eye/facial movements and analyze said movements from images, similar to  FIG. 35 . In particular, the eye/facial movement monitoring system  332  could include provisions for monitoring eye/facial movements. Eye movement can include, for example, pupil dilation, degree of eye or eyelid closure, eyebrow movement, gaze tracking, blinking, squinting, among others. Eye movement can also include eye vectoring including the magnitude and direction of eye movement/eye gaze. Facial movements can include various shape and motion features of the face (e.g., nose, mouth, lips, cheeks, chin). For example, facial movements and parameters that can be sensed, monitored and/or detected include, but are not limited to, yawning, mouth movement, mouth shape, mouth open, the degree of opening of the mouth, the duration of opening of the mouth, mouth closed, the degree of closing of the mouth, the duration of closing of the mouth, lip movement, lip shape, the degree of roundness of the lips, the degree to which a tongue is seen, cheek movement, cheek shape, chin movement, chin shape, etc. 
       FIG. 36  illustrates an embodiment of a process for detecting drowsiness by monitoring head movement in the driver. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  3602 , the response system  188  can receive optical and/or thermal information. In some cases, optical information could be received from a camera or an optical sensing device  162 . In other cases, thermal information could be received from a thermal sensing device  166 . In still other cases, both optical and thermal information could be received from a combination of optical and thermal devices. In some embodiments, at step  3602 , the response system  188  can receive head movement information from a head movement monitoring system  334 . 
     In step  3604 , the response system  188  can analyze head movement. By detecting head movement, the response system  188  can determine if a driver is leaning forward. In other embodiments, the response system  188  can analyze the head movement to determine a head pose of the driver&#39;s head with respect to the driver and the vehicle as discussed above with  FIGS. 16A, 16B, and 17 . For example, the response system  188  can determine a head look direction based on the head pose with respect to the driver and the vehicle frame. As another example, the response system  188  can determine a rotation (e.g., head of driver is turned) direction with respect to the driver and the vehicle (i.e., to the left, right, back, forward). Further, the response system  188  can determine head vectoring information including a magnitude (e.g., length of time) of the head look and/or head rotation. 
     The head movement can be determined using either optical information, thermal information, and/or head movement information from the head movement monitoring system  334  received during step  3602 . Moreover, as discussed above, any type of software or algorithm can be used to determine head movement from the optical, thermal or head movement information. 
     In step  3606 , the response system  188  determines the driver state index of the driver in response to the detected head movement. For example, in some cases, to determine the driver state index of the driver, the response system  188  determines if the head is tilted in any direction for extended periods. In some cases, the response system  188  can determine if the head is tilting forward. In some cases, the response system  188  can assign a driver state index depending on the level of tilt and/or the time interval over which the head remains tilted. For example, if the head is tilted forward for brief periods, the driver state index can be assigned a value of 2, to indicate that the driver is slightly drowsy (e.g., distracted). If the head is tilted forward for a significant period of time, the driver state index can be assigned a value of 4 to indicate that the driver is extremely drowsy (e.g., distracted). 
     In some embodiments, the response system  188  can determine the driver state index based on detecting a single instance of a driver tilting his or her head forward. Of course, it can also be the case that the response system  188  analyzes head movement over an interval of time and looks at average head movements. For example, head nods or head tilts over a period of time. 
     In a further example, the response system  188  can determine the driver state index based on detecting a head pose, head look direction and/or head rotation. The response system  188  can also determine the driver state index based on a length of time of the head pose and/or head look direction. For example, if the head look is rear-looking for more than two seconds, the driver state index can be assigned a value of 2, to indicate the driver is slightly drowsy (e.g., distracted). As another example, if the head look is forward-looking, the driver state index can be assigned a value of 1, to indicate the driver is not drowsy (e.g., not distracted). 
     In a further example, the response system  188  can include provisions for detecting the state of a driver by monitoring the relative position of the driver&#39;s head with respect to a headrest.  FIG. 37  illustrates a schematic view of a scenario in which the response system  188  is capable of monitoring the state of a driver. Referring to  FIG. 37 , the ECU  106  can receive information from a proximity sensor  184 . In some cases, the proximity sensor  184  can be a capacitor. In other cases, the proximity sensor  184  can be a laser based sensor. In still other cases, any other kind of proximity sensor known in the art could be used. The response system  188  can monitor the distance between the driver&#39;s head and a headrest  174 . In particular, the response system  188  can receive information from a proximity sensor  184  that can be used to determine the distance between the driver&#39;s head and a headrest  174 . For example, a first configuration  3702  shows a driver  102  in a fully awake state, with a head  186  disposed against headrest  174 . However, a second configuration  3704  shows the driver  102  in a somewhat drowsy state. In this case, the head  186  has moved further away from the headrest  174  as the driver  102  slumps forward slightly. A third configuration  3706  shows driver  102  in a fully drowsy state. In this case, the head  186  is moved still further away from the headrest  174  as the driver is further slumped over. In some embodiments, the response system  188  can be configured to analyze information related to the distance between the driver&#39;s head  186  and the headrest  174 . Moreover, the response system  188  can analyze head position and/or movement (including tilting, slumping, bobbing, rotation, head look) to determine if the driver  102  is in a normal state or a drowsy (e.g., distracted) state. 
     It will be understood that any type of algorithm known in the art for analyzing head distance and/or movement from proximity or distance information can be used. In particular, any type of algorithm that can determine the relative distance between a headrest and the driver&#39;s head can be used. In addition, any algorithms for analyzing changes in distance to determine head motion could also be used. Examples of such algorithms can include various pattern recognition algorithms known in the art. 
       FIG. 38  illustrates an embodiment of a process for detecting drowsiness by monitoring the distance of the driver&#39;s head from a headrest. In some embodiments, some of the following steps could be accomplished by the response system  188  of a motor vehicle  100 . In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  3802 , the response system  188  can receive proximity information. In some cases, proximity information could be received from a capacitor or laser based sensor. In other cases, proximity information could be received from any other sensor. In step  3804 , the response system  188  can analyze the distance of the head from a headrest. By determining the distance between the driver&#39;s head and the headrest, the response system  188  can determine if a driver is leaning forward. Moreover, by analyzing head distance over time, the response system  188  can also detect motion of the head. The distance of the head from the headrest can be determined using any type of proximity information received during step  3802 . Moreover, as discussed above, any type of software or algorithm can be used to determine the distance of the head and/or head motion information. 
     In step  3806 , the response system  188  determines the driver state index of the driver in response to the detected head distance and/or head motion. For example, in some cases, to determine the driver state index of the driver, the response system  188  determines if the head is leaning away from the headrest for extended periods. In some cases, the response system  188  can determine if the head is tilting forward. In some cases, the response system  188  can assign a driver state index depending on the distance of the head from the headrest as well as from the time interval over which the head is located away from the headrest. For example, if the head is located away from the headrest for brief periods, the driver state index can be assigned a value of 2, to indicate that the driver is slightly drowsy (e.g., slightly distracted). If the head is located away from the headrest for a significant period of time, the driver state index can be assigned a value of 4 to indicate that the driver is extremely drowsy (e.g., extremely distracted). It will be understood that in some cases, a system could be configured so that the alert state of the driver is associated with a predetermined distance between the head and the headrest. This predetermined distance could be a factory set value or a value determined by monitoring a driver over time. Then, the driver state index can be increased when the driver&#39;s head moves closer to the headrest or further from the headrest with respect to the predetermined distance. In other words, in some cases the system can recognize that the driver&#39;s head can tilt forward and/or backward as he or she gets drowsy. 
     In some embodiments, the response system  188  can determine the driver state index based on detecting a single distance measurement between the driver&#39;s head and a headrest. Of course, it can also be the case that the response system  188  analyzes the distance between the driver&#39;s head and the headrest over an interval of time and uses average distances to determine driver state index. 
     In some other embodiments, the response system  188  could detect the distance between the driver&#39;s head and any other reference location within the vehicle. For example, in some cases, a proximity sensor could be located in a ceiling of the vehicle and the response system  188  can detect the distance of the driver&#39;s head with respect to the location of the proximity sensor. In other cases, a proximity sensor could be located in any other part of the vehicle. Moreover, in other embodiments, any other portions of a driver could be monitored for determining if a driver is drowsy or otherwise alert and/or distracted. For example, in still another embodiment, a proximity sensor could be used in the backrest of a seat to measure the distance between the backrest and the back of the driver. 
     In another embodiment, the response system  188  could detect a position and contact of the driver&#39;s hands on a steering wheel of the motor vehicle  100 . For example, in one embodiment, the steering wheel includes a touch steering wheel system  134 . Specifically, the steering wheel can include sensors (e.g., capacitive sensors, electrodes) mounted in or on the steering wheel. The sensors are configured to measure contact of the hands of the driver with the steering wheel and a location of the contact (e.g., behavioral information). In some embodiments, the sensors can function as a switch wherein the contact of the hands of the driver and the location of the contact are associated with actuating a device and/or a vehicle function of the vehicle. Accordingly, the response system  188  can detect and/or receive information about the position and/or contact of the driver&#39;s hands on a steering wheel from the touch steering wheel system  134 . This information can be used to determine a behavioral driver state (e.g., a driver state index). As discussed above,  FIG. 18  illustrates an exemplary touch steering wheel  1802  with both hands  1804  and  1806  of a driver in contact and grasping the steering wheel. 
       FIG. 39  illustrates an embodiment of a process for detecting drowsiness by monitoring hand contact and position information with respect to a steering wheel. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  3902 , the response system  188  can receive hand contact and position information with respect to a steering wheel. In some cases, the hand contact and position information can be received from the touch steering wheel system  134  or directly from some kind of sensor (e.g., an optical sensor). It is understood that in some embodiments, any type of driver contact information with the steering wheel can be received. For example, driver appendage (e.g., elbow, shoulder, arm, knee) contact and position information. Next, in step  3904 , the response system  188  can analyze hand contact and position information. Any method of analyzing hand contact and position information can be used. 
     In step  3906 , the response system  188  can determine the driver state index (e.g., a behavioral driver state index) of the driver based on hand contact and position information with respect to the steering wheel. For example, if the driver has both hands on the steering wheel (e.g., See  FIG. 18 ), the response system  188  can assign a driver state index of 1 to indicate that the driver is not distracted (e.g., not drowsy). If the driver has one hand on the steering wheel, the response system  188  can assign a driver state index of 2 to indicate that the driver is slightly distracted (e.g., slightly drowsy). If the driver has no hands on the steering wheel, the response system  188  can assign a driver state index of greater than 2 to indicate that the driver is distracted (e.g., drowsy). 
     In some embodiments, the position of the hands can also be used to determine the driver state index at step  3906 . For example, if the driver has both hands on the wheel, but the hands are both located at a 6 o&#39;clock steering position, the response system  188  can assign a driver state index of 2 to indicate that the driver is slightly distracted (e.g., slightly drowsy). If the driver has both hands on the wheel, located at a 9 o&#39;clock and 3 o&#39;clock steering position, the response system  188  can assign a driver state index of 1 to indicate that the driver is not distracted (e.g., not drowsy). Further embodiments for determining a driver state and controlling a vehicle display using hand contact and position information and/or head movement information is described in U.S. application Ser. No. 14/744,247 filed on Jun. 19, 2015, which is incorporated herein by reference. 
     3. Vehicular-Sensed Driver State 
     A vehicular-sensed driver state is based on vehicle information from vehicular monitoring systems and sensors, as discussed above in Section II (B) (1). Specifically, vehicle information for determining a vehicular-sensed driver state includes information related to the motor vehicle  100  of  FIG. 1A  and/or the vehicle systems  126 , including those vehicle systems listed in  FIG. 2 , that relate to a driver of the motor vehicle  100 . In particular, a driver transmits information when operating the motor vehicle  100  and the vehicle systems  126 , and based on this operation, other types of information about the driver can be provided by the motor vehicle  100  and/or the vehicle systems  126 . For example, when the driver operates the motor vehicle and/or the vehicle systems  126 , changes in vehicle acceleration, velocity, lane position, and direction all provide information that directly correlates to the driver and a state of the driver. 
     As an illustrative example, vehicle information for determining a vehicular-sensed driver state can include steering information that correlates to the driver from the electronic power steering system  132 , electronic stability control system  202 , the lane departure warning system  222 , and the lane keep assist system  226 , among others. Vehicle information for determining a vehicular-sensed driver state can include braking information that correlates to the driver from the electronic stability control system  202 , the antilock brake system  204 , the brake assist system  206 , among others. Vehicle information for determining a vehicular-sensed driver state can include acceleration information that correlates to the driver from the electronic stability control system  202 , among others. Vehicle information for determining a vehicular-sensed driver state can include navigation information that correlates to the driver from the navigation system  230 , among others. It is understood that other types of vehicle information that directly correlates to the driver can be obtained from other vehicle systems to determine a vehicular-sensed driver state. 
     The following examples describe a variety of different methods for determining a vehicular-sensed driver state, for example a vehicular-sensed driver state based on steering and lane departure information. It is understood that the methods for operating vehicle systems in response to a vehicular-sensed driver state can also include vehicular-sensed driver states based on other types of vehicle information. 
     In one example, a response system can include provisions for detecting abnormal steering by a driver for purposes of determining if a driver is distracted and/or drowsy.  FIG. 40  illustrates a schematic view of the motor vehicle  100  being operated by a driver  102 . In this situation, ECU  106  can receive information related to the steering angle or steering position as a function of time. In addition, ECU  106  could also receive information about the torque applied to a steering wheel as a function of time. In some cases, the steering angle information or torque information can be received from an EPS system  132 , which can include a steering angle sensor as well as a torque sensor. By analyzing the steering position or steering torque over time, the response system  188  can determine if the steering is inconsistent, which can indicate that the driver is drowsy. 
       FIG. 41  illustrates an embodiment of a process for detecting drowsiness by monitoring the steering behavior of a driver. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  4102 , the response system  188  can receive steering angle information. In some cases, the steering angle information can be received from EPS  132  or directly from a steering angle sensor. Next, in step  4104 , the response system  188  can analyze the steering angle information. In particular, the response system  188  can look for patterns in the steering angle as a function of time that suggest inconsistent steering, which could indicate a drowsy driver. Any method of analyzing steering information to determine if the steering is inconsistent can be used. Moreover, in some embodiments, the response system  188  can receive information from lane keep assist system  226  to determine if a driver is steering the motor vehicle  100  outside of a current lane. 
     In step  4106 , the response system  188  can determine the driver state index (e.g., a vehicular-sensed driver state index) of the driver based on steering wheel movement. For example, if the steering wheel movement is inconsistent, the response system  188  can assign a driver state index of 2 or greater to indicate that the driver is distracted and/or drowsy. 
     A response system can also include provisions for detecting abnormal driving behavior by monitoring lane departure information.  FIG. 42  illustrates a schematic view of an embodiment of the motor vehicle  100  being operated by a driver  102 . In this situation, ECU  106  can receive lane departure information. In some cases, the lane departure information can be received from the LDW system  222 . Lane departure information could include any kind of information related to the position of a vehicle relative to one or more lanes, steering behavior, trajectory or any other kind of information. In some cases, the lane departure information could be processed information analyzed by the LDW system  222  that indicates some kind of lane departure behavior. By analyzing the lane departure information, the response system  188  can determine if the driving behavior is inconsistent, which can indicate that the driver is distracted and/or drowsy. In some embodiments, whenever the LDW system  222  issues a lane departure warning (e.g., warning  4204 ), the response system  188  can determine that the driver is drowsy. Moreover, the level of drowsiness could be determined by the intensity of the warning. 
       FIG. 43  illustrates an embodiment of a process for detecting drowsiness by monitoring lane departure information. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  4302 , the response system  188  can receive lane departure information. In some cases, the lane departure information can be received from the LDW system  222  or directly from some kind of sensor (such as a steering angle sensor, or a relative position sensor). Next, in step  4304 , the response system  188  can analyze the lane departure information. Any method of analyzing lane departure information can be used. 
     In step  4306 , the response system  188  can determine the driver state index (e.g., a vehicular-sensed driver state index) of the driver based on lane departure information. For example, if the vehicle is drifting out of the current lane, the response system  188  can assign a driver state index of 2 or greater to indicate that the driver is distracted and/or drowsy. Likewise, if the lane departure information is a lane departure warning from the LDW system  222 , the response system  188  can assign a driver state index of 2 or greater to indicate that the driver is distracted and/or drowsy. Using this process, the response system  188  can use information from one or more vehicle systems  126  to help determine if a driver is drowsy. This is possible since drowsiness (or other types of inattentiveness) not only manifest as driver states, but can also cause changes in the operation of the vehicle, which can be monitored by the various vehicle systems  126 . 
     It will be understood that the methods discussed above for determining the driver state (e.g., the driver state index) of a driver according to eye movement, head movement, steering wheel movement and/or sensing autonomic information are only intended to be exemplary and in other embodiments any other method of detecting the state of a driver, including states associated with drowsiness, could be used. For example, driver state can be determined by monitoring heart rate information and/or information transfer rates as discussed herein. 
     Additionally, it will be understood that the method discussed above for determining driver states can also be used for determining a plurality of driver states and/or a combined driver state. Specifically, it will be understood that in some embodiments multiple methods for detecting driver states to determine a driver state could be used simultaneously, as will now be discussed in detail. 
     B. Determine Combined Driver State 
     As discussed above,  FIG. 24A  illustrates an embodiment of a process for controlling one or more vehicle systems in a motor vehicle based on the state of the driver. However, in one embodiment, controlling one or more vehicle systems in a motor vehicle can depend on one or more driver states (e.g., a plurality of driver states), specifically, a combined driver state based on one or more driver states. The “combined driver state,” as used herein, refers to a combined measure of the state of the driver, for example the vigilance, the attention and/or the drowsiness of a driver. In some cases, the combined driver state could be given as a numerical value, for example a combined driver state level, a combined driver state index, among others. In other cases, the combined driver state could be given as a non-numerical value, for example, drowsy, non-drowsy, slightly drowsy, a Boolean value, among others. Moreover, the combined driver state can range from values associated with complete alertness (e.g., attentive) to values associated with extreme drowsiness (e.g., distraction) or even a state in which the driver is asleep (e.g., distraction). For example, in one embodiment, the combined driver state index could take on the values 1, 2, 3 and 4, where 1 is the least drowsy and 4 is the most drowsy. In another embodiment, the combined driver state index could take on values from 1-10. In other cases, the combined driver state can range from values associated with complete focus on the driving task (10 for example) to values associated complete distraction (1 for example) and values there between. 
     The one or more driver states can be one of a physiological driver state, a behavioral driver state and a vehicular-sensed driver state. Thus, the combined driver state can be based on different types of driver states derived from different types of monitoring information (e.g., physiological information, behavioral information, vehicle information) and/or from information from different types of monitoring systems (e.g., physiological monitoring systems and sensors, behavioral monitoring systems and sensors, vehicular monitoring systems and sensors). The combined driver state can also be based on the same types of driver states or various combinations of driver states that can be derived from the same or different types of monitoring information and/or monitoring systems. 
     Further, the one or more driver states can be determined, combined and/or and confirmed with one another. Determining, combining and/or confirming one or more driver states provides a reliable and robust driver monitoring system. This driver monitoring system verifies driver states (e.g., to eliminate false positives), provides a combined driver state based on more than one driver state using different types of monitoring information (e.g., multi-modal inputs), and modifies one or more vehicle systems based on the combined driver state. In this way, behaviors and risks can be assessed in multiple modes and modification of vehicle systems can be controlled accurately. 
     1. Determine Combined Driver State Based on a Plurality Driver States 
     Referring now to  FIG. 44 , a method is illustrated of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle, similar to  FIG. 24A , except the process of  FIG. 44  depends on a combined driver state based on a plurality of driver states. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  4402 , the response system  188  can receive monitoring information. In one embodiment, the monitoring information is at least one of physiological information, behavioral information and vehicle information. The monitoring information can be received from one or more sensors, one or more monitoring systems, one or more vehicle systems, any other device of the motor vehicle  100 , and/or any combination of sensors, monitoring systems, vehicles systems or other devices. 
     In step  4404 , the response system  188  can determine a plurality of driver states. The plurality of driver states being at least one of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. A physiological driver state, a behavioral driver state, or a vehicular-sensed driver state can be referred to herein as drive state types or types of driver states. The physiological driver state is based on physiological information, the behavioral driver state is based on behavioral information, and the vehicular-sensed driver state is based on vehicle information. As will be discussed herein, in some embodiments, each of the plurality of driver states are a different one of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. In other embodiments, at least two of the plurality of driver states are based on the same type of driver state. 
     In some embodiments, step  4404  includes determining a first driver state and a second driver state based on the monitoring information from the one or more monitoring systems. In another embodiment, step  4404  includes determining a third driver state based on the monitoring information from the one or more monitoring systems. It is appreciated that other combinations of information and driver states can be implemented. For example, behavioral information could be used to determine a first driver state and physiological information could be used to determine a second driver state, and so on. In another example, first and second driver states could be based on behavioral information from two different systems or sensors. 
     It is appreciated that any number of driver states can be determined. In one embodiment, the first driver state is one of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state, and the second driver state is another of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. The third driver state can be a further one of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. By using different types of monitoring information to determine different driver states, multi-modal driver state confirmation is possible, as will be described herein. The driver state can be determined by the ECU  106 , the response system  188 , the vehicle systems  126  and/or the monitoring systems  300  described herein. 
     It should be noted that in any of the embodiments described herein, the first, second and third driver states could each be derived from the same type of monitoring systems and/or information, meaning the first driver state could be a physiological driver state based on physiological information, the second driver state could be a physiological driver state based on physiological information but derived from a different source than the first driver state, and the third driver state could be a physiological driver state based on physiological information but derived from a different source than either the first or second driver state. In addition, the first, second and third driver states could each be derived from distinct monitoring systems and/or information, meaning the first driver state could be a physiological driver state based on physiological information, the second driver state could be a behavioral driver state based on behavioral information and the third driver state could be a vehicular-sensed driver state based on vehicle information. Any combination of these examples is possible. 
     In step  4406 , the response system  188  can determine a combined driver state based on the plurality of driver states of step  4404 . In some cases, the combined driver state can be normal or drowsy. In other cases, the combined driver state can range over three or more states ranging between normal and very drowsy (or even asleep). As will be discussed in further detail herein, the combined driver state can be determined in various ways. 
     In step  4408 , in some embodiments, the response system  188  can determine whether the driver state is true based on the combined driver state. For example, whether or not the driver is vigilant, drowsy, inattentive, distracted, intoxicated, among others. If the driver state is not true (i.e., NO), the response system  188  can proceed back to step  4402  to receive additional monitoring information. If, however, the driver state is true (i.e., YES), the response system  188  can proceed to step  4410 . 
     In step  4410 , the response system  188  can modify the control of one or more vehicle systems, including any of the vehicle systems discussed above. By modifying the control of one or more vehicle systems, the response system  188  can help to avoid various hazardous situations that can be caused by, for example, a distracted and/or drowsy driver. In some embodiments, step  4408  is optional and after determining a combined driver state at step  4406 , the method can directly proceed to step  4410 , where modifying the control of the one or more vehicle systems is based on the combined driver state.  FIG. 25 , discussed above, illustrates various vehicle systems and how these vehicle systems can be modified or controlled by the response system  188 . 
     As discussed above,  FIG. 26  illustrates an embodiment of a process of modifying the operation of a vehicle system according to the level of drowsiness detected. However, in one embodiment, modifying the operation of a vehicle system can depend on a plurality of driver state levels. In particular, the plurality of driver state levels can be combined into a combined driver state level. Each of the plurality of driver state levels can be one of a physiological driver state level, a behavioral driver state level and a vehicular-sensed driver state level. Thus, the combined driver state level can be based on different types of driver state levels each derived from different types of monitoring information and/or from information from different types of monitoring systems. 
     Referring now to  FIG. 45 , a method is illustrated of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle that depends on a combined driver state level based on a plurality of driver state levels. In step  4502 , the response system  188  can determine a plurality of driver state levels. In one embodiment, each of the plurality of driver state levels is based on at least one of physiological information, behavioral information, and vehicle information. Thus, the plurality of driver state levels are at least one of a physiological driver state level, a behavioral driver state level or a vehicular-sensed driver state level. Said differently, the physiological driver state level is based on physiological information, the behavioral driver state level is based on behavioral information and the vehicular-sensed driver state level is based on vehicle information. 
     The driver state level can be a “level of drowsiness.” The term “level of drowsiness” as used throughout this detailed description and in the claims refers to any numerical or other kind of value for distinguishing between two or more states of drowsiness. For example, in some cases, the level of drowsiness can be given as a percentage between 0% and 100%, where 0% refers to a driver that is totally alert and 100% refers to a driver that is fully drowsy or even asleep. In other cases, the level of drowsiness could be a value in the range between 1 and 10. In still other cases, the level of drowsiness is not a numerical value, but could be associated with a given discrete state, such as “not drowsy,” “slightly drowsy,” “drowsy,” “very drowsy” and “extremely drowsy.” Moreover, the level of drowsiness could be a discrete value or a continuous value. 
     In another embodiment, the driver state level can be a “level of distraction.” The term “level of distraction” as used throughout this detailed description and in the claims refers to any numerical or other kind of value for distinguishing between two or more states of distraction. For example, in some cases, the level of distraction can be given as a percentage between 0% and 100%, where 0% refers to a driver that is totally attentive and 100% refers to a driver that is fully distracted. In other cases, the level of distraction could be a value in the range between 1 and 10. In still other cases, the level of distraction is not a numerical value, but could be associated with a given discrete state, such as “not distracted,” “slightly distracted,” “distracted”, “very distracted” and “extremely distracted”. Moreover, the level of distraction could be a discrete value or a continuous value. In some cases, the level of distraction can indicate the driver is engaged in a secondary task (e.g., other than the primary task of driving). 
     In some cases, the level of drowsiness and/or distraction can be associated with a driver state index. Thus, in some embodiments, in step  4504 , the response system  188  can determine a plurality of driver state indices. In one embodiment, each of the driver state indices are based on at least one of physiological information, behavioral information, and vehicle information. The term “driver state index” refers to a measure of the state of driver, for example, the level drowsiness of a driver and/or the level distraction of the driver. In some cases, the driver state index could be given as a numerical value. In other cases, the driver state index could be given as a non-numerical value. Moreover, the driver state index can range from values associated with complete alertness (e.g., attentive) to values associated with extreme drowsiness (e.g., extreme distraction) or even a state in which the driver is asleep. In one embodiment, the driver state index could take on the values 1, 2, 3 and 4, where 1 is the least drowsy (e.g., distracted) and 4 is the most drowsy (e.g., distracted). In another embodiment, the driver state index could take on values from 1-10. 
     Accordingly, at step  4504 , the plurality of driver state levels are least one of a physiological driver state, a behavioral driver state or a vehicular-sensed driver state. Said differently, the physiological driver state level is based on physiological information, the behavioral driver state level is based on behavioral information and the vehicular-sensed driver state level is based on vehicle information. 
     In some embodiments, step  4504  includes determining a first driver state level and a second driver state level based on the monitoring information from the one or more monitoring systems. In another embodiment, the step  4504  includes determining a third driver state level based on the monitoring information from the one or more monitoring systems. It is appreciated that other combinations of information and driver state levels can be implemented. For example, behavioral information could be used to determine a first driver state level and physiological information could be used to determine a second driver state level, and so on. 
     It is appreciated that any number of driver state levels can be determined. In one embodiment, the first driver state level is one of a physiological driver state level, a behavioral driver state level or a vehicular-sensed driver state level, and the second driver state level is another of a physiological driver state level, a behavioral driver state level or a vehicular-sensed driver state level. The third driver state level can be a further one of a physiological driver state level, a behavioral driver state level or a vehicular-sensed driver state level. By using different types of monitoring information to determine different driver states, multi-modal driver state confirmation is possible, as will be described herein. The driver state levels can be determined by the response system  188 , the vehicle 
     In step  4506 , the response system  188  can determine a combined driver state level based on the plurality of driver state levels of step  4504 . In another embodiment, in step  4506 , the response system  188  can determine a combined driver state index based on the plurality of driver state indices of step  4504 . As will be discussed in further detail herein, the combined driver state can be determined in various ways. 
     In step  4508 , in some embodiments, the response system  188  can determine whether or not the driver state is true based on the combined driver state level and/or index. For example, whether or not the driver is vigilant, drowsy, inattentive, distracted, intoxicated, among others. If the driver state is not true (i.e., NO), the response system  188  can proceed back to step  4502  to receive additional monitoring information. If, however, the driver state is true (i.e., YES), the response system  188  can proceed to step  4510 . 
     In step  4510 , the response system  188  can modify the control of one or more vehicle systems, including any of the vehicle systems discussed above. By modifying the control of one or more vehicle systems, the response system  188  can help to avoid various hazardous situations that can be caused by, for example, a drowsy and/or distracted driver. In some embodiments, step  4508  is optional and after determining a combined driver state at step  4506 , the method can directly proceed to step  4510 , where modifying the control of the one or more vehicle systems is based on the combined driver state. 
     In another embodiment and with reference to  FIG. 46 , driver states can be determined and combined into one or more groups. In step  4602 , the response system  188  can determine a plurality of driver states, and in some embodiments, driver state levels. At step  4604 , the method includes determining a first combined driver state based on the plurality of driver states of step  4602 . In this embodiment, the first combined driver state can be based on a subset of the plurality of driver states. For example, at step  4604 , a first driver state, a second driver state, a third driver state and a fourth driver state can be determined. Accordingly, at step  4606 , the first combined driver state can be based on a subset of the plurality of driver states, for example, the first driver state and the second driver state. In other embodiments, the first combined driver state is based on the first driver state and the third driver state, or any other combination. 
     At step  4608 , the method can include determining a second combined driver state. The second combined driver state can be based on the first combined driver state and one or more other driver states. For example, if the first combined driver state is based on the first driver state and the second driver state, the second combined driver state can be based on the first combined driver state, the third driver state and the fourth driver state. It is appreciated, that other combinations of driver states and combined driver states can be implemented. Further, it is appreciated that a second set of a plurality of driver states can be determined at step  4608 . In this embodiment, the second combined driver state can be based on the first combined driver state and the second set of plurality of driver states. 
     In step  4508 , in some embodiments, the response system  188  can determine whether or not the driver state is true based on the combined driver state level and/or index. For example, whether or not the driver is vigilant, drowsy, inattentive, distracted, intoxicated, among others. If the driver state is not true (i.e., NO), the response system  188  can proceed back to step  4602  to receive additional monitoring information. If, however, the driver state is true (i.e., YES), the response system  188  can proceed to step  4612 . 
     At step  4612 , the vehicle systems can be controlled based on the first combined driver state and/or the second combined driver state. It is appreciated, that although  FIG. 46  illustrates two combined driver states, the process can include more than two combined driver states. 
     As discussed above with  FIG. 27 , in some embodiments, the response system  188  can determine a control parameter. In one embodiment, the control parameter can be based on the combined driver state level determined by the response system  188  in step  4506  of  FIG. 45 . The term “control parameter” as used throughout this detailed description and in the claims refers to a parameter used by one or more vehicle systems. In some cases, a control parameter can be an operating parameter that is used to determine if a particular function should be activated for a given vehicle system. The control parameter can be used in step  4506  to modify the control of one or more vehicle systems. 
     Determining a control parameter based on the combined driver state level and/or index will now be discussed.  FIG. 47  illustrates a schematic view of how a combined driver state index can be used to retrieve a control coefficient. A control coefficient can be any value used in determining a control parameter. In some cases, the control coefficient varies as a function of driver state index and is used as an input for calculating the control parameter. Examples of control coefficients include, but are not limited to electronic stability control system coefficients, brake assist coefficients, blind spot zone warning coefficients, warning intensity coefficients, forward collision warning coefficients, lane departure warning coefficients and lane keep assist coefficients. Some systems cannot use a control coefficient to determine the control parameter. For example, in some cases, the control parameter can be determined directly from the driver state index. 
     In one embodiment, the value of the control coefficient  4702  increases from 0% to 25% as the combined driver state index increases from 1 to 4. In some cases, the control coefficient can serve as a multiplicative factor for increasing or decreasing the value of a control parameter. For example, in some cases when the combined driver state index is 4, the control coefficient can be used to increase the value of a control parameter by 25%. In other embodiments, the control coefficient could vary in any other manner. In some cases, the control coefficient could vary linearly as a function of the combined driver state index. In other cases, the control coefficient could vary in a nonlinear manner as a function of the combined driver state index. In still other cases, the control coefficient could vary between two or more discrete values as a function of the combined driver state index. 
       FIG. 29 , discussed above, illustrates a calculation unit  2902  for determining a control parameter. The calculation unit  2902  receives a control coefficient  2904  and vehicle operating information  2906  as inputs. The calculation unit  2902  outputs the control parameter  2908 . The vehicle operating information  2906  can include any information necessary to calculate a control parameter. For example, in situations where the vehicle system is an electronic stability control system, the system can receive wheel speed information, steering angle information, roadway friction information, as well as other information necessary to calculate a control parameter that is used to determine when stability control should be activated. Moreover, the control coefficient  2904  can be determined from the combined driver state index using, for example, a look-up table. The calculation unit  2902  then considers both the vehicle operating information and the control coefficient  2904  in calculating the control parameter  2908 . 
     In some embodiments, a control parameter can be associated with a status or state of a given vehicle system.  FIG. 48  illustrates an embodiment of a general relationship between the combined driver state index of the driver and a system status  4802 . The system shown here is general and could be associated with any vehicle system. For a low combined driver state index (1 or 2), the system status  4802  is ON. However, if the combined driver state index increases to 3 or 4 the system status  4802  is turned OFF. In still other embodiments, a control parameter could be set to multiple different “states” according to the combined driver state index. Using this arrangement, the state of a vehicle system can be modified according the combined driver state index of a driver. 
     i. Exemplary Driver State Combinations 
     Determining a combined driver state and/or a combined driver state index will now be described in further detail. It is appreciated that the following combinations can be implemented with the systems and methods for confirming driver states as will be discussed below.  FIG. 49  illustrates an exemplary AND logic gate  4902  that can be executed by the response system  188  for combining a plurality of driver states, namely, a first driver state (DS 1 ) and a second driver state (DS 2 ). It is understood that any number of driver states can be combined (e.g., DS i  . . . DS n ). Further, as discussed above, it is understood that a driver state can also be a driver state index. In  FIG. 49 , each driver state is determined based on one of a plurality of monitoring information types, namely, physiological information, behavioral information, and vehicle information. Accordingly, the first driver state and the second driver state are each one a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. In particular, in one embodiment, the first driver state, and the second driver state are each a different one of said driver states. In another embodiment, the first driver state and the second driver state can be the same type (i.e., behavioral) but derived from different monitoring systems and/or information. 
     At the AND logic gate  4902 , the response system  188  analyzes the first driver state and the second driver state to determine a combined driver state. In the illustrative examples discussed herein, drowsiness will be used as an exemplary driver state, however, it is understood that other driver states can be implemented. For example, if the first driver state (e.g., a physiological driver state) indicates a drowsy driver state (i.e., YES; 1) and the second driver state (e.g., a vehicular-sensed driver state) indicates a drowsy driver state (i.e., YES; 1), the combined driver state returned by the gate  4902  indicates a drowsy driver state (i.e., YES; 1), based on the first driver state and the second driver state. In another example, if the first driver state (e.g., a behavioral driver state) indicates a non-drowsy driver state (i.e., NO; 0), and the second driver state (e.g., a physiological driver state) indicates a drowsy driver state (i.e., YES; 1), the combined driver state returned by the gate  4902  indicates a non-drowsy driver state (i.e., NO; 0), based on the first driver state and the second driver state. 
     A truth table  4904  illustrates the various combinations and functions for the AND logic gate  4902 . Although the AND logic gate  4902  is described with Boolean values, it is understood that in other embodiments, which will be described herein, the first driver state, the second driver state and the combined driver state can each include numeric values (e.g., a driver state index, a combined driver state index). Thus, the response system  188  can determine a combined driver state based on the first driver state numeric value and/or the second driver state numeric value as a result of the output of the AND logic gate  11700 . 
       FIG. 50  illustrates another exemplary AND logic gate  5002  for combining a plurality of driver states. In this example, a first driver state (DS 1 ), a second driver state (DS 2 ) and a third driver state (DS 3 ) are combined. Similar to  FIG. 49 , each of the driver states is determined based on one of a plurality of monitoring information types, namely, physiological information, behavioral information, and vehicle information. Accordingly, the first driver state, the second driver state and the third driver state, are one a physiological driver state, a behavioral driver state and a vehicular-sensed driver state. However, it is understood that in other embodiments, the one or more of the driver states can be based on physiological information, behavioral information, and vehicle information. 
     At the AND logic gate  5002 , the response system  188  analyzes the first driver state, the second driver and the third driver state inputs to determine a combined driver state. For example, if the first driver state (e.g., a physiological driver state) indicates a drowsy driver state (i.e., YES; 1), the second driver state (e.g., a vehicular-sensed driver state) indicates a drowsy driver state (i.e., YES; 1), and the third driver state (e.g., a behavioral driver state) indicates a drowsy driver state (i.e., YES; 1), the combined driver state returned by the gate  5002  indicates a drowsy driver state (i.e., YES; 1), based on the first driver state, the second driver state and the third driver state. In another example, if the first driver state (e.g., a behavioral driver state) indicates a non-drowsy driver state (i.e., NO; 0), the second driver state (e.g., a physiological driver state) indicates a drowsy driver state (i.e., YES; 1), and the third driver state (e.g., a vehicular-sensed driver state) indicates a drowsy driver state (i.e., YES; 1), the combined driver state returned by the gate  5002  indicates a non-drowsy driver state (i.e., NO; 0), based on the first driver state, the second driver state and the third driver state. A truth table  5004  illustrates the various combinations and functions for the AND logic gate  5002 . 
     Although the AND logic gate  5002  is described with Boolean values, it is understood that in other embodiments, which will be described herein, the first driver state, the second driver state, the third driver state and the combined driver state can each include numeric values (e.g., a driver state index, a combined driver state index). Thus, the response system  188  can determine a combined driver state based on the first driver state numeric value, the second driver state numeric value and/or the third driver state numeric value as a result of the output the AND logic gate  5002 . 
       FIG. 51  illustrates an exemplary AND/OR logic gate  5102  that can be executed by the response system  188  for combining a plurality of driver states, namely, a first driver state (DS 1 ), a second driver state (DS 2 ) and a third driver state (DS 3 ). Similar to  FIGS. 49 and 50 , each of the driver states is determined based on one of a plurality of monitoring information types, namely, physiological information, behavioral information, and vehicle information. Accordingly, the first driver state, the second driver state and the third driver state, are one a physiological driver state, a behavioral driver state and a vehicular-sensed driver state. However, it is understood that in other embodiments, the one or more of the driver states can be based on physiological information, behavioral information, and vehicle information. 
     At the AND/OR logic gate  5102 , the response system  188  analyzes the first driver state, the second driver and the third driver state inputs to determine a combined driver state. The AND/OR logic gate  5102 , includes an OR logic gate  5104  to analyze a first driver state and a second driver state and an AND logic gate  5106  to analyze an output of the OR logic gate  5104  and the third driver state. For example, if the first driver state (e.g., a physiological driver state) indicates a drowsy driver state (i.e., YES; 1), and the second driver state (e.g., a vehicular-sensed driver state) indicates a drowsy driver state (i.e., YES; 1), the output of the OR logic gate  5104  indicates a drowsy driver state (i.e., YES; 1). Accordingly, if the third driver state (e.g., a behavioral driver state) indicates a drowsy driver state (e.g., YES; 1), the combined driver state returned by the gate  5106  indicates a drowsy driver state (e.g., YES; 1), based on the first driver state, the second driver state and the third driver state. 
     In another example, if the first driver state (e.g., a vehicular-sensed driver state) does not indicate a drowsy driver state (i.e., NO; 0), and the second driver state (e.g., a physiological driver state) indicates a drowsy driver state (i.e., YES; 1), the output of the OR logic gate  5104  indicates a non-drowsy driver state (i.e., NO; 0). Accordingly, if the third driver state (e.g., a behavioral driver state) indicates a drowsy driver state (i.e., YES; 1), the combined driver state returned by the gate  5106  indicates a drowsy driver state (i.e., YES; 1), based on the first driver state, the second driver state and the third driver state. In some embodiments, the combined driver state can be based on only those driver states that indicate a drowsy driver state (i.e., YES; 1). Thus, in the previous example, the combined driver state can be based on the second driver state and the third driver state. 
     A truth table  5108  illustrates the various combinations and functions of the AND/OR logic gate  5102 . Although the AND/OR logic gate  5102  is described with Boolean values, it is understood that in other embodiments, which will be described herein, the first driver state, the second driver state, the third driver state, and the combined driver state can each include numeric values (e.g., a driver state index, a combined driver state index). Thus, the response system  188  can determine a combined driver state based on the first driver state numeric value, the second driver state numeric value and/or the third driver state numeric value as a result of the output the AND/OR logic gate  5102 . 
     ii. Exemplary Combined Driver State Calculations 
     As mentioned above, each driver state (e.g., a physiological driver state, a behavioral driver state, and a vehicular-sensed driver state) and the combined driver state can be quantified as a level, a numeric value or a numeric value associated with a level. For example, as a driver state level, a combined driver state level, a driver state index, a combined driver state index, among others. Based on the methods, examples and logic gates described above in  FIGS. 44-51 , the combined driver state can be computed in various ways. In the examples that follow, each driver state will be quantified as a driver state index and the combined driver state will be quantified as a combined driver state index, however, it is appreciated that other combinations or quantifications are contemplated. 
     In one embodiment, the response system  188  determines a combined driver state index by aggregating each driver state index (i.e., each driver state). For example, the combined driver state index I is the sum of one or more driver state indices as follows:
 
 I=Σ   i=1   n   DS   i   (10)
 
Where I is the combined driver state index and DS i  is the driver state index for DS i  . . . DS n . In one embodiment, each driver state index DS i  is one of a plurality of driver states (e.g., a physiological driver state, a behavioral driver state, a vehicular-sensed driver state). As an illustrative example, with reference to the AND logic gate  5002  of  FIG. 50 , let DS 1 =5 (i.e., a physiological driver state index) indicating a drowsy driver state (i.e., YES; 1), DS 2 =6 (i.e., a behavioral driver state index) indicating a drowsy driver state (i.e., YES; 1), and DS 3 =4 (i.e., a vehicular-sensed driver state index) indicating a drowsy driver state (i.e., YES; 1). The AND logic gate  5002  returns a combined driver state index indicating a drowsy driver state (i.e., YES; 1). Accordingly, the response system  188  computes the combined driver state index using equation (1) as 15 (5+6+4).
 
     In some embodiments, the combined driver state could be based on selecting driver states that return a YES value (i.e., indicating a drowsy driver state). As an illustrative example, with reference to the AND/OR logic gate  5102  of  FIG. 51 , let DS 1 =2 (i.e., a physiological driver state index) indicating a non-drowsy driver state (i.e., NO; 0), DS 2 =6 (i.e., a behavioral driver state index) indicating a drowsy driver state (i.e., YES; 1), and DS 3 =4 (i.e., a vehicular-sensed driver state index) indicating a drowsy driver state (i.e., YES; 1) The AND/OR logic gate  5102  returns a combined driver state indicating a drowsy driver state (i.e., YES; 1). Accordingly, the response system  188  computes the combined driver state index using equation (1) and based on DS 2  and DS 3 , as 10 (6+4). It is understood, that in other embodiments, the combined driver state index can be based on each driver state index, regardless of whether the driver state index indicates a drowsy driver state. 
     In another embodiment, the response system  188  determines a combined driver state index as an average of each driver state index. For example, the combined driver state index I is the average of one or more driver state indices as follows: 
                   I   =         ∑     i   =   1     n     ⁢           ⁢     DS   i       n             (   11   )               
Where k is the combined driver state index and DS i  is the driver state index for DS i , . . . DS n . Similar to the illustrative examples describing equation (10), the combined driver state according to equation (11) can be based on each driver state or based on each driver state that returns a YES value (i.e., indicating a drowsy driver state).
 
     In a further embodiment, the response system  188  determines a combined driver state index as a weighted average of each driver state index. For example, the combined driver state index I is the weighted average of one or more driver state indices as follows: 
                   I   =         ∑     i   =   1     n     ⁢           ⁢       DS   i     ⁢     w   i             Σ   i   n     ⁢     w   i                 (   12   )               
Where I is the combined driver state index and DS i  is the driver state index for DS i  . . . DS n . The weight of each driver state index can be based on different factors. In one embodiment, the weight of each driver state index is based on the type of driver state, the type of monitoring information and/or the type of monitoring system and sensors. In another embodiment, the weight of each driver state index is based on the quality of the monitoring information (e.g., signal strength). In a further embodiment, the weight of each driver state index is based on a location or a placement of the monitoring systems and sensors. In some embodiments, the weight of each driver state index can be pre-determined and/or based on the identity of the driver. In other embodiments, the weight of each driver state index can be dynamically selected or learned using artificial intelligence. In other embodiments, the weight of each driver state index is based on a confidence score of the applicable system or the data received from the applicable system.
 
     It is understood that various selections of driver states and combinations of driver states can be implemented with the methods discussed above. In some embodiments, the selections of driver states and combinations of driver states can be determined using artificial intelligence, such as a neural network. Further, it is understood that the exemplary combinations and computations described above can be used in whole or in part with the methods discussed below. 
     2. Determine Combined Driver State with Threshold Comparisons 
     In one embodiment, determining the combined driver state includes comparing at least one of the plurality of driver states to a threshold. Specifically, in some cases, determining the combined driver state further includes comparing at least one of the plurality of driver states to a threshold, and upon determining the at least one of the plurality of driver states meets the threshold, determining the combined driver state based on the least one of the plurality of driver states. Thus, for example, upon determining that a first driver state meets a first driver state threshold and a second driver state meets a second driver state threshold, the combined driver state is determined based on the first driver state and the second driver state. 
     The term “threshold” as used throughout this detailed description and in the claims refers to any numerical or other kind of value used for comparison with another value to determine one or more driver states, confirm one or more driver states, combine one or more driver states, modify one or more vehicles systems, determine or modify a control parameter, a control coefficient, or a failsafe threshold, among others. In some cases, the threshold is given as a percentage, a value between 1 and 10, a discrete value, a continuous value, or a range of values. The threshold can also be a frequency or a function of time. As will be discussed in more detail herein, the thresholds can be pre-determined and dynamically modified based on the driver states, the monitoring information, and/or the identity of the driver. 
       FIG. 52  illustrates a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle, similar to  FIG. 45 , except the process of  FIG. 52  includes threshold comparisons. The method of  FIG. 52  includes at step  5202  receiving monitoring information. At step  5204 , the method includes determining a plurality of driver state levels (e.g., DS i  . . . DS n ) based on the monitoring information. In one embodiment, each driver state is associated with a threshold related to said driver state. For example, a first driver state DS i  can be associated with a first driver state threshold T i . Accordingly, in  FIG. 52 , at step  5206 , for each driver state (e.g., while i&gt;0), it is determined if the driver state DS i  meets the threshold T i . If so (i.e., YES), DS i  is stored, for example, in an array at step  5208 , and a counter X is incremented. Once each driver state is compared to its associated threshold, at step  5210 , it is determined if X is greater than 0. If so (i.e., YES), the stored driver states which met the associated thresholds are used to determine a combined driver state at step  5212 . If not (i.e., NO, none of the driver states met the associated threshold), the method can return to step  5202  to receive monitoring information. 
     Referring now to  FIG. 53 , the exemplary AND logic gate of  FIG. 50  is shown as AND logic gate  5302  with threshold logic (i.e., T 1 , T 2 , T 3 ). The threshold can be related to the driver state and/or the monitoring information used to determine the driver state. As an illustrative example, if the first driver state DS 1  is based on heart rate (i.e., physiological information), the first driver state threshold T i  can be a numeric value indicating a high heart rate. It is appreciated that the thresholds described above can be applied to any number of driver states, to any of the logic gates discussed above and the confirmation of one or more driver states discussed below. 
     As mentioned above, the thresholds can be pre-determined and dynamically modified based on the driver states, the information used to determine the driver state (e.g., heart information, head pose information), the type of information and/or driver state (e.g., physiological, behavioral, vehicular), other types of monitoring information, and/or the identity of the driver. Accordingly, the thresholds provide an accurate measurement for the specific driver state, driver, and driving environment for determining the driver states, combining the driver states, and confirming the driver states. Illustrative embodiments will now be discussed. 
     In one embodiment, the thresholds can be determined and/or dynamically changed based on the monitoring information received, for example, from the systems shown in  FIGS. 2 and 3 . As mentioned above, the threshold can be related to the driver state and/or the monitoring information used to determine the driver state. As an illustrative example, if the first driver state is based on contiguous heart rate accelerations or decelerations, the first driver state threshold may be a numeric value indicating a high number of contiguous heart rate accelerations or decelerations. For example, a high number of contiguous heart rate accelerations or decelerations can be associated with a numeric value of 13. 
     Accordingly, the threshold can be related to a pattern of monitoring information. For example, the driver state can be number indicating a pattern and/or frequency of monitoring information over a period of time. Thus, the threshold can be a value associated with the pattern over a period of time. In one embodiment, the driver state can be based on steering information, for example, steering information indicating jerks, and/or steering corrections over a period of time. Accordingly, the threshold can be set to a value to determine whether the pattern of steering jerks over a period of time indicates a drowsy or non-drowsy driver. As an illustrative example, a threshold of 10 jerks in 30 seconds can indicate a drowsy driver. 
     In another embodiment, the driver state can be a number indicating lane departures over a period of time. Accordingly, the threshold can be set to a value to determine whether the number of lane departures over a period of time indicate a drowsy or non-drowsy driver. In another embodiment, the driver state can be a number indicating the number of acceleration and decelerations over a period of time. Accordingly, the threshold can be set to a value to determine whether the number acceleration and decelerations over a period of time indicate a drowsy or non-drowsy driver. 
     In another embodiment, the driver state can be a number indicating a frequency of head nods (e.g., the number of head nods over a period of time). Accordingly, the threshold can be set to a value to determine whether the frequency of head nods over a period of time indicate a drowsy or non-drowsy driver. In another example, the driver state can be a number of head looks from a forward-looking direction to a non-forward-looking direction (e.g., looking at a navigation system). Accordingly, the threshold can be set to a value to determine whether the driver is attentive or distracted. For example, a threshold of 10 head looks can indicate an inattentive driver. 
     In another embodiment, the threshold can indicate a pattern and/or frequency of monitoring information over time including vectoring (e.g., magnitude/length of time, direction) information about the head, eyes and/or body of the driver. For example, a driver state can be a number of head looks from a forward-looking direction to a head looking direction directed to a navigation system, where the head looking direction has a magnitude (e.g., time length) of a pre-determined number of seconds. Accordingly, the threshold can be set to a value to determine whether the driver is attentive or distracted based on the head vectoring, for example, five head looks. 
     As discussed above, the thresholds can be dynamically modified based on monitoring information. For example, a threshold can be dynamically modified based on gesture information from the gesture recognition and monitoring system  330 . For example, if it is determined based on the gesture information that the driver is operating a portable device in their hand, a threshold can be automatically adjusted to account for this risk. Thus, a threshold indicating an inattentive driver state could be lowered. As another example, if the driver&#39;s breathing is determined to be irregular based on information from the respiratory monitoring system  312 , a threshold indicating a stressed driver state could be lowered. 
     In another embodiment, the threshold can be modified based on contact and position information of the driver&#39;s hands with the steering wheel. For example, the threshold can be modified based on information from the touch steering wheel system  134 . In another example, a threshold related to a driver state based on perspiration rate information, can be adjusted based on monitoring information from the vehicle systems  126 . For example, the monitoring information from a climate control system may indicate the internal temperature of the vehicle is hot. If the internal temperature of the vehicle is hot, the driver can naturally have a higher perspiration rate. Thus, perspiration rate may not be an accurate indication of a driver state and the associated threshold may be increased. 
     Additionally, as mentioned above, the thresholds can be pre-determined and/or modified based on the identity of the driver and characteristics of the identified driver. For example, the response system  188  can determine the identity of the driver based on monitoring information, for example, from the systems of  FIG. 3  as discussed in Section III (B) (4). In some embodiments, systems and methods of biometric identification ( FIGS. 22-23 ) can be used to identify the driver and store normative data and/or past and current thresholds associated with the driver. It is appreciated that the response system  188  can use a machine pattern learning method to track monitoring information for the identified driver and determine normative baseline data for the identified driver. Any machine learning method or pattern recognition algorithm could be used. The normative baseline data can be used to determine the thresholds and/or modified the thresholds for the identified driver. Further, average, and/or normative data for other drivers with similar characteristics of the identified driver (e.g., age, sex) can be used to determine the thresholds and/or modified the thresholds for the identified driver. Accordingly, the thresholds are adaptive and learned overtime and/or are controlled based on the identity of the driver. 
     In one embodiment, the driver state can be a number indicating the number of acceleration and decelerations over a period of time. Accordingly, the response system  188 , after identifying the driver, can modify the threshold related to the number of acceleration and decelerations over a period of time based on the particular driving habits of the driver. For example, the driver&#39;s baseline data may show that the driver typically has a high number of accelerations and decelerations. Accordingly, the threshold can be modified to account for the driver&#39;s baseline data. For example, the threshold for indicating a drowsy driver may be increased. 
     Referring again to the illustrative example above where a threshold is a numeric value indicating a high number of contiguous heart rate accelerations or decelerations, the baseline threshold can be set to a numeric value of 13 to indicate a drowsy driver. However, after tracking the data of the identified driver, the numeric value of 13 may not indicate a drowsy driver state for the identified driver. Accordingly, the system may modify the value to 15. 
     In another embodiment, the response system  188  can determine that the normative baseline heart rate of a particular driver is higher than an average adult heart rate. Accordingly, the response system  188  can dynamically modify the threshold related to heart rate for the driver based on the driver normative baseline heart rate. In another embodiment, the response system  188  can determine an age of the driver based on the identity of the driver. For example, the response system  188 , after determining the identity of the driver, can retrieve a user profile including characteristics user preferences for the identified driver. The characteristics can include the age of the driver. The response system  188  can modify and/or determine the threshold based on the age of the driver. For example, a threshold associated with an alcohol level may be decreased (e.g., providing more strict control by lowering the alcohol level needed to reach the threshold) for a young driver. 
     In another embodiment, the response system  188  can determine that one or more vehicle occupants are present in the vehicle. The response system  188  can modify the threshold levels for the driver based on determining that one or more vehicle occupants are present. For example, a vehicle speed threshold may be lowered since to provide more safety for the other vehicle occupants present in the vehicle. In another embodiment, the response system  188  can identify the one or more vehicle occupants present in the vehicle and modify the threshold based on a characteristic of the one or more vehicle occupants. For example, if one of the vehicle occupants is young (e.g., a baby), the thresholds can be modified As discussed above, in one embodiment, the driver state can be based on steering information, for example, steering information indicating jerks and/or steering corrections over a period of time. Accordingly, after identifying a young vehicle occupant is present in the vehicle, the response system  188  can modify the threshold (e.g., decrease) for determine whether the pattern of steering jerks over a period of time indicates a drowsy driver. 
     Referring now to  FIG. 54 , a general process for determining and/or modifying a threshold is shown. At step  5402 , the method includes receiving monitoring information. In some embodiments, at step  5402 , the method can also include receiving and/or determining a driver state (e.g., based on the monitoring information). At step  5404 , the method includes identifying the driver, for example, using the methods and systems discussed in Section III (B) (4). Step  5404  can also include, at step  5408 , receiving stored driver data. The stored driver data can include monitoring information tracked over time (e.g., using machine and pattern learning algorithms). The stored driver data can be received using the telematics control unit from the Internet, a network, a storage device located at a network, among others. 
     At step  5406 , the method includes modifying and/or determining a threshold based on the identity of the driver. More specifically, the response system  188  can analyze the stored driver data to determine patterns of the identified driver and modify and/or determine the threshold accordingly. It is understood that the exemplary driver states, thresholds, and modifications discussed above are exemplary and other driver states, thresholds, and modifications can be implemented. 
     In some embodiments, the process shown in  FIG. 54  can apply to determining and/or modifying a control parameter and/or a control coefficient. Thus, at step  5406  of  FIG. 54 , the method can include modifying a control parameter and/or a control coefficient of one or more vehicle systems based on the identified driver. As an illustrative example, in situations where a lane deviation warning system is used, the control parameter can be a distance threshold to a potential lane deviation to provide a warning to the driver. Based on the identity of the driver and tracking the data of the identified driver (e.g., the stored driver data), the response system  188  may determine that the identified driver tends to drive close to the lane markers. Accordingly, the response system  188  can modify the control parameter based on the identified driver. For example, the response system  188  can decrease the distance threshold to a potential lane deviation to account for the identified driver&#39;s tendency to driver close to the lane markers. 
     As another illustrative example, in situations where an electronic stability control system is used, the control coefficient can be a stability error of steering associated with under-steering or over-steering. Based on the identity of the driver and tracking the data of the identified driver (e.g., the stored driver data), the response system  188  may determine that the identified driver naturally driver with a slight over-steer. Accordingly, the response system  188  can modify stability error of steering associated over-steering based on the identified driver. For example, the response system  188  can decrease the stability error of steering associated over-steering to account for the identified driver&#39;s slight over-steer. In some embodiments, the control coefficient can be modified as function of the pattern associated with the identified driver. For example, if the driver naturally drives with a moderate over-steer, the response system  188  can decrease the stability error of steering associated over-steering more than, if the driver naturally drives with a slight over-steer. Similarly, the control parameter can be modified as a function of the pattern associated with the identified driver. 
     3. Determine Combined Driver State with Confirmation of One or More Driver States 
     In one embodiment, the system and methods for responding to driver state include confirming one or more driver states with other driver states to determine a combined driver state. Said differently, the response system  188  can confirm at least one selected of the plurality of driver states with at least one selected different one of the plurality of driver states and determine a combined driver state index based on the at least one selected of the plurality of driver states and the at least one selected different one of the plurality of driver states. 
     The term “confirming,” as used herein can include comparing two values to validate the state of the driver. Accordingly, a first driver state can be confirmed with a second driver state by comparing the first driver state to the second driver state and determining if the first driver state and the second driver state both indicate the same or substantially the same driver state. 
       FIG. 55  illustrates a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle with confirming one or more driver states to determine a combined driver state. At step  5502 , the method includes receiving monitoring information. At step  5504 , the method includes determining a plurality of driver states. In one example, determining a plurality of driver states can include determining a first driver state and a second driver state. In some cases, each state of the plurality of driver states is determined based on one of a plurality of monitoring information types, namely, physiological information, behavioral information, and vehicle information. Accordingly, in one example, the first driver state and the second driver state are one of a physiological driver state, a behavioral driver state, and a vehicular-sensed driver state. 
     At step  5506 , the method includes confirming at least one selected of the plurality of driver states with at least one selected different one of the plurality of driver states. In one embodiment, confirming includes comparing the at least one selected of the plurality of driver states with the at least one selected different one of the plurality of driver states. For example, in  FIG. 55 , the first driver state DS 1  is confirmed with the second driver state DS 2 . If the first driver state is a physiological driver state indicating a drowsy driver (i.e., YES; 1) and the second driver state is a behavioral driver state indicating a drowsy driver (i.e., YES; 1), then at step  5508 , the combined driver state would indicate a drowsy driver. In another example, if the first driver state is a physiological driver state indicating a drowsy driver (i.e., YES; 1) and the second driver state is a vehicular-sensed driver state indicating a non-drowsy driver (i.e., NO; 1), then at step  5508 , the combined driver state would indicate a non-drowsy driver. In some embodiments if the output of the confirmed driver state is NO, then the process may proceed back to step  5502  to receive monitoring information. It is understood that steps  5506  and  5508  could be processed using the logic gates of  FIGS. 49, 50, and 51 . It is also understood that the method of  FIG. 55  can apply to a state or a level of state. For example, determining a driver state, a driver state level, a combined driver state, and a combined driver state level. 
     In further embodiment, the response system  188  can confirm at least one driver state of the plurality of driver states with another one of the plurality of driver states and combine the at least one driver state of the plurality of driver states with the another one of the plurality of driver states. As discussed above, and referring again to  FIG. 55 , at step  5506 , the method includes confirming at least one selected of the plurality of driver states with at least one selected different one of the plurality of driver states. In one embodiment, confirming includes comparing the at least one selected of the plurality of driver states with the at least one selected different one of the plurality of driver states. For example, if the first driver state is a physiological driver state indicating a drowsy driver (i.e., YES; 1) and the second driver state is a behavioral driver state indicating a drowsy driver (i.e., YES; 1), then at step  11306 , determining a combined driver state can include determining the combined driver state based on the first driver state and the second driver state. For example, determining the combined driver state can include aggregating the first driver state and the second driver state, calculating an average of the first driver state and the second driver state, calculating a weighted average of the first driver state and the second driver state, and so on. It is understood that steps  5506  and  5508  could be processed using the logic gates of  FIGS. 49, 50, and 51 . It is also understood that the method of  FIG. 55  can apply to a state or a level of state. For example, determining a driver state, a driver state level, a combined driver state, and a combined driver state level. 
     In some embodiments confirming one driver state with one or more driver states to determine a combined driver state can include comparing said driver states to a particular threshold as discussed above with reference to  FIG. 52 .  FIG. 56  illustrates a method of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle with confirming one or more driver states to determine a combined driver state including thresholds. 
     At step  5602 , the method includes receiving monitoring information. At step  5604 , the method includes determining a plurality of driver states. At step  5606 , the method includes confirming at least one selected of the plurality of driver states with at least one selected different one of the plurality of driver states. In one embodiment, confirming includes comparing the at least one selected of the plurality of driver states with the at least one selected different one of the plurality of driver states. 
     At step  5608 , for each confirmed driver state (e.g., while i&gt;0), it is determined if the confirmed driver state DS i  meets the threshold T i . If so (i.e., YES), DS i  is stored, for example, in an array at step  5610 , and a counter X is incremented. Once each confirmed driver state is compared to its associated threshold, at step  5612 , it is determined if X is greater than 0. If so (i.e., YES), the stored driver states which met the associated thresholds are used to determine a combined driver state at step  5614 . If not (i.e., NO; none of the driver states met the associated threshold hold), the method can return to step  5602  to receive monitoring information. As an illustrative example, in  FIG. 56 , the first driver state DS 1  is confirmed with the second driver state DS 2 . If the first driver state is a physiological driver state indicating a drowsy driver (i.e., YES; 1) and the second driver state is a behavioral driver state indicating a drowsy driver (i.e., YES; 1), then at step  5614 , the combined driver state would indicate a drowsy driver. It is understood that steps  5606  and  5614  could be processed using the logic gates of  FIGS. 49, 50, and 51 . It is also understood that the method of  FIG. 56  can apply to a state or a level of state. For example, determining a driver state, a driver state level, a combined driver state, and a combined driver state level. 
       FIG. 57  illustrates another embodiment of a method of a process for controlling one or more vehicle systems in a motor vehicle with confirming one or more driver states to determine a combined driver state including thresholds. In the embodiment of  FIG. 57 , at step  5702  the method includes receiving monitoring information. At step  5704 , the method includes determining a plurality of driver states. At step  5706 , for each driver state (e.g., while i&gt;0), it is determined if the driver state DS i  meets the threshold T L . If so (i.e., YES), DS i  is stored, for example, in an array at step  5708 , and a counter X is incremented. If not, (i.e., NO), the method can end and return to step  5704 . 
     Once each driver state is compared to its associated threshold, at step  5710 , it is determined if X is greater than 0. If not (i.e., NO; none of the driver states met the associated threshold hold), the method can return to step  5702  to receive monitoring information. If so (i.e., YES), one or more of the stored driver states that met the associated thresholds are confirmed at step  5712 . Specifically, the method includes confirming at least one selected of the plurality of driver states with at least one selected different one of the plurality of driver states. In one embodiment, confirming includes comparing the at least one selected of the plurality of driver states with the at least one selected different one of the plurality of driver states. In  FIG. 57 , the first driver state DS 1  is confirmed with the second driver state DS 2 . For example, if the first driver state is a physiological driver state indicating a drowsy driver (i.e., YES; 1) and the second driver state is a behavioral driver state indicating a drowsy driver (i.e., YES; 1), then at step  5714 , determining a combined driver state can include determining the combined driver state based on the first driver state and the second driver state. For example, determining the combined driver state can include aggregating the first driver state and the second driver state, calculating an average of the first driver state and the second driver state, calculating a weighted average of the first driver state and the second driver state, and so on. It is understood that steps  5712  and  5714  could be processed using the logic gates of  FIGS. 49, 50, and 51 . It is also understood that the method of  FIG. 57  can apply to a state or a level of state. For example, determining a driver state, a driver state level, a combined driver state, and a combined driver state level. 
       FIG. 58  illustrates another embodiment of a method of a process for controlling one or more vehicle systems in a motor vehicle with confirming one or more driver states to determine a combined driver state including thresholds. In the embodiment of  FIG. 58 , at step  5802  the method includes receiving monitoring information. At step  5804 , the method includes determining a plurality of driver states. At step  5806 , for each driver state (e.g., while i&gt;0), it is determined if the driver state DS i  meets the threshold T L . If so (i.e., YES), DS i  is stored, for example, in an array at step  5808 , and a counter X is incremented. If not (i.e., NO), the process can return to step  5804 ). 
     Once each driver state is compared to its associated threshold, at step  5810 , it is determined if X is greater than 0. If not (i.e., NO; none of the driver states met the associated threshold hold), the method can return to step  5802  to receive monitoring information. If so (i.e., YES), one or more of the stored driver states that met the associated thresholds are confirmed at step  5812 . 
     Specifically, at step  5812  the method includes confirming at least one selected of the plurality of driver states with at least one selected different one of the plurality of driver states. In one embodiment, confirming includes comparing the at least one selected of the plurality of driver states with the at least one selected different one of the plurality of driver states. In  FIG. 58 , the first driver state DS 1  is confirmed with the second driver state DS 2 . In another embodiment, the outcome of the confirmation of the first driver state DS 1  and the second driver state DS 2 . is confirmed with the third driver state DS 3 . For example, if the first driver state is a physiological driver state indicating a drowsy driver (i.e., YES; 1) and the second driver state is a behavioral driver state indicating a drowsy driver (i.e., YES; 1), then the outcome the confirmation of the first driver state and the second driver state indicates a drowsy driver state (i.e., YES; 1). The outcome can be compared to the third driver state. If the third driver state is a vehicular-sensed driver state and indicates a drowsy driver (i.e., YES; 1), then at step  5814 , the combined driver state can indicate a drowsy driver. However, if the third driver state is a vehicular-sensed driver state and indicates a non-drowsy driver (i.e., NO; 0), then at step  5814 , the combined driver state can indicate a non-drowsy driver. 
     In another embodiment, determining the combined driver state can include aggregating, calculating an average, or calculating a weighted average of the first driver state, the second driver state, and the third driver state. It is understood that steps  5812  and  5814  could be processed using the logic gates of  FIGS. 49, 50, and 51 . It is also understood that the method of  FIG. 58  can apply to a state or a level of state. For example, determining a driver state, a driver state level, a combined driver state, and a combined driver state level. It should also be understood that any of the embodiments described above for determining a combined driver state can apply to a state, a level of state, or a state index. In other words, a combined driver state index could be found using the methods described above. 
     In some embodiments, the driver state confirmation processes described above can include assigning a priority level to the driver states and confirming the driver states in an order based on the priority level. The priority level can be based on the type of driver state, the driver state level, the type of monitoring information the driver state is based on, the quality of the monitoring information, among others. In this way, the driver state confirmation process can be controlled and provide accurate confirmation results. Referring now to  FIG. 59 , an embodiment of a method of a process for controlling one or more vehicle systems in a motor vehicle with confirming one or more driver states based on priority levels to determine a combined driver state is shown. 
     In the embodiment of  FIG. 59 , at step  5902  the method includes receiving monitoring information. At step  5904 , the method includes determining a plurality of driver states. At step  5906 , the method includes assigning a priority level to each driver state determined at step  5904 . The priority level can be based on the type of driver state, the driver state level, the type of monitoring information the driver state is based on, the quality of the monitoring information, among others. The priority level indicates an order for confirming the driver states. As an illustrative example, a first driver state DS 1  can be assigned a priority level of 4, a second driver state DS 2  can be assigned a priority level of 1, a third driver state DS 3  can be assigned a priority level of 2 and a fourth driver state DS 4  can be assigned a priority level of 3. In this example, the driver states can be confirmed with one another, at step  5908 , in order of the priority level, for example, the second driver state DS 2 , the third driver state DS 3 , the first driver state DS 1  and the fourth driver state DS 4 , where a priority level of 1 is the highest priority level. 
     As another illustrative example, the priority level can be based on the type of monitoring information used to determine each driver state. For example, in one embodiment, assigning a priority level to each driver state at step  5906  is based on the type of monitoring information, in the following order from highest to lowest priority level: physiological monitoring information, behavioral monitoring information and vehicular monitoring information. Further, priority levels can be assigned based on the characteristic used to determine the monitoring information. For example, physiological information can be assigned a priority level in the following order from highest to lowest: heart monitoring information, eye movement information, and head movement information. In both of these examples, the priority level is based on the type of information and the type of characteristic wherein an internal characteristic receives a higher priority level and an external characteristic. 
     In another embodiment, the priority level can be based on the quality of the monitoring information used to determine each driver state. For example, the signals indicating a measurement of the mentoring information can be analyzed to determine the quality of the signals. Monitoring information with a high quality signal (e.g., no/less noise) can be assigned a higher priority level than monitoring information with a low quality signal (e.g., high noise). The methods for selectively receiving output from sensors and processing the output as described in in U.S. Pat. No. 9,398,875, entitled A System and Method for Biological Signal Analysis, filed on Nov. 7, 2013, which is incorporated by reference in its entirety herein, discussed above, can be used to assign priority levels to monitoring information based on the quality of the monitoring information. 
     Similarly, in some embodiments, at step  5906 , the method can include selectively confirming driver states based on the priority level. For example, a driver state with a low priority level can be discarded and not used in the confirmation process. As an illustrative example, driver states based on monitoring information having a high quality signal (e.g., no/less noise) can be assigned a higher priority level than driver states based on monitoring information with a low quality signal (e.g., high noise). In this example, driver states with a low priority level (e.g., indicating low quality monitoring information) are selectively discarded and not used during the confirmation process. 
     It is understood that steps  5908  and  5910  could be processed using the logic gates of  FIGS. 49, 50, and 51 . It is also understood that the method of  FIG. 59  can apply to a state or a level of state. For example, determining a driver state, a driver state level, a combined driver state, and a combined driver state level. It should also be understood that any of the embodiments described above for determining a combined driver state can apply to a state, a level of state, or a state index. In other words, a combined driver state index could be found using the methods described above. 
     4. Network System for Determining a Combined Driver State 
     The components of the systems and methods described above for combining and confirming one or more driver states can be organized into different architectures for different embodiments. Referring now to  FIG. 60 , a diagram of network system  6000  for controlling one or more vehicle systems including confirming and combining one or more driver states according to an exemplary embodiment is shown. The system  6000  can in some embodiments, be an artificial neural network for controlling one or more vehicle systems. Additionally, it is understood that the systems and methods described above for combining and confirming one or more driver states can be implemented with the system  6000 . 
     The vehicle systems  126  ( FIG. 1A, 2 ) and/or the monitoring systems  300  ( FIG. 3 ) discussed above provide monitoring information to the system  6000 . The monitoring information can include physiological information  6002 , behavioral information  6004 , and/or vehicle information  6006 . By utilizing physiological information  6002 , behavioral information  6004  and vehicle information  6006 , the network system  6000  is created that determines more than one type of driver state to accurately assess the driver and a current vehicle situation and subsequently control one or more vehicle systems appropriately. As shown in  FIG. 60 , physiological information  6002 , behavioral information  6004  and vehicle information  6006  can be used to determine an input node, namely, determine a first driver state  6008 , determine a second driver state  6010  and determine a third driver state  6012 . It is appreciated, and as will be discussed in further detail herein, other numbers of driver states, for example, two, three, four, five, etc., can be used. 
     In one exemplary embodiment, the first driver state  6008  is based on physiological information  6002 , for example, heart rate measured by a heart rate sensor (e.g., a bio-monitoring sensor  180 ) positioned in the vehicle seat  168  of the motor vehicle  100  ( FIG. 1A ). The second driver state  6010  can be based on behavioral information  6004 , for example, pupil dilation measured by an optical sensor, for example, the optical sensing device  162  in the motor vehicle  100  ( FIG. 1 ). The third driver state  6012  can be based on vehicle information  6006 , for example, steering information from the electronic power steering system  132  ( FIGS. 1 and 2 ). The above types of exemplary driver states are illustrative in nature and it is appreciated that other types of physiological information  6002 , behavioral information  6004 , and vehicle information  6006  can be used to determine one or more of the driver states. 
     In the embodiment of  FIG. 60 , as shown, each input node (e.g., driver state) can include a threshold related to said node. For example, the first driver state  6008  can have a first driver state threshold that is related to the first driver state. Thus, for example, if the first driver state  6008  is based on a heart rate numeric value, the first driver state threshold may be a numeric value indicating a high heart rate. 
     As discussed above, the thresholds can be pre-determined for each driver state and/or the information the driver state is based on. In other embodiments, the threshold is also determined based on the particular driver and adjusted based on the driver. For example, the response system  188  can use a machine learning method to determine normative baseline data for a particular driver. Any machine learning method or pattern recognition algorithm could be used. For example, the response system  188  can determine that the normative baseline heart rate of a particular driver is higher than an average adult heart rate. Accordingly, the response system  188  can dynamically modify the threshold related to heart rate for the driver based on the driver normative baseline heart rate. As discussed above, the threshold can be customized based on the driver. In some embodiments, systems and methods of biometric identification ( FIGS. 22-23 ) can be used to identify the driver and store normative data and/or past and current thresholds associated with the driver. 
     As discussed above, the threshold can be dynamically modified or pre-determined based on other monitoring information. As an illustrated example, a threshold related to a driver state based on perspiration rate information, can be adjusted based on monitoring information from the vehicle systems  126  indicating the internal temperature of the vehicle is hot. If the internal temperature of the vehicle is hot, the driver can naturally have a higher perspiration rate, which may not be an accurate indication of a driver state. Accordingly, the threshold related to a driver state based on perspiration rate information can be dynamically modified to account of the internal temperature of the vehicle. Other examples of thresholds and modifying thresholds are discussed in Section III (B) (2). 
     In one embodiment, upon determining one or more driver states at the input nodes, the input nodes are activated thereby triggering the output nodes to determine a combined driver state index based on the one or more driver states. For example, the first driver state  6008 , the second driver state  6010  and/or the third driver state  6012  are combined into a combine driver state index. In some cases, the one or more driver states are first compared to the associated threshold before determining a combine driver state index. Upon meeting said threshold, the one or more driver states are combined into a combined driver state index at the output nodes. 
     In another embodiment, upon meeting said threshold, the input node is activated and subsequently triggers activation at a confirmation node. This allows at least one selected of the plurality of driver states to be confirmed with at least one selected different one of the plurality driver states. Thus, for example, confirmation node  6014  triggers confirmation of the first driver state  6008  with the second driver state  6010  and/or the third driver state  6012 . More specifically, in one embodiment, upon meeting the first driver state threshold, the second driver state  6010  is compared to the second driver state threshold. Upon meeting the second driver state threshold, in one embodiment the third driver state  6012  is compared to the third driver state threshold. In other embodiments, upon meeting the first driver state threshold, the third driver state  6012  is compared to the second driver state threshold, and so forth. It is appreciated that other combinations of confirmation can be implemented. 
     Similarly, confirmation node  6016  triggers confirmation of the second driver state  6010  with the first driver state  6008  and/or the third driver state  6012 . Confirmation node  6018  triggers confirmation of the third driver state  6012  with the first driver state  6008  and/or the second driver state  6010 . Accordingly, by confirming more than one driver state based on more than one type of monitoring information, accurate driver state estimation is possible. 
     Moreover, the confirmed driver states can be forwarded to an output node. Specifically, a combined driver state index is determined based on the confirmed driver states and the combined driver state index is output to control one or more vehicle systems. As discussed above, the combined driver state index can be determined in various ways. For example, by aggregation, averaging, or weighted averaging. 
     As an illustrative example, at confirmation node  6014 , the first driver state  6008  was confirmed with the second driver state  6010  and the third driver state  6012 . Accordingly, the combined driver state index at output node  6020  can be determined as an aggregate of the first driver state  6008 , the second driver state  6010  and the third driver state  6012 . If for example, the first driver state  6008  was confirmed with the second driver state  6010 , the combined driver state index at output node  6020  can be determined as an aggregate of the first driver state  6008  and the second driver state  6010 . 
     Referring now to  FIG. 61  a schematic flow chart of a detailed process of controlling vehicle systems according to a combined drive state index according to the network  6000  of  FIG. 60  is shown. As shown in  FIG. 61 , monitoring information is received and includes receiving physiological information at step  6102 , receiving behavioral information at step  6104 , and receiving vehicle information at step  6106 . Specifically, in one embodiment, the monitoring information is at least one of physiological information, behavioral information or vehicle information. The physiological information received at step  6102  is input used to determine a first driver state at step  6108 . The behavioral information received at step  6104  is input used to determine a second driver state at step  6110 . The vehicle system information received at step  6106  is used to determine a third driver state at step  6112 . It is appreciated that other combinations of information and driver states can be implemented. For example, behavioral information could be used to determine a first driver state and physiological information could be used to determine a second driver state, and so on. It is appreciated that other combinations of information and driver states can be implemented. For example, behavioral information could be used to determine a first driver state and physiological information could be used to determine a second driver state, and so on. 
     It is appreciated that any number of driver states can be determined. In one embodiment, the first driver state is one of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state, and the second driver state is another of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. The third driver state can be a further one of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. By using different types of monitoring information to determine different driver states, multi-modal driver state confirmation is possible, as will be described herein. Further, it is appreciated that the plurality of driver states can be determined in various ways as discussed throughout the specification. For example, the driver state could be a driver state index. The driver state can be determined by the response system  188 , vehicle systems  126  and/or the monitoring systems described herein. 
     As discussed above, in some embodiments, determining the combined driver state index further includes comparing at least one of the plurality of driver states to a threshold, and upon determining the at least one of the plurality of driver states meets the threshold, determining the combined driver state index based on the least one of the plurality of driver states. Thus, for example, upon determining that a first driver state meets a first driver state threshold and a second driver state meets a second driver state threshold, the combined driver state index is determined based on the first driver state and the second driver state. In another embodiment, as discussed above, determining the combined driver state index further includes confirming at least one selected of the plurality of driver states with at least one selected different one of the plurality of driver states and determining a combined driver state index based on the at least one selected of the plurality of driver states and the at least one selected different one of the plurality of driver states. 
     As illustrated in the example shown in  FIG. 61 , at step  6114 , it is determined if the first driver state meets the first driver state threshold. Upon determining that the first driver state meets the first driver threshold, first driver state is confirmed with at least one other driver state at step  6122 . For example, in one embodiment, the first driver state is confirmed with the second driver state, for example, at step  6116 . In this embodiment, the first driver state is one of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state, and the second driver state is another of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. Accordingly, the state of the driver is assessed by confirming driver states based on different monitoring information types. 
     As mentioned above, confirming the first driver state with the second driver state can further include comparing the second driver state to a second driver state threshold at step  6116 . Upon determining the second driver state meets the second driver state threshold, the method can include determining the combined driver state index based on the first driver state and the second driver state at step  6128 . 
     In another embodiment, the step of confirming includes confirming the first driver state with at least one of the second driver state or the third driver state and determining the combined driver state index based on the first driver state and the at least one of the second driver state or the third driver state. For example, upon determining that the first driver state meets the first driver state threshold at step  6114 , the first driver state is confirmed at step  6122  with the third driver state at step  6118 . Upon determining that the third driver state meets the third driver state threshold, a combined driver state index is determined at step  6128  based on the first driver state and the third driver state. 
     It will be appreciated that in some embodiments, all three driver states are confirmed (e.g., by determining if each driver state meets its respective driver state threshold) and the combined driver state index is based on all three driver states. In this example, the three driver states are each one of a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. Further, as discussed above, the thresholds discussed in  FIG. 61  can be pre-determined and/or dynamically based on the driver states, the information used to determine the driver state (e.g., heart information, head pose information), the type of information and/or driver state (e.g., physiological, behavioral, vehicular), other types of monitoring information, and/or the identity of the driver. 
     Determining which driver state triggers the confirmation process and which driver states are confirmed in response can be based on an artificial neural network, for example, the network  6000  of  FIG. 60 . For example, determining which driver state triggers the confirmation process and which driver states are confirmed can be predetermined based on the type of monitoring information, type of driver distraction and/or dynamically selected. 
     For example, in one embodiment, to determine if a driver is drowsy, the driver states could be based on predetermined monitoring information indicating a drowsy driver, for example, heart rate from a heart rate sensor placed on the driver&#39;s seat to determine a first driver state, eye movement information from an optical sensor to determine a second driver state, and steering information from the steering wheel to determine a third driver state. In other embodiments, the driver states could be dynamically selected based on the quality of the monitoring information. For example, if it is determined that the heart rate information is weak (e.g., using signal analysis), a driver state based on a different type of physiological information could be determined. 
     V. Determine One or More Vehicular States 
     In addition to determining one or more driver states, in some embodiments, the systems and methods for responding to driver state can also include determining one or more vehicular states and modifying the control of one or more vehicle systems based on the driver state and/or the vehicular state, or any combination of one or more of said states. A vehicular state describes a state of the motor vehicle  100  and/or the vehicle systems  126 . In particular, in some embodiments, the vehicular state describes a state of the motor vehicle  100  based on external information about the vehicle environment. In one embodiment, the vehicular state can describe a risk surrounding the vehicle environment. For example, as discussed below in Section B, a vehicular state can be characterized as a hazard, a hazard level, a risk level, among others. 
     A vehicular state is based on vehicle information from vehicular monitoring systems and sensors, as discussed above in Section III (B) (1). Specifically, vehicle information for determining a vehicular state includes information related to the motor vehicle  100  of  FIG. 1A  and/or the vehicle systems  126 , including those vehicle systems listed in  FIG. 2 . As an illustrative example, vehicle information for determining a vehicular state can include information about objects, pedestrians, hazards, and/or other vehicles in the environment of the vehicle, for example from visual devices  140 , the collision warning system  218 , the automatic cruise control system  216 , the lane departure warning system  222 , the blind spot indicator system  224 , the lane keep assist system  226 , the lane monitoring system  228 , among others. Vehicle information for determining a vehicular state can include traffic information, weather information, road speed limit information, navigation information, for example, from, visual devices  140 , the climate control system  234 , and the navigation system  230 , among others. 
     In another embodiment, the vehicular state can be based on a failure detection system. For example, the failure detection system  244  can detect a level of failure and/or a fail-safe state of the motor vehicle  100  and/or vehicle systems  126 . Vehicle information for determining a vehicular state can also include other information corresponding to the motor vehicle  100  and/or the vehicle systems  126  describing the state of the motor vehicle  100  and/or the external environment of the motor vehicle  100 . 
     Similar to the driver state discussed above, it is understood that the vehicular state can also be quantified as a level, a numeric value or a numeric value associated with a level. In some embodiments, discussed above, the vehicular state can be characterized as a hazard, a type of hazard, a hazard level, and/or a risk level. In one embodiment, controlling one or more vehicle systems is based on one or more driver states and one or more vehicular states. Referring now to  FIG. 62 , a method is illustrated of an embodiment of a process for controlling one or more vehicle systems in a motor vehicle similar to  FIG. 45 , however, the process is based on a combined driver state level and a vehicular state. 
     At step  6202 , the method includes receiving monitoring information. In step  6204 , the response system  188  can determine a plurality of driver state levels. In one embodiment, each of the plurality of driver state levels is based on at least one of physiological information, behavioral information, and vehicle information. Thus, the plurality of driver state levels are at least one of a physiological driver state level, a behavioral driver state level or a vehicular-sensed driver state level. Said differently, the physiological driver state level is based on physiological information, the behavioral driver state level is based on behavioral information, and the vehicular-sensed driver state level is based on vehicle information. 
     In step  6206 , the response system  188  can determine a combined driver state level based on the plurality of driver state levels of step  6204 . In another embodiment, in step  6206 , the response system  188  can determine a combined driver state index based on the plurality of driver state indices of step  6204 . As will be discussed above, the combined driver state can be determined in various ways. 
     In step  6208 , in some embodiments, the response system  188  can determine whether or not the driver state is true based on the combined driver state level and/or index. For example, whether or not the driver is vigilant, drowsy, inattentive, distracted, intoxicated, among others. If the driver state is not true (i.e., NO), the response system  188  can proceed back to step  6202  to receive additional monitoring information. If, however, the driver state is true (i.e., YES), the response system  188  can proceed to step  6210 . 
     At step  6210 , the response system  188  can determine a vehicular state. As discussed above, the vehicular state can be based on vehicle information. In another embodiment, the response system  188  can determine more than one vehicular state. In one embodiment, the process proceeds to step  6212 . In another embodiment, the response system  188  proceeds to step  6214 , where the response system  188  compares the driver state level to the vehicular state level. In another embodiment, instead of comparing the driver state level to the vehicular state level, the response system  188  compares the vehicular state level to a predetermined threshold. The predetermined threshold can be based on the vehicular state and/or the vehicle information used to determine the vehicular state. If the outcome of step  6214  is YES, the response system can proceed to step  6212 . If the outcome of step  6214  is NO, the response system  188  can proceed back to step  6202  to receive additional monitoring information. 
     In step  6212 , the response system  188  can automatically modify the control of one or more vehicle systems, including any of the vehicle systems discussed above, based on the driver state level and the vehicular state. By automatically modifying the control of one or more vehicle systems, the response system  188  can help to avoid various hazardous situations that can be caused by, for example, a drowsy driver. 
     It is understood that the vehicular state and/or a vehicular state level can be determined before or after other steps shown in  FIG. 62 . For example, in some embodiments, the vehicular state can be determined at step  6204 . Further, in other embodiments, the vehicular state can be used to determine a combined driver state level, for example, as shown in  FIGS. 49, 50 and 51 . It is appreciated that the logic gates, equations and methods described in Section IV can also be implemented with a fourth state, the vehicular state. 
     VI. Modify Control of Vehicle Systems 
     As discussed above, in some embodiments, modifying control of one or more vehicle systems can be based on a driver state, a level of a driver state, a driver state index, a combined driver state, a level of a combined driver state, or a combined driver state index. In a further embodiment, modifying control of one or more vehicle systems can be based on a driver state, a level of a driver state, a driver state index, a combined driver state, a level of a combined driver state, the combined driver state index, and/or a vehicular state. Accordingly, modifying the control of the one or more vehicle systems can include changing at least one operating parameter of the one or more vehicle systems based on a driver state, a level of a driver state, a driver state index, a combined driver state, a level of a combined driver state, the combined driver state index and/or a vehicular state. The operating parameter can be used to determine activation of a particular function of the one or more vehicle systems. 
     In some embodiments, modifying control of one or more vehicle systems can include operating one or more vehicle systems based on a driver state, a level of a driver state, a driver state index, a combined driver state, a level of a combined driver state, the combined driver state index, and/or a vehicular state. A control parameter can be used to operate the one or more vehicle systems. In a one embodiment, the control parameter is determined based on a driver state, a level of a driver state, a driver state index, a combined driver state, a level of a combined driver state, the combined driver state index, and/or a vehicular state. 
     Accordingly, the above described systems and methods provide multi-modal monitoring and authentication of driver states. Utilizing such a system, provides a reliable and robust driver monitoring system that verifies driver states, provides a driver state (e.g., a combined driver state) based on multiple driver states using different types of monitoring systems (e.g., multi-modal inputs) and modifies one or more vehicle systems based on the driver state. In this way, behaviors and risks can be assessed in multiple modes and modification of vehicle systems can be controlled accurately. Exemplary types of operation, control, and modification of one or more vehicle systems will now be described in detail. It is appreciated that the following examples are exemplary in nature and other examples or combinations can be implemented. 
     A. Exemplary Operational Response of a Vehicle System to Driver State 
     In one embodiment, a response system can include provisions for controlling one or more vehicle systems to help wake a drowsy driver based on the detected driver state. For example, a response system could control various systems to stimulate a driver in some way (visually, orally, or through movement, for example). A response system could also change ambient conditions in a motor vehicle to help wake the driver and thereby increase the driver&#39;s alertness. 
       FIGS. 63 and 64  illustrate a schematic view of a method of waking a driver by modifying the control of an electronic power steering system.  FIGS. 63 and 64  will be described with reference to  FIGS. 1A, 1B, 2, and 3 . Referring to  FIG. 63 , the driver  102  (e.g., of the motor vehicle  100 ) is drowsy. The response system  188  can detect that the driver  102  is drowsy using any of the detection methods mentioned previously or through any other detection methods. During normal operation, the EPS system  132  functions to assist a driver in turning a touch steering wheel  134 . However, in some situations, it can be beneficial to reduce this assistance. For example, as seen in  FIG. 64 , by decreasing the power steering assistance, the driver  102  must put more effort into turning the touch steering wheel  134 . This can have the effect of waking up the driver  102 , since the driver  102  must now apply a greater force to turn the touch steering wheel  134 . 
       FIG. 65  illustrates an embodiment of a process for controlling power steering assistance according to the detected level of drowsiness for a driver. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  6502 , the response system  188  can receive drowsiness information. In some cases, the drowsiness information includes whether a driver is in a normal state or a drowsy state. Moreover, in some cases, the drowsiness information could include a value indicating the level of drowsiness, for example on a scale of 1 to 10, with 1 being the least drowsy and 10 being the drowsiest. 
     In step  6504 , the response system  188  determines if the driver is drowsy based on the drowsiness information. If the driver is not drowsy, the response system  188  returns back to step  6502 . If the driver is drowsy, the response system  188  proceeds to step  1506 . In step  6506 , steering wheel information can be received. In some cases, the steering wheel information can be received from an EPS system  132 . In other cases, the steering wheel information can be received from a steering angle sensor or a steering torque sensor directly. 
     In step  6508 , the response system  188  can determine if the driver is turning the steering wheel. If not, the response system  188  returns to step  6502 . If the driver is turning the steering wheel, the response system  188  proceeds to step  6510  where the power steering assistance is decreased. It will be understood that in some embodiments, the response system  188  cannot check to see if the wheel is being turned before decreasing power steering assistance. 
       FIG. 66  illustrates an embodiment of a detailed process for controlling power steering assistance to a driver according to a driver state index. In step  6602 , the response system  188  can receive steering information. The steering information can include any type of information including steering angle, steering torque, rotational speed, motor speed as well as any other steering information related to a steering system and/or a power steering assistance system. In step  6604 , the response system  188  can provide power steering assistance to a driver. In some cases, the response system  188  provides power steering assistance in response to a driver request (for example, when a driver turns on a power steering function). In other cases, the response system  188  automatically provides power steering assistance according to vehicle conditions or other information. 
     In step  6606 , the response system  188  can determine the driver state index of a driver using any of the methods discussed above for determining a driver state index. Next, in step  6608 , the response system  188  can set a power steering status corresponding to the amount of steering assistance provided by the electronic power steering system. For example, in some cases, the power steering status is associated with two states, including a “low” state and a “standard” state. In the “standard” state, power steering assistance is applied at a predetermined level corresponding to an amount of power steering assistance that improves drivability and helps increase the driving comfort of the user. In the “low” state, less steering assistance is provided, which requires increased steering effort by a driver. As indicated by look-up table  6610 , the power steering status can be selected according to the driver state index. For example, if the driver state index is 1 or 2 (corresponding to no drowsiness or slight drowsiness), the power steering status is set to the standard state. If, however, the driver state index is 3 or 4 (corresponding to a drowsy condition of the driver), the power steering status is set to the low state. It will be understood that look-up table  6610  is only intended to be exemplary and in other embodiments, the relationship between driver state index and power steering status can vary in any manner. 
     Once the power steering status is set in step  6608 , the response system  188  proceeds to step  6612 . In step  1528 , the response system  188  determines if the power steering status is set to low. If not, the response system  188  can return to step  6602  and continue operating power steering assistance at the current level. However, if the response system  188  determines that the power steering status is set to low, the response system  188  can proceed to step  6614 . In step  6614 , the response system  188  can ramp down power steering assistance. For example, if the power steering assistance is supplying a predetermined amount of torque assistance, the power steering assistance can be varied to reduce the assisting torque. This requires the driver to increase steering effort. For a drowsy driver, the increased effort required to turn the steering wheel can help increase his or her alertness and improve vehicle handling. 
     In some cases, during step  6616 , the response system  188  can provide a warning to the driver of the decreased power steering assistance. For example, in some cases, a dashboard light reading “power steering off” or “power steering decreased” could be turned on. In other cases, a navigation screen or other display screen associated with the vehicle could display a message indicating the decreased power steering assistance. In still other cases, an audible or haptic indicator could be used to alert the driver. This helps to inform the driver of the change in power steering assistance so the driver does not become concerned of a power steering failure. 
       FIGS. 67 and 68  illustrate schematic views of a method of helping to wake a drowsy driver by automatically modifying the operation of a climate control system.  FIGS. 67 and 68  will be described with reference to  FIGS. 1A, 1B, 2, and 3 . Referring to  FIG. 67 , a climate control system  234  has been set to maintain a temperature of 75 degrees Fahrenheit inside the cabin of the motor vehicle  100  by the driver  102 . This is indicated on display screen  6702 . As the response system  188  detects that the driver  102  is becoming drowsy, the response system  188  can automatically change the temperature of the climate control system  234 . As seen in  FIG. 68 , the response system  188  automatically adjusts the temperature to 60 degrees Fahrenheit. As the temperature inside the motor vehicle  100  cools down, the driver  102  can become less drowsy. This helps the driver  102  to be more alert while driving. In other embodiments, the temperature can be increased in order to make the driver more alert. 
       FIG. 69  illustrates an embodiment of a process for helping to wake a driver by controlling the temperature in a vehicle. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  6902 , the response system  188  may receive drowsiness information. In step  6904 , the response system  188  determines if the driver is drowsy. If the driver is not drowsy, the response system  188  proceeds back to step  6902 . If the driver is drowsy, the response system  188  proceeds to step  6906 . In step  6906 , the response system  188  automatically adjusts the cabin temperature. In some cases, the response system  188  can lower the cabin temperature by engaging a fan or air-conditioner. However, in some other cases, the response system  188  could increase the cabin temperature using a fan or heater. Moreover, it will be understood that the embodiments are not limited to changing temperature and in other embodiments other aspects of the in-cabin climate could be changed, including airflow, humidity, pressure, or other ambient conditions. For example, in some cases, a response system could automatically increase the airflow into the cabin, which can stimulate the driver and help reduce drowsiness. 
       FIGS. 70 and 71  illustrate schematic views of methods of alerting a drowsy driver using visual, audible, and tactile feedback for a driver.  FIGS. 70 and 71  will be described with reference to  FIGS. 1A, 1B, 2, and 3 . Referring to  FIG. 70 , the driver  102  is drowsy as the motor vehicle  100  is moving. Once the response system  188  detects this drowsy state, the response system  188  can activate one or more feedback mechanisms to help wake the driver  102 . Referring to  FIG. 71 , three different methods of waking a driver are shown. In particular, the response system  188  can control one or more of the tactile devices  148 . Examples of tactile devices include vibrating devices (such as a vibrating seat or massaging seat) or devices whose surface properties can be modified (for example, by heating or cooling or by adjusting the rigidity of a surface). In one embodiment, the response system  188  can operate the vehicle seat  168  to shake or vibrate. This can have the effect of waking the driver  102 . In other cases, steering wheel  134  could be made to vibrate or shake. In addition, in some cases, the response system  188  could activate one or more lights or other visual indicators. For example, in one embodiment, a warning can be displayed on display screen  7002 . In one example, the warning can be “Wake!” and can include a brightly lit screen to catch the driver&#39;s attention. In other cases, overhead lights or other visual indicators could be turned on to help wake the driver. In some embodiments, the response system  188  could generate various sounds through speakers  7004 . For example, in some cases, the response system  188  could activate a radio, CD player, MP3 player or other audio device to play music or other sounds through the speakers  7004 . In other cases, the response system  188  could play various recordings stored in memory, such as voices that tell a driver to wake. 
       FIG. 72  illustrates an embodiment of a process for waking up a driver using various visual, audible, and tactile stimuli. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  7202 , the response system  188  can receive drowsiness information. In step  7204 , the response system  188  determines if the driver is drowsy. If the driver is not drowsy, the response system  188  returns to step  7202 . Otherwise, the response system  188  proceeds to step  7206 . In step  7206 , the response system  188  can provide tactile stimuli to the driver. For example, the response system  188  could control a seat or other portion of the motor vehicle  100  to shake and/or vibrate (for example, a steering wheel). In other cases, the response system  188  could vary the rigidity of a seat or other surface in the motor vehicle  100 . 
     In step  7208 , the response system  188  can turn on one or more lights or indicators. The lights could be any lights associated with the motor vehicle  100  including dashboard lights, roof lights or any other lights. In some cases, the response system  188  can provide a brightly lit message or background on a display screen, such as a navigation system display screen or climate control display screen. In step  7210 , the response system  188  can generate various sounds using speakers in the motor vehicle  100 . The sounds could be spoken words, music, alarms, or any other kinds of sounds. Moreover, the volume level of the sounds could be chosen to ensure the driver is put in an alert state by the sounds, but not so loud as to cause great discomfort to the driver. 
     A response system can include provisions for controlling a seat belt system to help wake a driver. In some cases, a response system can control an electronic pretensioning system for a seat belt to provide a warning pulse to a driver.  FIGS. 73 and 74  illustrate schematic views of an embodiment of a response system controlling an electronic pretensioning system for a seat belt.  FIGS. 73 and 74  will be described with reference to  FIGS. 1A, 1B, 2, and 3 . Referring to  FIGS. 73 and 74 , as the driver  102  begins to feel drowsy, the response system  188  can automatically control EPT system  236  to provide a warning pulse to the driver  102 . In particular, a seat belt  7302  can be initially loose as seen in  FIG. 73 , but as the driver  102  gets drowsy, the seat belt  7302  is pulled taut against the driver  102  for a moment as seen in  FIG. 74 . This momentary tightening serves as a warning pulse that helps to wake the driver  102 . 
       FIG. 75  illustrates an embodiment of a process for controlling the EPT system  236 . During step  7502 , the response system  188  receives drowsiness information. During step  7504 , the response system  188  determines if the driver is drowsy. If the driver is not drowsy, the response system  188  returns to step  7502 . If the driver is drowsy, the response system  188  proceeds to step  7506  where a warning pulse is sent. In particular, the seat belt can be tightened to help wake or alert the driver. 
     In addition to controlling various vehicle systems to stimulate a driver, a motor vehicle can also include other provisions for controlling various vehicle systems (e.g., the vehicle systems in  FIG. 2 ) based on the driver state. The methods and systems for controlling various vehicle systems discussed herein are exemplary and it is understood that other modifications to other vehicle systems are contemplated. For example, a motor vehicle can include provisions for adjusting various brake control systems according to the behavior of a driver. For example, a response system can modify the control of antilock brakes, brake assist, brake prefill, as well as other braking systems when a driver is drowsy. This arrangement helps to increase the effectiveness of the braking system in hazardous driving situations that can result when a driver is drowsy. 
       FIGS. 76 and 77  illustrate schematic views of the operation of an antilock braking system.  FIGS. 76 and 77  will be described with reference to  FIGS. 1A, 1B, 2, and 3 . Referring to  FIG. 76  when a driver  102  is fully awake, the ABS system  204  can be associated with a first stopping distance  7602 . In particular, for a particular initial speed  7604 , as a driver  102  depresses brake pedal  7606 , the motor vehicle  100  can travel to the first stopping distance  7602  before coming to a complete stop. Thus, the first stopping distance  7602  can be the result of various operating parameters of the ABS system  204 . 
     Referring now to  FIG. 77 , as the driver  102  becomes drowsy, the response system  188  can modify the control of the ABS system  204 . In particular, in some cases, one or more operating parameters of the ABS system  204  can be changed to decrease the stopping distance. In this case shown in  FIG. 77 , as the driver  102  depresses a brake pedal  7606 , the motor vehicle  100  can travel to a second stopping distance  7608  before coming to a complete stop. In one embodiment, the second stopping distance  7608  can be substantially shorter than the first stopping distance  7602 . In other words, the stopping distance can be decreased when the driver  102  is drowsy. Since a drowsy driver can engage the brake pedal later due to a reduced awareness, the ability of the response system  188  to decrease the stopping distance can help compensate for the reduced reaction time of the driver. In another embodiment, if the vehicle is on a slippery surface the reduction in stopping cannot occur and instead tactile feedback can be applied through the brake pedal. 
       FIG. 78  illustrates an embodiment of a process for modifying the control of an antilock braking system according to the behavior of a driver. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1   b  through  3 , including the response system  188 . 
     In step  7802 , the response system  188  can receive drowsiness information. In step  27804 , the response system  188  can determine if the driver is drowsy. If the driver is not drowsy, the response system  188  returns to step  7802 . If the driver is drowsy, the response system  188  can proceed to step  7806 . In step  7806 , the response system  188  can determine the current stopping distance. The current stopping distance can be a function of the current vehicle speed, as well as other operating parameters including various parameters associated with the brake system. In step  7808 , the response system  188  can automatically decrease the stopping distance. This can be achieved by modifying one or more operating parameters of the ABS system  204 . For example, the brake line pressure can be modified by controlling various valves, pumps, and/or motors within the ABS system  204 . In a further embodiment, the idle stop function linked to the engine  104  and the braking systems can be modified by turning the idle stop function OFF when the driver is drowsy. 
     In some embodiments, a response system can automatically prefill one or more brake lines in a motor vehicle in response to driver state.  FIG. 79  illustrates an embodiment of a process for controlling brake lines in a motor vehicle in response to driver state. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  7902 , the response system  188  can receive drowsiness information. In step  7904 , the response system  188  can determine if the driver is drowsy. If the driver is not drowsy, the response system  188  can return to step  7902 . If the driver is drowsy, the response system  188  can automatically prefill the brake lines with brake fluid in step  7906 . For example, the response system  188  can use the automatic brake prefill system  208 . In some cases, this can help increase braking response if a hazardous condition arises while the driver is drowsy. It will be understood that any number of brake lines could be prefilled during step  7906 . Moreover, any provisions known in the art for prefilling brake lines could be used including any pumps, valves, motors or other devices needed to supply brake fluid automatically to brake lines. 
     Some vehicles can be equipped with brake assist systems that help reduce the amount of force a driver must apply to engage the brakes. These systems can be activated for older drivers or any other drivers who can need assistance with braking. In some cases, a response system could utilize the brake assist systems when a driver is drowsy, since a drowsy driver may not be able to apply the necessary force to the brake pedal for stopping a vehicle quickly. 
       FIG. 80  illustrates an embodiment of a method for controlling automatic brake assist in response to driver state. In step  8002 , the response system  188  can receive drowsiness information. In step  8004 , the response system  188  can determine if the driver is drowsy. If the driver is not drowsy, the response system  188  proceeds back to step  8002 . If the driver is drowsy, the response system  188  can determine if the brake assist system  206  is already on in step  8006 . If the brake assist system  206  is already on, the response system  188  can return to step  8002 . If the brake assist system  206  is not currently active, the response system  188  can turn on the brake assist system  206  in step  8008 . This arrangement allows for braking assistance to a drowsy driver, since the driver may not have sufficient ability to supply the necessary braking force in the event that the motor vehicle  100  must be stopped quickly. 
     In some embodiments, a response system could modify the degree of assistance in a brake assist system. For example, a brake assist system can operate under normal conditions with a predetermined activation threshold. The activation threshold can be associated with the rate of change of the master cylinder brake pressure. If the rate of change of the master cylinder brake pressure exceeds the activation threshold, brake assist can be activated. However, when a driver is drowsy, the brake assist system can modify the activation threshold so that brake assist is activated sooner. In some cases, the activation threshold could vary according to the degree of drowsiness. For example, if the driver is only slightly drowsy, the activation threshold can be higher than when the driver is extremely drowsy. 
       FIG. 81  illustrates an embodiment of a detailed process for controlling automatic brake assist in response to driver state. In particular,  FIG. 81  illustrates a method in which brake assist is modified according to the driver state index of the driver. In step  8102 , the response system  188  can receive braking information. Braking information can include information from any sensors and/or vehicle systems. In step  8104 , the response system  188  can determine if a brake pedal is depressed. In some cases, the response system  188  can receive information that a brake switch has been applied to determine if the driver is currently braking. In other cases, any other vehicle information can be monitored to determine if the brakes are being applied. In step  8106 , the response system  188  can measure the rate of brake pressure increase. In other words, the response system  188  determines how fast the brake pressure is increasing, or how “hard” the brake pedal is being depressed. In step  8108 , the response system  188  sets an activation threshold. The activation threshold corresponds to a threshold for the rate of brake pressure increase. Details of this step are discussed in detail below. 
     In step  8110 , the response system  188  determines if the rate of brake pressure increase exceeds the activation threshold. If not, the response system  188  proceeds back to step  8102 . Otherwise, the response system  188  proceeds to step  8112 . In step  8112 , the response system  188  activates a modulator pump and/or valves to automatically increase the brake pressure. In other words, in step  8112 , the response system  188  activates brake assist. This allows for an increase in the amount of braking force applied at the wheels. 
       FIG. 82  illustrates an embodiment of a process of selecting the activation threshold discussed above. In some embodiments, the process shown in  FIG. 82  corresponds to step  8108  of  FIG. 82 . In step  8202 , the response system  188  can receive the brake pressure rate and vehicle speed as well as any other operating information. The brake pressure rate and vehicle speed correspond to current vehicle conditions that can be used for determining an activation threshold under normal operating conditions. In step  8204 , an initial threshold setting can be determined according to the vehicle operating conditions. 
     In order to accommodate changes in brake assist due to drowsiness, the initial threshold setting can be modified according to the state of the driver. In step  8206 , the response system  188  determines the driver state index of the driver using any method discussed above. Next, in step  8208 , the response system  188  determines a brake assist coefficient. As seen in look-up table  8210 , the brake assist coefficient can vary between 0% and 25% according to the driver state index. Moreover, the brake assist coefficient generally increases as the driver state index increases. In step  8212 , the activation threshold is selected according to the initial threshold setting and the brake assist coefficient. If the brake assist coefficient has a value of 0%, the activation threshold is just equal to the initial threshold setting. However, if the brake assist coefficient has a value of 25%, the activation threshold can be modified by up to 25% in order to increase the sensitivity of the brake assist when the driver is drowsy. In some cases, the activation threshold can be increased by up to 25% (or any other amount corresponding to the brake assist coefficient). In other cases, the activation threshold can be decreased by up to 25% (or any other amount corresponding to the brake assist coefficient). 
     A motor vehicle can include provisions for increasing vehicle stability when a driver is drowsy. In some cases, a response system can modify the operation of an electronic stability control system. For example, in some cases, a response system could ensure that a detected yaw rate and a steering yaw rate (the yaw rate estimated from steering information) are very close to one another. This can help enhance steering precision and reduce the likelihood of hazardous driving conditions while the driver is drowsy. 
       FIGS. 83 and 84  are schematic views of an embodiment of the motor vehicle  100  turning around a curve in roadway  8300 .  FIGS. 83 and 84  will be described with reference to  FIGS. 1A, 1B, 2, and 3 . Referring to  FIG. 83 , the driver  102  is wide-awake and turning a steering wheel  134 . Also shown in  FIG. 83  are a driver intended path  8302  and an actual vehicle path  8304 . The driver intended path can be determined from steering wheel information, yaw rate information, lateral g information, as well as other kinds of operating information. The driver intended path represents the ideal path of the vehicle, given the steering input from the driver. However, due to variations in road traction as well as other conditions, the actual vehicle path can vary slightly from the driver intended path. Referring to  FIG. 84 , as the driver  102  gets drowsy, the response system  188  modifies the operation of the electronic stability control system  202 . In particular, the ESC system  202  is modified so that the actual vehicle path  8402  is closer to the driver intended path  8404 . This helps to minimize the difference between the driver intended path and the actual vehicle path when the driver is drowsy, which can help improve driving precision. 
       FIG. 85  illustrates an embodiment of a process for controlling an electronic vehicle stability system according to driver state. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  8502 , the response system  188  can receive drowsiness information. In step  8504 , the response system  188  determines if the driver is drowsy. If the driver is not drowsy, the response system  188  can return to step  8502 . Otherwise, the response system  188  receives yaw rate information in step  8506 . The yaw rate information could be received from a yaw rate sensor in some cases. In step  8508 , the response system  188  receives steering information. This could include, for example, the steering wheel angle received from a steering angle sensor. In step  8510 , the response system  188  determines the steering yaw rate using the steering information. In some cases, additional operating information could be used to determine the steering yaw rate. In step  8512 , the response system  188  can reduce the allowable error between the measured yaw rate and the steering yaw rate. In other words, the response system  188  helps minimize the difference between the driver intended path and the actual vehicle path. 
     In order to reduce the allowable error between the yaw rate and the steering yaw rate, the response system  188  can apply braking to one or more brakes of the motor vehicle  100  in order to maintain the motor vehicle  100  close to the driver intended path. Examples of maintaining a vehicle close to a driver intended path can be found in Ellis et al., U.S. Pat. No. 8,426,257, filed Mar. 17, 2010, the entirety of which is hereby incorporated by reference. 
       FIG. 86  illustrates an embodiment of a process for controlling an electronic stability control system in response to driver state. In particular,  FIG. 86  illustrates an embodiment in which the operation of the electronic stability control system is modified according to the driver state index of the driver. In step  8602 , the response system  188  receives operating information. This information can include any operating information such as yaw rate, wheel speed, steering angles, as well as other information used by an electronic stability control system. In step  8604 , the response system  188  can determine if the vehicle behavior is stable. In particular, in step  8606 , the response system  188  measures the stability error of steering associated with under-steering or over-steering. In some cases, the stability is determined by comparing the actual path of the vehicle with the driver intended path. 
     In step  8608 , the response system  188  sets an activation threshold associated with the electronic stability control system. The activation threshold can be associated with a predetermined stability error. In step  8610 , the response system  188  determines if the stability error exceeds the activation threshold. If not, the response system  188  can return to step  8602 . Otherwise, the response system  188  can proceed to step  8612 . In step  8612 , the response system  188  applies individual wheel brake control in order to increase vehicle stability. In some embodiments, the response system  188  could also control the engine to apply engine braking or modify cylinder operation in order to help stabilize the vehicle. 
     In some cases, in step  8614 , the response system  188  can activate a warning indicator. The warning indicator could be any dashboard light or message displayed on a navigation screen or other video screen. The warning indicator helps to alert a driver that the electronic stability control system has been activated. In some cases, the warning could be an audible warning and/or a haptic warning. 
       FIG. 87  illustrates an embodiment of a process for setting the activation threshold used in the previous method. In step  8702 , the response system  188  receives vehicle operating information. For example, the vehicle operating information can include wheel speed information, road surface conditions (such as curvature, friction coefficients, etc.), vehicle speed, steering angle, yaw rate, as well as other operating information. In step  8704 , the response system  188  determines an initial threshold setting according to the operating information received in step  8702 . In step  8706 , the response system  188  determines the driver state index of the driver. 
     In step  8708 , the response system  188  determines a stability control coefficient. As seen in look-up table  8710 , the stability control coefficient can be determined from the driver state index. In one example, the stability control coefficient ranges from 0% to 25%. Moreover, the stability control coefficient generally increases with the driver state index. For example, if the driver state index is 1, the stability control coefficient is 0%. If the driver state index is 4, the stability control coefficient is 25%. It will be understood that these ranges for the stability control coefficient are only intended to be exemplary and in other cases, the stability control coefficient could vary in any other manner as a function of the driver state index. 
     In step  8712 , the response system  188  can set the activation threshold using the initial threshold setting and the stability control coefficient. For example, if the stability control coefficient has a value of 25%, the activation threshold can be up to 25% larger than the initial threshold setting. In other cases, the activation threshold can be up to 25% smaller than the initial threshold setting. In other words, the activation threshold can be increased or decreased from the initial threshold setting in proportion to the value of the stability control coefficient. This arrangement helps to increase the sensitivity of the electronic stability control system by modifying the activation threshold in proportion to the state of the driver. 
       FIG. 88  illustrates a schematic view of the motor vehicle  100  equipped with a collision warning system  218 . The collision warning system  218  can function to provide warnings about potential collisions to a driver. For purposes of clarity, the term “host vehicle” as used throughout this detailed description and in the claims refers to any vehicle including a response system while the term “target vehicle” refers to any vehicle monitored by, or otherwise in communication with, a host vehicle. In the current embodiment, for example, the motor vehicle  100  can be a host vehicle. In this example, as the motor vehicle  100  approaches an intersection  8800  while a target vehicle  8802  passes through the intersection  8800 , the collision warning system  218  can provide a warning alert  8804  on a display screen  8806 . Further examples of collision warning systems are disclosed in Mochizuki, U.S. Pat. No. 8,558,718, filed Sep. 20, 2010, and Mochizuki et al., U.S. Pat. No. 8,587,418, filed Jul. 28, 2010, the entirety of both being hereby incorporated by reference. 
       FIG. 89  illustrates an embodiment of a process for modifying a collision warning system according to driver state. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  8902 , the response system  188  may receive drowsiness information. In step  8904 , the response system  188  can determine if the driver is drowsy. If the driver is not drowsy, the response system  188  can proceed back to step  8902 . Otherwise, the response system  188  can proceed to step  8906 . In step  8906 , the response system  188  can modify the operation of a collision warning system so that the driver is warned earlier about potential collisions. For example, if the collision warning system was initially set to warn a driver about a potential collision if the distance to the collision point is less than 25 meters, the response system  188  could modify the system to warn the driver if the distance to the collision point is less than 50 meters. 
       FIG. 90  illustrates an embodiment of a process for modifying a collision warning system according to driver state. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  9002 , the collision warning system  218  can retrieve the heading, position, and speed of an approaching vehicle. In some cases, this information could be received from the approaching vehicle through a wireless network, such as a DSRC network. In other cases, this information could be remotely sensed using radar, lidar or other remote sensing devices. 
     In step  9004 , the collision warning system  218  can estimate a vehicle collision point. The vehicle collision point is the location of a potential collision between the motor vehicle  100  and the approaching vehicle, which could be traveling in any direction relative to the motor vehicle  100 . In some cases, in step  9004 , the collision warning system  218  can use information about the position, heading, and speed of the motor vehicle  100  to calculate the vehicle collision point. In some embodiments, this information could be received from a GPS receiver that is in communication with the collision warning system  218  or the response system  188 . In other embodiments, the vehicle speed could be received from a vehicle speed sensor. 
     In step  9006 , the collision warning system  218  can calculate the distance and/or time to the vehicle collision point. In particular, to determine the distance, the collision warning system  218  can calculate the difference between the vehicle collision point and the current location of the motor vehicle  100 . Likewise, to determine the time to the collision warning system  218  could calculate the amount of time it will take to reach the vehicle collision point. 
     In step  9008 , the collision warning system  218  can receive drowsiness information from the response system  188 , or any other system or components. In step  9010 , the collision warning system  218  can determine if the driver is drowsy. If the driver is not drowsy, the collision warning system  218  can proceed to step  9012 , where a first threshold parameter is retrieved. If the driver is drowsy, the collision warning system  218  can proceed to step  9014 , where a second threshold distance is retrieved. The first threshold parameter and the second threshold parameter could be either time thresholds or distance thresholds, according to whether the time to collision or distance to collision was determined during step  9006 . In some cases, where both time and distance to the collision point are used, the first threshold parameter and the second threshold parameter can each comprise both a distance threshold and a time threshold. Moreover, it will be understood that the first threshold parameter and the second threshold parameter can be substantially different thresholds in order to provide a different operating configuration for the collision warning system  218  according to whether the driver is drowsy or not drowsy. Following both step  9012  and  9014 , collision warning system  218  proceeds to step  9016 . In step  9016 , the collision warning system  218  determines if the current distance and/or time to the collision point is less than the threshold parameter selected during the previous step (either the first threshold parameter or the second threshold parameter). 
     The first threshold parameter and the second threshold parameter could have any values. In some cases, the first threshold parameter can be less than the second threshold parameter. In particular, if the driver is drowsy, it can be beneficial to use a lower threshold parameter, since this corresponds to warning a driver earlier about a potential collision. If the current distance or time is less than the threshold distance or time (the threshold parameter), the collision warning system  218  can warn the driver in step  9018 . Otherwise, the collision warning system  218  may not warn the driver in step  9020 . 
     A response system can include provisions for modifying the operation of an automatic cruise control system according to driver state. In some embodiments, a response system can change the headway distance associated with an automatic cruise control system. In some cases, the headway distance is the closest distance a motor vehicle can get to a preceding vehicle. If the automatic cruise control system detects that the motor vehicle is closer than the headway distance, the system can warn the driver and/or automatically slow the vehicle to increase the headway distance. 
       FIGS. 91 and 92  illustrate schematic views of the motor vehicle  100  cruising behind a preceding vehicle  9102 . In this situation, the automatic cruise control system  216  is operating to automatically maintain a predetermined headway distance behind the preceding vehicle  9102 . When the driver  102  is awake, automatic cruise control system  216  uses a first headway distance  9104 , as seen in  FIG. 91 . In other words, the automatic cruise control system  216  automatically prevents the motor vehicle  100  from getting closer than the first headway distance  9104  to the preceding vehicle  9102 . As the driver  102  becomes drowsy, as seen in  FIG. 92 , the response system  188  can modify the operation of the automatic cruise control system  216  so that the automatic cruise control system  216  increases the headway distance to a second headway distance  9106 . The second headway distance  9106  can be substantially larger than the first headway distance  9104 , since the reaction time of the driver  102  can be reduced when the driver  102  is drowsy. 
       FIG. 93  illustrates an embodiment of a method of modifying the control of an automatic cruise control system according to driver state. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  9302 , the response system  188  can receive drowsiness information. In step  9304 , the response system  188  can determine if the driver is drowsy. If the driver is not drowsy, the response system  188  can return to step  9302 . If the driver is drowsy, the response system  188  can proceed to step  9306 . In step  9306 , the response system  188  can determine if automatic cruise control is being used. If not, the response system  188  can return back to step  9302 . If automatic cruise control is being used, the response system  188  can proceed to step  9308 . In step  9308 , the response system  188  can retrieve the current headway distance for automatic cruise control. In step  9310 , the response system  188  can increase the headway distance. With this arrangement, the response system  188  can help increase the distance between the motor vehicle  100  and other vehicles when a driver is drowsy to reduce the chances of a hazardous driving situation while the driver is drowsy. 
       FIG. 94  illustrates an embodiment of a process for controlling automatic cruise control in response to driver state. This embodiment could also apply to normal cruise control systems. In particular,  FIG. 94  illustrates an embodiment of a process where the operation of an automatic cruise control system is varied in response to the driver state index of a driver. In step  9402 , the response system  188  can determine that the automatic cruise control function is turned on. This can occur when a driver selects to turn on cruise control. In step  9404 , the response system  188  can determine the driver state index of the driver using any method discussed above as well as any method known in the art. In step  9406 , the response system  188  can set the automatic cruise control status based on the driver state index of the driver. For example, look-up table  9408  indicates that the automatic cruise control status is set to on for driver state indexes of 1, 2, and 3. Also, the automatic cruise control status is set to off for driver state index of 4. In other embodiments, the automatic cruise control status can be set according to driver state index in any other manner. 
     In step  9410 , the response system  188  determines if the automatic cruise control status is ON. If so, the response system  188  proceeds to step  9412 . Otherwise, if the status is OFF, the response system  188  proceeds to step  9414 . In step  9414 , the response system  188  ramps down control of automatic cruise control. For example, in some cases the response system  188  can slow down the vehicle gradually to a predetermined speed. In step  9416 , the response system  188  can turn off automatic cruise control. In some cases, in step  9418 , the response system  188  can inform the driver that automatic cruise control has been deactivated using a dashboard warning light or message displayed on a screen of some kind. In other cases, the response system  188  could provide an audible warning that automatic cruise control has been deactivated. In still other cases, a haptic warning could be used. 
     If the automatic cruise control status is determined to be on during step  9410 , the response system  188  can set the automatic cruise control distance setting in step  9412 . For example, look-up table  9420  provides one possible configuration for a look-up table relating the driver state index to a distance setting. In this case, a driver state index of 1 corresponds to a first distance, a driver state index of 2 corresponds to a second distance, and a driver state index of 3 corresponds to a third distance. Each distance can have a substantially different value. In some cases, the value of each headway distance can increase as the driver state index increases in order to provide more headway room for drivers who are drowsy or otherwise inattentive. In step  9422 , the response system  188  can operate automatic cruise control using the distance setting determined during step  9412 . 
     A response system can include provisions for automatically reducing a cruising speed in a cruise control system based on driver monitoring information.  FIG. 95  illustrates an embodiment of a method for controlling a cruising speed. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  9502 , the response system  188  can receive drowsiness information. In step  9504 , the response system  188  can determine if the driver is drowsy. If the driver is not drowsy, the response system  188  returns to step  9502 , otherwise the response system  188  proceeds to step  9506 . In step  9506 , the response system  188  determines if cruise control is operating. If not, the response system  188  returns back to step  9502 . If cruise control is operating, the response system  188  determines the current cruising speed in step  9508 . In step  9510 , the response system  188  retrieves a predetermined percentage. The predetermined percentage could have any value between 0% and 100%. In step  9512 , the response system  188  can reduce the cruising speed by the predetermined percentage. For example, if the motor vehicle  100  is cruising at 60 mph and the predetermined percentage is 50%, the cruising speed can be reduced to 30 mph. In other embodiments, the cruising speed could be reduced by a predetermined amount, such as by 20 mph or 30 mph. In still other embodiments, the predetermined percentage could be selected from a range of percentages according to the driver body index. For example, if the driver is only slightly drowsy, the predetermined percentage could be smaller than the percentage used when the driver is very drowsy. Using this arrangement, the response system  188  can automatically reduce the speed of the motor vehicle  100 , since slowing the vehicle can reduce the potential risks posed by a drowsy driver. 
       FIG. 96  illustrates an embodiment of a process for controlling a low speed follow system  212  in response to driver state. In step  9602 , the response system  188  can determine if the low speed follow system is on. “Low speed follow” refers to any system that is used for automatically following a preceding vehicle at low speeds. 
     In step  9604 , the response system  188  can determine the driver state index of the driver. Next, in step  9606 , the response system  188  can set the low speed follow status based on the driver state index of the driver. For example, look-up table  9610  shows an exemplary relationship between driver state index and the low speed follow status. In particular, the low speed follow status varies between an “on” state and an “off” state. For low driver state index (driver state indexes of 1 or 2) the low speed follow status can be set to “ON.” For high driver state index (driver state indexes of 3 or 4) the low speed follow status can be set to “OFF.” It will be understood that the relationship between driver state index and low speed follow status shown here is only exemplary and in other embodiments the relationship could vary in any other manner. 
     In step  9612 , the response system  188  determines if the low speed follow status is ON or OFF. If the low speed follow status is ON, the response system  188  returns to step  9602 . Otherwise, the response system  188  proceeds to step  9614  when the low speed follow status is off. In step  9614 , the response system  188  can ramp down control of the low speed follow function. For example, the low speed follow system  212  can gradually increase the headway distance with the preceding vehicle until the system is shut down in step  9616 . By automatically turning of low speed follow when a driver is drowsy, the response system  188  can help increase driver attention and awareness since the driver must put more effort into driving the vehicle. 
     In some cases, in step  9618 , the response system  188  can inform the driver that low speed follow has been deactivated using a dashboard warning light or message displayed on a screen of some kind. In other cases, the response system  188  could provide an audible warning that low speed follow has been deactivated. 
     A response system can include provisions for modifying the operation of a lane departure warning system  222 , which helps alert a driver if the motor vehicle is unintentionally leaving the current lane. In some cases, a response system could modify when the lane departure warning system  222  alerts a driver. For example, the lane keep departure warning system could warn the driver before the vehicle crosses a lane boundary line, rather than waiting until the vehicle has already crossed the lane boundary line. 
       FIGS. 97 and 98  illustrate schematic views of an embodiment of a method of modifying the operation of a lane departure warning system  222 . The motor vehicle  100  travels on a roadway  9700 . Under circumstances where a driver  102  is fully alert (see  FIG. 97 ), the lane departure warning system  222  can wait until the motor vehicle  100  crosses a lane boundary line  9702  before providing a warning  9704 . However, in circumstances where the driver  102  is drowsy (see  FIG. 98 ), the lane departure warning system  222  can provide the warning  9704  just prior to the moment when the motor vehicle  100  crosses the lane boundary line  9702 . In other words, the lane departure warning system  222  warns the driver  102  earlier when the driver  102  is drowsy. This can help improve the likelihood that the driver  102  stays inside the current lane. 
       FIG. 99  illustrates an embodiment of a process of operating a lane departure warning system  222  in response to driver state. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  9902 , the response system  188  can retrieve drowsiness information. In step  9904 , the response system  188  can determine if the driver is drowsy. If the driver is not drowsy, the response system  188  proceeds back to step  9902 . Otherwise, the response system  188  proceeds to step  9906 . In step  9906 , the response system  188  can modify the operation of lane departure warning system  222  so that the driver is warned earlier about potential lane departures. 
       FIG. 100  illustrates an embodiment of a process for operating a lane departure warning system  222  in response to driver state. In particular,  FIG. 100  illustrates an embodiment of a process where the operation of a lane departure warning system  222  is modified in response to the driver state index of a driver. In step  10002 , the response system  188  receives roadway information. The roadway information can include road size, shape as well as the locations of any road markings or lines. In step  10004 , the response system  188  can determine the vehicle position relative to the road. In step  10006 , the response system  188  can calculate the time to lane crossing. This can be determined from vehicle position, vehicle turning information, and lane location information. 
     In step  10008 , the response system  188  can set the road crossing threshold. The road crossing threshold can be a time associated with the time to lane crossing. In step  10010 , the response system  188  determines if the time to lane crossing exceeds the road crossing threshold. If not, the response system  188  proceeds back to step  10002 . Otherwise, the response system  188  proceeds to step  10012  where a warning indicator is illuminated indicating that the vehicle is crossing a lane. In other cases, audible or haptic warnings could also be provided. If the vehicle continues exiting, the lane a steering effort correction can be applied in step  10014 . 
       FIG. 101  illustrates an embodiment of a process for setting the road crossing threshold. In step  10102 , the response system  188  determines a minimum reaction time for vehicle recovery. In some cases, the minimum reaction time is associated with the minimum amount of time for a vehicle to avoid a lane crossing once a driver becomes aware of the potential lane crossing. In step  10104 , the response system  188  can receive vehicle operating information. Vehicle operating information could include roadway information as well as information related to the location of the vehicle within the roadway. 
     In step  10106 , the response system  188  determines an initial threshold setting from the minimum reaction time and the vehicle operating information. In step  10108 , the response system  188  determines the body index state of the driver. In step  10110 , the response system  188  determines a lane departure warning coefficient according to the driver state index. An exemplary look-up table  10112  includes a range of coefficient values between 0% and 25% as a function of the driver state index. Finally, in step  10114 , the response system  188  can set the road crossing threshold according to the lane departure warning coefficient and the initial threshold setting. 
     In addition to providing earlier warnings to a driver through a lane departure warning system, the response system  188  can also modify the operation of a lane keep assist system, which can also provide warnings as well as driving assistance in order to maintain a vehicle in a predetermined lane. 
       FIG. 102  illustrates an embodiment of a process of operating a lane keep assist system in response to driver state. In particular,  FIG. 102  illustrates a method where the operation of a lane keep assist system is modified in response to the driver state index of a driver. In step  10202 , the response system  188  can receive operating information. For example, in some cases the response system  188  can receive roadway information related to the size and/or shape of a roadway, as well as the location of various lines on the roadway. In step  10204 , the response system  188  determines the location of the road center and the width of the road. This can be determined using sensed information, such as optical information of the roadway, stored information including map based information, or a combination of sensed and stored information. In step  10206 , the response system  188  can determine the vehicle position relative to the road. 
     In step  10208 , the response system  188  can determine the deviation of the vehicle path from the road center. In step  10210 , the response system  188  can learn the driver&#39;s centering habits. For example, alert drivers generally adjust the steering wheel constantly in attempt to maintain the car in the center of a lane. In some cases, the centering habits of a driver can be detected by the response system  188  and learned. Any machine learning method or pattern recognition algorithm could be used to determine the driver&#39;s centering habits. 
     In step  10212 , the response system  188  can determine if the vehicle is deviating from the center of the road. If not, the response system  188  proceeds back to step  10202 . If the vehicle is deviating, the response system  188  proceeds to step  10214 . In step  10214 , the response system  188  can determine the driver state index of the driver. Next, in step  10216 , the response system  188  can set the lane keep assist status using the driver state index. For example, a look-up table  10218  is an example of a relationship between driver state index and lane keep assist status. In particular, the lane keep assist status is set to a standard state for low driver state index (indexes 1 or 2) and is set to a low state for a higher driver state index (indexes 3 or 4). In other embodiments, any other relationship between driver state index and lane keep assist status can be used. 
     In step  10220 , the response system  188  can check the lane keep assist status. If the lane keep assist status is standard, the response system  188  proceeds to step  10222  where standard steering effort corrections are applied to help maintain the vehicle in the lane. If, however, the response system  188  determines that the lane keep assist status is low in step  10220 , the response system  188  can proceed to step  10224 . In step  10224 , the response system  188  determines if the road is curved. If not, the response system  188  proceeds to step  10226  to illuminate a lane keep assist warning so the driver knows the vehicle is deviating from the lane. If, in step  10224 , the response system  188  determines the road is curved, the response system  188  proceeds to step  10228 . In step  10228 , the response system  188  determines if the driver&#39;s hands are on the steering wheel. If so, the response system  188  proceeds to step  10230  where the process ends. Otherwise, the response system  188  proceeds to step  10226 . 
     This arrangement allows the response system  188  to modify the operation of the lane keep assist system in response to driver state. In particular, the lane keep assist system can only help steer the vehicle automatically when the driver state is alert (low driver state index). Otherwise, if the driver is drowsy or very drowsy (higher driver state index), the response system  188  can control the lane keep assist system to only provide warnings of lane deviation without providing steering assistance. This can help increase the alertness of the driver when he or she is drowsy. 
     A response system can include provisions for modifying the control of a blind spot indicator system when a driver is drowsy. For example, in some cases, a response system could increase the detection area. In other cases, the response system could control the monitoring system to deliver warnings earlier (i.e., when an approaching vehicle is further away). 
       FIGS. 103 and 104  illustrate schematic views of an embodiment of the operation of a blind spot indicator system. In this embodiment, the motor vehicle  100  is traveling on roadway  10302 . The blind spot indicator system  224  (see  FIG. 2 ) can be used to monitor any objects traveling within a blind spot monitoring zone  10304 . For example, in the current embodiment, the blind spot indicator system  224  can determine that no object is inside of the blind spot monitoring zone  10304 . In particular, a target vehicle  10306  is just outside of the blind spot monitoring zone  1304 . In this case, n103o alert is sent to the driver. 
     In  FIG. 103 , the driver  102  is shown as fully alert. In this alert state, the blind spot monitoring zone is set according to predetermined settings and/or vehicle operating information. However, as seen in  FIG. 104 , as the driver  102  becomes drowsy, the response system  188  can modify the operation of the blind spot indicator system  224 . For example, in one embodiment, the response system  188  can increase the size of the blind spot monitoring zone  10304 . As seen in  FIG. 104 , under these modified conditions the target vehicle  10306  is now traveling inside of the blind spot monitoring zone  10304 . Therefore, in this situation the driver  102  is alerted (e.g., alert  10308 ) to the presence of the target vehicle  10306 . 
       FIG. 105  illustrates an embodiment of a process of operating a blind spot indicator system in response to driver state. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  10502 , the response system  188  can receive drowsiness information. In step  10504 , the response system  188  determines if the driver is drowsy. If the driver is not drowsy, the response system  188  returns back to step  10502 . If the driver is drowsy, the response system  188  proceeds to step  10506 . In step  10506 , response system  188  can increase the blind spot detection area. For example, if the initial blind spot detection area is associated with the region of the vehicle between the passenger side mirror about 3-5 meters behind the rear bumper, the modified blind spot detection area can be associated with the region of the vehicle between the passenger side mirror and about 4-7 meters behind the rear bumper. Following this, in step  10508 , the response system  188  can modify the operation of the blind spot indicator system  224  so that the system warns a driver when a vehicle is further away. In other words, if the system initially warns a driver if the approaching vehicle is within 5 meters of the motor vehicle  100 , or the blind spot, the system can be modified to warn the driver when the approaching vehicle is within 10 meters of the motor vehicle  100 , or the blind spot of the motor vehicle  100 . Of course, it will be understood that in some cases, step  10506 , or step  10508  can be optional steps. In addition, other sizes and locations of the blind spot zone are possible. 
       FIG. 106  illustrates an embodiment of a process of operating a blind spot indicator system in response to driver state as a function of the driver state index of the driver. In step  10602 , the response system  188  receives object information. This information can include information from one or more sensors capable of detecting the location of various objects (including other vehicles) within the vicinity of the vehicle. In some cases, for example, the response system  188  receives information from a remote sensing device (such as a camera, lidar or radar) for detecting the presence of one or more objects. 
     In step  10604 , the response system  188  can determine the location and/or bearing of a tracked object. In step  10606 , the response system  188  sets a zone threshold. The zone threshold can be a location threshold for determining when an object has entered into a blind spot monitoring zone. In some cases, the zone threshold can be determined using the driver state index of the driver as well as information about the tracked object. 
     In step  10608 , the response system  188  determines if the tracked object crosses the zone threshold. If not, the response system  188  proceeds to step  10602 . Otherwise, the response system  188  proceeds to step  10610 . In step  10610 , the response system  188  determines if the relative speed of the object is in a predetermined range. If the relative speed of the object is in the predetermined range, it is likely to stay in the blind spot monitoring zone for a long time and can pose a very high threat. The response system  188  can ignore objects with a relative speed outside the predetermined range, since the object is not likely to stay in the blind spot monitoring zone for very long. If the relative speed is not in the predetermined range, the response system  188  proceeds back to step  10602 . Otherwise, the response system  188  proceeds to step  10612 . 
     In step  106012 , the response system  188  determines a warning type using the driver state index. In step  10614 , the response system  188  sets the warning intensity and frequency using the driver state index. Lookup table  10618  is an example of a relationship between driver state index and a coefficient for warning intensity. Finally, in step  10620 , the response system  188  activates the blind spot indicator warning to alert the driver of the presence of the object in the blind spot. 
       FIG. 107  illustrates an embodiment of a process for determining a zone threshold. In step  10702 , the response system  188  retrieves tracked object information. In step  10704 , the response system  188  can determine an initial threshold setting. In step  10706 , the response system  188  can determine the driver state index of the driver. In step  10708 , the response system  188  can determine a blind spot zone coefficient. For example, a look-up table  10710  includes a predetermined relationship between driver state index and the blind spot zone coefficient. The blind spot zone coefficient can range between 0% and 25% in some cases and can generally increase with the driver state index. Finally, in step  10712 , the response system  188  can determine the zone threshold. 
     Generally, the zone threshold can be determined using the initial threshold setting (determined in step  10704 ) and the blind spot zone coefficient. For example, if the blind spot zone coefficient has a value of 25%, the zone threshold can be up to 25% larger than the initial threshold setting. In other cases, the zone threshold can be up to 25% smaller than the initial threshold setting. In other words, the zone threshold can be increased or decreased from the initial threshold setting in proportion to the value of the blind spot zone coefficient. Moreover, as the value of the zone threshold changes, the size of the blind spot zone or blind spot detection area can change. For example, in some cases, as the value of the zone threshold increases, the length of the blind spot detection area is increased, resulting in a larger detection area and higher system sensitivity. Likewise, in some cases, as the value of the zone threshold decreases, the length of the blind spot detection area is decreased, resulting in a smaller detection area and lower system sensitivity. 
       FIG. 108  illustrates an example of an embodiment of various warning settings according to the driver state index in the form of a lookup table  10802 . For example, when the driver&#39;s driver state index is 1, the warning type can be set to indicator only. In other words, when the driver is not drowsy, the warning type can be set to light-up one or more warning indicators only. When the driver state index is 2, both indicators and sounds can be used. When the driver&#39;s driver state index is 3, indicators and haptic feedback can be used. For example, a dashboard light can flash and the driver&#39;s seat or the steering wheel can vibrate. When the driver&#39;s driver state index is 4, indicators, sounds and haptic feedback can all be used. In other words, as the driver becomes more drowsy (increased driver state index), a greater variety of warning types can be used simultaneously. It will be understood that the present embodiment only illustrates exemplary warning types for different driver state indexes and in other embodiments, any other configuration of warning types for driver state indexes can be used. 
       FIGS. 109 through 116  illustrate exemplary embodiments of the operation of a collision mitigation braking system (CMBS) in response to driver state. In some cases, a collision mitigation braking system could be used in combination with a forward collision warning system. In particular, in some cases, a collision mitigation braking system could generate forward collision warnings in combination with, or instead of, a forward collision warning system. Moreover, the collision mitigation braking system could be configured to further actuate various systems, including braking systems and electronic seat belt pretensioning systems, in order to help avoid a collision. In other cases, however, a collision mitigation braking system and a forward collision warning system could be operated as independent systems. In the exemplary situations discussed below, a collision mitigation braking system is capable of warning a driver of a potential forward collision. However, in other cases, a forward collision warning could be provided by a separate forward collision warning system. 
     As seen in  FIG. 109 , the motor vehicle  100  is driving behind target vehicle  10902 . In this situation, the motor vehicle  100  is traveling at approximately 60 mph, while a target vehicle  10902  is slowing to approximately 30 mph. At this point, the motor vehicle  100  and the target vehicle  10902  are separated by a distance D 1 . Because the driver is alert, however, the CMBS  220  determines that the distance D 1  is not small enough to require a forward collision warning. In contrast, when the driver is drowsy, as seen in  FIG. 110 , the response system  188  can modify the operation of the CMBS  220  so that a warning  11002  is generated during a first warning stage of the CMBS  220 . In other words, the CMBS  220  becomes more sensitive when the driver is drowsy. Moreover, as discussed below, the level of sensitivity can vary in proportion to the degree of drowsiness (indicated by the driver state index). 
     Referring now to  FIG. 111 , the motor vehicle  100  continues to approach the target vehicle  10902 . At this point, the motor vehicle  100  and the target vehicle  10902  are separated by a distance D 2 . This distance is below the threshold for activating a forward collision warning  11102 . In some cases, the warning could be provided as a visual alert and/or an audible alert. However, because the driver is alert, the distance D 2  is not determined to be small enough to activate additional collision mitigation provisions, such as automatic braking and/or automatic seat belt pretensioning. In contrast, when the driver is drowsy, as seen in  FIG. 112 , the response system  188  can modify the operation of the CMBS  220  so that in addition to providing the forward collision warning  11102 , the CMBS  220  can also automatically pretension a seat belt  11202 . Also, in some cases, the CMBS  220  can apply light braking  11204  to slow the motor vehicle  100 . In other cases, however, no braking can be applied at this point. 
     For purposes of illustration, the distance between vehicles is used as the threshold for determining if the response system  188  should issue a warning and/or apply other types of intervention. However, it will be understood that in some cases, the time to collision between vehicles can be used as the threshold for determining what actions the response system  188  can perform. In some cases, for example, using information about the velocities of the host and target vehicles as well as the relative distance between the vehicles can be used to estimate a time to collision. The response system  188  can determine if warnings and/or other operations should be performed according to the estimated time to collision. 
       FIG. 113  illustrates an embodiment of a process for operating a collision mitigation braking system in response to driver state. In step  11302 , the response system  188  can receive target vehicle information and host vehicle information. For example, in some cases the response system  188  can receive the speed, location, and/or bearing of the target vehicle as well as the host vehicle. In step  11304 , the response system  188  can determine the location of an object in the sensing area, such as a target vehicle. In step  11306 , the response system  188  can determine the time to collision with the target vehicle. 
     In step  11308 , the response system  188  can set a first time to collision threshold and a second time to collision threshold. In some cases, the first time to collision threshold can be greater than the second time to collision threshold. However, in other cases, the first time to collision threshold can be less than or equal to the second time to collision threshold. Details for determining the first time to collision threshold and the second time to collision threshold are discussed below and shown in  FIG. 114 . 
     In step  11310 , the response system  188  can determine if the time to collision is less than the first time to collision threshold. If not, the response system  188  returns to step  11302 . In some cases, the first time to collision threshold can a value above which there is no immediate threat of a collision. If the time to collision is less than the first time to collision threshold, the response system  188  proceeds to step  11312 . 
     At step  11312 , the response system  188  can determine if the time to collision is less than the second time to collision threshold. If not, the response system  188  enters a first warning stage at step  11314 . The response system  188  can then proceed through further steps discussed below and shown in  FIG. 115 . If the time to collision is greater than the second time to collision threshold, the response system  188  can enter a second warning stage at step  11316 . The response system  188  can then proceed through further steps discussed below and shown in  FIG. 116 . 
       FIG. 114  illustrates an embodiment of a process for setting a first time to collision threshold and a second time to collision threshold. In step  11402 , the response system  188  can determine a minimum reaction time for avoiding a collision. In step  11404 , the response system  188  can receive target and host vehicle information such as location, relative speeds, absolute speeds, as well as any other information. In step  11406 , the response system  188  can determine a first initial threshold setting and a second initial threshold setting. In some cases, the first initial threshold setting corresponds to the threshold setting for warning a driver. In some cases, the second initial threshold setting corresponds to the threshold setting for warning a driver and also operating braking and/or seat belt pretensioning. In some cases, these initial threshold settings can function as default setting that can be used with a driver is fully alert. Next, in step  11408 , the response system  188  can determine the driver state index of the driver. 
     In step  11410 , the response system  188  can determine a time to collision coefficient. In some cases, the time to collision coefficient can be determined using look-up table  11412 , which relates the time to collision coefficient to the driver state index of the driver. In some cases, the time to collision coefficient increases from 0% to 25% as the driver state index increases. In step  11414 , the response system  188  can set the first time to collision threshold and the second time to collision threshold. Although a single time to collision coefficient is used in this embodiment, the first time to collision threshold and the second time to collision threshold can differ according to the first initial threshold setting and the second initial threshold setting, respectively. Using this configuration, in some cases, the first time to collision threshold and the second time to collision threshold can be decreased as the driver state index of a driver increases. This allows the response system  188  to provide earlier warnings of potential hazards when a driver is drowsy. Moreover, the timing of the warnings varies in proportion to the driver state index. 
       FIG. 115  illustrates an embodiment of a process for operating a motor vehicle in a first warning stage of the CMBS  220 . In step  11502 , the response system  188  can select visual and/or audible warnings for alerting a driver of a potential forward collision. In some cases, a warning light can be used. In other cases, an audible noise, such as a beep, could be used. In still other cases, both a warning light and a beep could be used. 
     In step  11504 , the response system  188  can set the warning frequency and intensity. This can be determined using the driver state index in some cases. In particular, as the driver state increases due to the increased drowsiness of the driver, the warning state frequency and intensity can be increased. For example, in some cases a look-up table  11506  can be used to determine the warning frequency and intensity. In particular, in some cases as the warning intensity coefficient increases (as a function of driver state index), the intensity of any warning can be increased by up to 25%. In step  11508 , the response system  188  can apply a warning for forward collision awareness. In some cases, the intensity of the warning can be increased for situations where the warning intensity coefficient is large. For example, for a low warning intensity coefficient (0%) the warning intensity can be set to a predetermined level. For higher warning intensity coefficients (greater than 0%), the warning intensity can be increased beyond the predetermined level. In some cases, the luminosity of visual indicators can be increased. In other cases, the volume of audible warnings can be increased. In still other cases, the pattern of illuminating a visual indicator or making an audible warning could be varied. 
       FIG. 116  illustrates an embodiment of process of operating a motor vehicle in a second stage of the CMBS  220 . In some cases, during step  11602 , the CMBS  220  can use visual and/or audible warnings to alert a driver of a potential collision. In some cases, the level and/or intensity of the warnings could be set according to the driver state index, as discussed above and shown in step  11504  of  FIG. 115 . Next, in step  11604 , the response system  188  can use a haptic warning. In situations where visual and/or audible warnings are also used, the haptic warning can be provided simultaneously with the visual and/or audible warnings. In step  11606 , the response system  188  can set the warning frequency and intensity of the haptic warning. This can be achieved using look-up table  11608 , for example. Next, in step  11610 , the response systems  188  can automatically pretension a seat belt in order to warn the driver. The frequency and intensity of the tensioning can vary as determined in step  11606 . In step  11612 , the response system  188  can apply light braking automatically in order to slow the vehicle. In some cases, step  11612  can be optional step. 
       FIG. 117  illustrates an embodiment of a process of operating a navigation system in response to driver state. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     In step  11702 , the response system  188  can receive drowsiness information. In step  11704 , the response system  188  can determine if the driver is drowsy. If the driver is not drowsy, the response system  188  proceeds back to step  11702 . Otherwise, the response system  188  proceeds to step  11706 . In step  11706 , the response system  188  can turn off navigation system  230 . This can help reduce driver distraction. 
       FIG. 118  illustrates an embodiment of a process of operating a failure detection system in response to a driver state. In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as the failure detection system  244  and/or the vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     At step  11802 , the method includes receiving drowsiness information. In some cases, the drowsiness information includes whether a driver is in a normal state or a drowsy state. Moreover, in some cases, the drowsiness information could include a value indicating the level of drowsiness, for example on a scale of 1 to 10, with 1 being the least drowsy and 10 being the drowsiest. In some embodiments, other types of information can be received at step  11802 , for example, physiological monitoring information, behavioral monitoring information, vehicular monitoring information, and other monitoring information from the vehicle systems  126  and the monitoring systems  300 . 
     At step  11804 , the method includes determining if the driver is drowsy based on the drowsiness information. If the driver is not drowsy, the response system  188  returns back to step  11802 . If the driver is drowsy, the response system  188  proceeds to step  11806 . 
     In step  11806 , the method includes receiving vehicle information. In some cases, the ECU  106  and/or the response system  188  can receive the vehicle information from one or more vehicle systems  126 . In other cases, the vehicle information can be received directly from the one or more vehicle systems  126 . In some embodiments, a vehicular state can be determined at step  11806  based on the vehicle information. 
     In step  11808 , the method includes modifying one or more failure thresholds of the failure detection system based on the drowsiness information and the vehicle information. It is appreciated, that in some embodiments, the failure thresholds can be modified based on the drowsiness information only and that step  11806  can be omitted. The response system  188  can modify one or more failure thresholds of the failure detection system  244  for one or more vehicle systems  126 . It is understood that the response system  188  can modify one or more failure thresholds specific to a vehicle system (e.g., the failure threshold for a braking system can be different from the failure threshold for an electric power steering system). Modifying the failure threshold changes the sensitivity of the detection of failure in the corresponding vehicle system. For example, in a situation where the driver is drowsy, the sensitivity of the detection of failure in the corresponding vehicle system can be increased. In one embodiment, the threshold is modified as a function of the driver state and/or vehicular state. 
     In one embodiment, at step  11808 , modifying the failure threshold is based on a function of the driver state. For example, the failure threshold can be decreased as the driver state index increases (e.g., indicating drowsiness). The failure detection system  244  may include a lookup table  11810 . The lookup table  11810  shows example control types of the failure thresholds according to the driver state index. For example, when the driver state index is 1 or 2, the control type can be set to “no change.” In these situations, the response system  188  may not modify the failure threshold. When the driver state index of the driver is 3, which can indicate that the driver is somewhat drowsy, the response system  188  can set the control type to “moderate change.” In this situation, the response system  188  may modify the failure threshold slightly, for example, the failure threshold can be decreased slightly (e.g., therefore increasing the failure sensitivity slightly). When the driver state index of the driver is 4, which can indicate that the driver is drowsy, the response system  188  can set the control type to “significant change” (e.g., considerable change). In this situation, the response system  188  may modify the failure threshold greatly, for example, the failure threshold can be decreased greatly (e.g., therefore increasing the failure sensitivity greatly). 
     Referring now to  FIG. 119 , a diagram showing exemplary failure detection by a failure detection system is shown.  FIG. 119  will be described with respect to detecting a failure in a control signal  11902  of an electronic power steering system, however, it is appreciated that failure detection can apply to any vehicle system. In  FIG. 119 , exemplary failure thresholds  11904  and  11906  indicate failure thresholds where the failure detection system  244  executes a fail-safe function (e.g., system shutdown). Exemplary control thresholds  11908  and  11910  indicate thresholds where the failure detection system  244  executes a non-fail-safe function (e.g., controlling a vehicle system). 
     In  FIG. 119 , the failure detection system  244  receives the control signal  11902  over a period of time from, for example, an electronic power steering system  132 . As an illustrative example, the control signal  11902  can be a signal indicating a steering angle (e.g., corresponding to a rotation angle of the steering wheel). In another example, the control signal  11902  can be a signal from another type of steering wheel sensor. The failure detection system  244  monitors the control signal  11902  and compares the control signal  11902  to the thresholds. At points  11912 ,  11914  and  11916 , the control signal  11902  meets the control threshold  11908 . At these points, the failure detection system  244  executes a no fail-state function to help control and/or mitigate system shut down. For example, the failure detection system  244  may control a braking system to apply braking when the control signal  11902  meets a control threshold. 
     At point  11918 , the control signal  11902  meets the failure threshold  11904 . Accordingly, the failure detection system  244  executes a fail-safe function and shuts down the electronic power steering system  132  indicating a system failure has occurred. According to the methods and systems described herein (e.g.,  FIG. 118 ), the failure threshold  11904  can be modified based on the driver state and/or the situation in which the motor vehicle and/or vehicle system is operating. As shown in  FIG. 119 , an exemplary modified failure threshold  11920  is shown. Accordingly, at point  11922 , the control signal  11902  meets the modified failure threshold  11920 . This causes the failure detection system  244  to execute a fail-safe function and shut down the electronic power steering system  132  at a time t (e.g., an earlier time) than the failure detected at point  11918  based on the original failure threshold  11904 . 
     As will be discussed in further detail herein, in addition to modifying failure thresholds, the failure detection system  244  can also control one or more vehicle systems based on the driver state and an operating condition of the vehicle when a failure is detected. Referring now to  FIG. 120 , an embodiment of operating one or more vehicle systems in response to driver state and failure detection is illustrated. It is appreciated that the components of  FIGS. 118 and 120  can be integrated and or organized into different processes for different embodiments. 
     In some embodiments, some of the following steps could be accomplished by a response system  188  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  106  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as the failure detection system  244  and/or the vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIGS. 1A, 1B through 3 , including the response system  188 . 
     At step  12002 , the method includes receiving monitoring information. The monitoring information can include drowsiness information indicating whether a driver is in a normal state or a drowsy state. Moreover, in some cases, the drowsiness information could include a value indicating the level of drowsiness, for example on a scale of 1 to 10, with 1 being the least drowsy and 10 being the drowsiest. The monitoring information can also include other types of information, for example, physiological monitoring information, behavioral monitoring information, vehicle information, and other monitoring information from the vehicle systems  126  and the monitoring systems  300 . Further, the monitoring information can include information from the failure detection system  244 . 
     At step  12004 , the method includes determining if a failure is detected for one or more vehicle systems. For example, the response system  188  can receive failure information (e.g., monitoring information received at step  12002 ) about one or more vehicle systems from the failure detection system  244 . Referring to  FIG. 119 , a failure is detected, for example, at failure thresholds  11904 ,  11906 , or  11920 . In another embodiment, the response system  188  can receive vehicle information directly from vehicle systems  126  and analyze the vehicle information based on the thresholds of the failure detection system  244 . For example, the response system  188  can receive a control signal  11902  from a steering system and analyze the control signal  11902  with respect to the failure thresholds  11904 ,  11906 , or  11920 . Referring back to  FIG. 120 , if a failure is not detected, the method returns to step  12002 . If a failure is detected, at step  12006  it is determined if the driver is drowsy, for example, based on the monitoring information. 
     If the driver is not drowsy, the method returns to step  12002 . If the driver is drowsy, at step  12008 , the method includes determining a vehicular state. The vehicular state can include information related to the motor vehicle  100  of  FIG. 1A  and/or the vehicle systems  126 , including those vehicle systems listed in  FIG. 2 . In some cases, the vehicle information can also be related to a driver of the motor vehicle  100 . Specifically, vehicle information can include vehicle conditions, vehicle behaviors, and information about the external environment of the vehicle. In some embodiments, at step  12008 , vehicular information can be received from one or more vehicle systems to determine a vehicular state. In other embodiments, the vehicle information can be received at step  12002 . In some embodiments, at step  12008 , the method can include determining a current vehicle operating condition. In other embodiments, at step  12008 , the method can include determining a current vehicle situation. In further embodiments, at step  12008 , the method can include determining a hazard and/or risk level of the vehicle operating condition. 
     At step  12010 , the method includes modifying one or more vehicle systems based on the driver state and the vehicular state. Accordingly, the vehicle systems can be adjusted to mitigate the vehicle system failure and/or mitigate the consequences of the vehicle system failure. The vehicle systems are modified not only based on the driver state, but also the current operating conditions and/or current situation of the vehicle. It is appreciated that in some embodiments, the vehicle systems can be modified according to the driver state and/or the vehicular state as described in the lookup table  11810  of  FIG. 118 . Further, in some embodiments, the vehicle systems can be modified according to the severity of the failure detected. 
       FIG. 121  illustrates another embodiment of operating one or more vehicle systems and modifying failure thresholds in response to driver state and failure detection. At step  12102 , the method includes receiving monitoring information. The monitoring information can include drowsiness information indicating whether a driver is in a normal state or a drowsy state. Moreover, in some cases, the drowsiness information could include a value indicating the level of drowsiness, for example on a scale of 1 to 10, with 1 being the least drowsy and 10 being the drowsiest. The monitoring information can also include other types of information, for example, physiological monitoring information, behavioral monitoring information, vehicle information, and other monitoring information from the vehicle systems  126  and the monitoring systems  300 . Further, the monitoring information can include information from the failure detection system  244 . 
     At step  12104  it is determined if the driver is drowsy, for example, based on the monitoring information. If the driver is not drowsy, the method returns to step  12102 . If the driver is drowsy, at step  12106 , the method may include modifying one or more failure thresholds of the failure detection system  244  based on the monitoring information and drowsiness information. Modifying the failure threshold changes the sensitivity of the detection of failure in the corresponding vehicle system. For example, in a situation where the driver is drowsy, the sensitivity of the detection of failure in the corresponding vehicle system can be increased. In one embodiment, the threshold is modified as a function of the driver state. 
     At step  12108 , the method includes determining if a failure is detected for one or more vehicle systems. For example, the response system  188  can receive failure information (e.g., monitoring information received at step  12102 ) about one or more vehicle systems from the failure detection system  244 . Referring to  FIG. 119 , a failure is detected, for example, at failure thresholds  11904 ,  11906 , or  11920 . In another embodiment, the response system  188  can receive vehicle information directly from vehicle systems  126  and analyze the vehicle information based on the thresholds of the failure detection system  244 . For example, the response system  188  can receive a control signal  11902  from a steering system and analyze the control signal  11902  with respect to the failure thresholds  11904 ,  11906 , or  11920 . Referring back to  FIG. 121 , in another embodiment, the response system  188  can compare information from one or more vehicle systems to determine if a failure is detected as described in U.S. application Ser. No. 14/733,836 filed on Jun. 8, 2015 and incorporated herein by reference. It is understood that other methods for determining and/or detecting a failure can be implemented herein. 
     If a failure is not detected, the method returns to step  12102 . If a failure is detected, at step  12110 , the method includes determining a vehicular state. The vehicular state can include information related to the motor vehicle  100  of  FIG. 1A  and/or the vehicle systems  126 , including those vehicle systems listed in  FIG. 2 . In some cases, the vehicle information can also be related to a driver of the motor vehicle  100 . Specifically, vehicle information can include vehicle conditions, vehicle behaviors, and information about the external environment of the vehicle. In some embodiments, at step  12110 , vehicular can be received from one or more vehicle systems to determine the vehicular state. In other embodiments, the vehicle information can be received at step  12102 . In some embodiments, at step  12110 , the method can include determining a current vehicle operating condition. In other embodiments, at step  12110 , the method can include determining a current vehicle situation. In further embodiments, at step  12110 , the method can include determining a hazard and/or risk level of the vehicle operating condition. 
     At step  12112 , the method includes modifying one or more vehicle systems based on the driver state and the vehicular state. Accordingly, the vehicle systems can be adjusted to mitigate the vehicle system failure and/or mitigate the consequences of the vehicle system failure. The vehicle systems are modified not only based on the driver state, but also the current operating conditions and/or current situation of the vehicle. It is appreciated that in some embodiments, the vehicle systems can be modified according to the driver state and/or the vehicular state as described in the lookup table  11810  of  FIG. 118 . Further, in some embodiments, the vehicle systems can be modified according to the severity of the failure detected. 
     Specific examples of modifying one or more vehicle systems according to the process of  FIGS. 118, 120 and/or 121  will now be discussed. It is understood that the follow examples are illustrative in nature and that other vehicle systems can be modified. Referring again to  FIG. 120 , at  12004  it is determined based on monitoring information from the failure detection system  244  and/or the engine  104  that a vehicle transmission system is in a failure state. For example, as shown in  FIG. 122A , the effect of a vehicle transmission system in a failure state is shown. Here, the motor vehicle  100  is travelling on a road  12202  (e.g., a hill) and the vehicle transmission system (not shown) of the motor vehicle  100  is detected as being in a fail state (e.g., the motor vehicle  100  is rolling back on the road  12202 ). 
     Accordingly, at step  12006 , it is determined if the driver is drowsy. If YES, at step  12008  a vehicular state is determined. In this example, the vehicular state is determined based on vehicle information about the vehicle and the environment of the vehicle (e.g., current operating parameters and/or a current situation). For example, in  FIG. 122A , the motor vehicle  100  is on a road (e.g., a hill, a road with a steep grade incline)  12202 . Other information can include weather conditions (e.g., icy road) and/or roll back speed. Based on at least one of the driver state and the vehicular state, one or more vehicle systems at step  12010  are modified. For example, the electric parking brake system  210  can be applied. In another embodiment, other modifications to other braking systems can be applied, for example, a brake assist system  206 , an automatic brake prefill system  208 , among others, can be modified. 
     In another example, shown in  FIG. 122B , a vehicular state can include information about objects around the vehicle, detected for example, by a blind spot indicator system  224 , a lane monitoring system  228 , among others. In  FIG. 122B , a target vehicle  12204  is shown behind the motor vehicle  100 . Accordingly, modifying the one or more vehicle systems can include modifying the braking systems according to a distance  12206  between the target vehicle  12204  and the motor vehicle  100 . For example, if the target vehicle  12204  is very close to the motor vehicle  100 , the electric parking brake system  210  may be applied immediately. 
     As another illustrative example and referring again to the method of  FIG. 120 , it may be determined at step  12004  from monitoring information received at step  12002  that vehicle acceleration is in a failure state. For example, the vehicle may be experience sudden acceleration unexpectedly without input from the driver  102  (e.g., via an accelerator pedal). Accordingly, at step  12006 , it is determined if the driver is drowsy. If YES, at step  12008  a vehicular state is determined. In this example, the vehicular state determined based on vehicle information about the vehicle and the environment of the vehicle (e.g., current operating parameters and/or a current situation). For example, as shown in  FIG. 123 , the motor vehicle  100  in a failure state where sudden acceleration is detected. The vehicular state can include information about objects around the motor vehicle  100 , for example the target vehicle  12302  in front of the motor vehicle  100  and the distance  12304  between the motor vehicle  100  and the target vehicle  12302 . Accordingly, at step  12010 , the vehicle systems are modified based on at least one of the driver state and the vehicular state. For example, a brake assist system  206  can be actuated to begin braking the vehicle. The braking can be based on the distance  12304  between the target vehicle  12302  and the motor vehicle  100  to avoid a collision with the target vehicle  12302 . If the target vehicle  12302  is not present, the brake assist system  206  may be actuated to brake at a slower rate than if the target vehicle  12302  was present. 
     As another illustrative example and referring again to the method of  FIG. 120 , it may be determined at step  12004  from monitoring information received at step  12002  that the electronic power steering system  132  is in a failure state (e.g., loss of steering, steering circuit brake). Accordingly, at step  12006 , it is determined if the driver is drowsy. If YES, at step  12008  a vehicular state is determined. In this example, the vehicular state determined based on vehicle information about the vehicle and the environment of the vehicle (e.g., current operating parameters and/or a current situation). For example, as shown in  FIG. 124 , the motor vehicle  100  is in a failure state where there is a sudden loss of steering. Here, a target vehicle  12402  is detected in a blind spot monitoring zone  12404  by a blind spot indicator system  224 . Further, a potential lane deviation (e.g., caused by the sudden loss of steering) can be detected towards the center lane  12406  by a lane departure warning system  222 . Accordingly, at step  12010 , the vehicle systems are modified based on at least one of the driver state and the vehicular state. 
     In this example, the steering wheel  134  can be actuated and turned in a direction away from the target vehicle  12402 . In another embodiment, a lane keep assist system  226  can be actuated to keep the motor vehicle  100  in the current lane. In another embodiment, the response system  188  can actuate an auto control status (e.g., vehicle mode selector system  238 ) and/or a braking system to safely stop the vehicle. For example, the response system  188  can activate the automatic cruise control system  216  and the lane keep assist system  226  to slow down the vehicle, keep the vehicle in a current lane until the vehicle comes to a complete stop. 
     It will be appreciated that the exemplary operational responses discussed in Section VI can also apply to methods and systems utilizing a plurality of driver states, a combined driver state, and/or a vehicular state. Thus, the driver state index discussed in the exemplary operational responses can be substituted with more than one driver state and/or a combined driver state index as determined by the methods and systems discussed in Section IV. Exemplary operational responses based on one or more driver states (e.g., multi-modal neural network of driver states) and/or vehicular states will now be discussed. However, it is appreciated that these examples are illustrative in nature and other combinations of vehicle systems, monitoring systems and responses can be contemplated. 
     Referring now to  FIG. 125 , a flow chart of an illustrative process of controlling vehicle systems according to combined driver state index using heart rate information and eye movement information according to an exemplary embodiment is shown. In step  12502 , the method includes receiving heart rate information, from for example a heart rate monitoring system that senses heart rate using a bio-monitoring sensor  180  embedded in the vehicle seat  168  ( FIG. 1A ). In step  12504 , the first driver state is determined based on the heart rate information. Thus, in this embodiment, the first driver state is a physiological driver state. In step  12506 , the method includes receiving head and/or eye movement information, from for example, an optical sensing device  162 , the eye/facial movement monitoring system  332  and/or the head movement monitoring system  334 . In step  12508 , a second driver state is determined based on the eye movement information. Thus, in this embodiment, the second driver state is a behavioral driver state. 
     In step  12510 , it is determined if the first driver state meets a first driver state threshold. If YES, in step  12512 , the first driver state is confirmed with another driver state, namely, the second driver state. In step  12514 , it is determined if the second driver state meets a second driver state threshold. If YES, at step  12516 , a combined driver state index is determined based on the first driver state and the second driver state. In step  12518 , control of one or more vehicle systems is modified based on the combined driver state index. For example, an antilock brake system  204  can be modified based on the combined driver state index similar to the methods and systems described in the  FIGS. 76 and 77 . It is understood that the steps of  FIG. 125  can be reorganized for different embodiments. For example, as discussed in Section IV, the combined driver state index can be determined with or without thresholds and/or with or without confirmation with another driver state. Further, the thresholds can be implemented at different points in the process of  FIG. 125 , for example, after confirmation. It is also appreciated that the process of  FIG. 125  can include more than two driver states and/or a vehicular state. 
       FIG. 126  illustrates a flow chart of an illustrative process of controlling vehicle systems according to combined driver state index similar to  FIG. 125 , but using heart rate information and steering information. In step  12602 , the method includes receiving heart rate information, from for example a heart rate monitoring system that senses heart rate using a bio-monitoring sensor  180  embedded in the vehicle seat  168  ( FIG. 1A ). In step  12604 , the first driver state is determined based on the heart rate information. Thus, in this embodiment, the first driver state is a physiological driver state. In step  12606 , the method includes receiving steering information, from for example, the electronic stability control system  202 . In step  12608 , a second driver state is determined based on the steering information. Thus, in this embodiment, the second driver state is a vehicular-sensed driver state, since the steering information is associated with the driver  102 . 
     In step  12610 , it is determined if the first driver state meets a first driver state threshold. If YES, in step  12612 , the first driver state is confirmed with another driver state, namely, the second driver state. In step  12614 , it is determined if the second driver state meets a second driver state threshold. If YES, at step  12616 , a combined driver state index is determined based on the first driver state and the second driver state. In step  12618 , control of one or more vehicle systems is modified based on the combined driver state index. For example, a brake assist system  206  can be modified based on the combined driver state index similar to the methods and systems described in the  FIGS. 80 and 81 . It is understood that the steps of  FIG. 126  can be reorganized for different embodiments. For example, as discussed in Section IV, the combined driver state index can be determined with or without thresholds and/or with or without confirmation with another driver state. Further, the thresholds can be implemented at different points in the process of  FIG. 126 , for example, after confirmation. It is also appreciated that the process of  FIG. 126  can include more than two driver states and/or a vehicular state. 
       FIG. 127  illustrates a flow chart of an illustrative process of controlling vehicle systems according to combined driver state index similar to  FIGS. 125 and 126 , but using head movement information and acceleration/deceleration information. In step  12702 , the method includes receiving head movement information, from for example a head movement monitoring system  334 . In step  12704 , the first driver state is determined based on the head movement information. As an illustrative example, the first driver state can indicate a number of head nods over a period of time as determined by the head movement monitoring system  334 . In step  12706 , the method includes receiving acceleration and/or deceleration information, from for example, the electronic stability control system  202 . In step  12708 , a second driver state is determined based on the acceleration and/or deceleration information. As an illustrative example, the second driver state can indicate a number of accelerations over a period of time. 
     In step  12710 , it is determined if the first driver state meets a first driver state threshold. For example, the first driver state threshold can be a number of head nods over a period of time indicating a drowsy driver. If YES, in step  12712 , the first driver state is confirmed with another driver state, namely, the second driver state. In step  12714 , it is determined if the second driver state meets a second driver state threshold. For example, the second driver state can be a number of accelerations over a period of time indicating a drowsy driver. If YES, at step  12716 , a combined driver state index is determined based on the first driver state and the second driver state. If no, the process returns to receiving monitoring information. In step  12718 , control of one or more vehicle systems is modified based on the combined driver state index. It is understood that the steps of  FIG. 127  can be reorganized for different embodiments. For example, as discussed in Section IV, the combined driver state index can be determined with or without thresholds and/or with or without confirmation with another driver state. Further, the thresholds can be implemented at different points in the process of  FIG. 127 , for example, after confirmation. It is also appreciated that the process of  FIG. 127  can include more than two driver states and/or a vehicular state. 
     An exemplary operational response based on one or more driver states and a vehicular state will now be described.  FIG. 128  illustrates a flow chart of an illustrative process of controlling vehicle systems according to combined driver state index and a vehicular state including thresholds. At step  12802 , the response system  188  determines a first driver state. In one embodiment, the first driver state is at least one of a physiological driver state, a behavioral driver state, and a vehicular-sensed driver state. As an illustrative example, the first driver state of  FIG. 128  is a physiological driver state based on, for example, heart rate information of the driver. 
     At step  12804 , the response system  188  determines a second driver state. In one embodiment, the second driver state is at least one of a physiological driver state, a behavioral driver state, and a vehicular-sensed driver state. Thus, referring again to the illustrative example, in  FIG. 128 , the first driver state is a behavioral driver state based on, for example, gesture recognition information from the driver. It is appreciated that a third driver state can also be determined and utilized in the process of  FIG. 128 . In an embodiment with a third driver state, in  FIG. 128 , the third driver state is at least one of a physiological driver state, a behavioral driver state and a vehicular-sensed driver state. 
     At step  12806 , the response system  188  determines a vehicular state based on vehicle information. As an illustrative example, in  FIG. 128 , the vehicular state is based on a current vehicle speed. Each of the first driver state, the second driver state, and the vehicular state can optionally be passed through respective thresholds (e.g., T 1 , T 2 , T v ) by the response system  188 . With regards to the first driver state and the second driver state, at step  12808 , the first driver state and the second driver state can be confirmed, as discussed herein. In one embodiment, step  12808  can be a decision step. Thus, if the outcome of step  12808  is YES (i.e., driver states are confirmed), the response system can proceed to step  12810  to determine a combined driver state based on the first drive state and the second driver state. 
     In another embodiment, the first driver state and the second driver state may not be confirmed, but can be used by the response system  188  to determine a combined driver state index at step  12810 . Further, the combined driver state index can be confirmed and/or compared to the vehicular state by the response system  188  at step  12812 . In one embodiment, step  12812  can be a decision step. Thus, if the outcome of step  12812  is YES (i.e., the combined driver state is confirmed with the vehicular state), the response system  188  can modify the control of the vehicle systems at step  12814  based on the combined driver state index and the vehicular state. 
     An operational illustrative example will now be described. The first driver state (i.e., a heart rate of the driver) meets threshold T 1  indicating a normal driver state (e.g., normal heart rate for the driver). The second driver state (i.e., gesture recognition information) meets threshold T 2  indicating a distracted driver state (e.g., the driver is using gestures that indicate the driver is engaged in other activities other than the task of driving, for example, on the phone). The vehicular state (i.e., current vehicle speed) meets threshold T v  indicating a high risk level (e.g., the current vehicle speed is high). 
     In one embodiment, at step  12808 , the first driver state and the second driver state can be confirmed. In this example, in some embodiments, if the first driver state is normal (i.e., 0) and the second driver state is distracted (i.e., 1), the response system  188  can proceed to step  12810  to determine a combined driver state index based on the first driver state and the second driver state. 
     At step  12812 , the combined driver state index is confirmed with the vehicular state. In this embodiment, if the combined driver state index indicates a distracted driver and the vehicular state indicates a high risk, the response system  188  can modify the control of the vehicle systems at step  12814 . For example, the response system  188  can alert the driver visually (e.g., visual devices  140 ) to their current speed and/or alert the driver about their distracted state. In another embodiment, the response system  188  could restrict the use of the phone the driver is using via, for example, the navigation system  230 . In another embodiment, the response system  188  could modify the lane departure warning system  222  and/or the blind spot indicator system  224  to warn the driver earlier of potential collisions or to prevent the vehicle from changing lanes if the driver is distracted. 
     As another illustrative example, if the vehicular state is based on current traffic information and meets threshold T v  indicating a low risk level (e.g., no traffic or low traffic), at step  12812  when the vehicular state is confirmed and/or compared to the combined driver state index, the response system  188  may not restrict the use of the driver phone, but instead only provide a visual warning to the driver. As can be understood, various combinations and modifications to the one or more vehicle systems are possible. 
     B. Exemplary Operational Response of More than One Vehicle System to Driver State 
     In some embodiments, a vehicle can include provisions for modifying different vehicle systems in response to driver state. Further, in some embodiments, the vehicle can include provisions for modifying different vehicle systems in response to driver state, a combined driver state, and/or a vehicular state, substantially and/or simultaneously. The multiple vehicle systems, in some embodiments, can communicate information to each other for proper modification of control of one or more vehicle systems. The number of vehicle systems that can be simultaneously activated in response to driver state is not limited. For example, in some cases, one or more vehicle systems can be configured to communicate with one another in order to coordinate responses to a hazard or other driving condition. In some cases, the hazard or other driving condition is a vehicular state as discussed above in Section V. In some cases, a centralized control unit, such as an ECU, can be configured to control various different vehicle systems in a coordinated manner to address hazards or other driving conditions. 
     For purposes of clarity, the term hazard, or hazardous condition, is used throughout this detailed description and in the claims to refer generally to one or more objects and/or driving scenarios that pose a potential safety threat to a vehicle. For example, a target vehicle traveling in the blind spot of a driver can be considered a hazard since there is some risk of collision between the target vehicle and the host vehicle should the driver turn into the lane of the target vehicle. Additionally, a target vehicle that is traveling in front of a host vehicle can also be categorized as a hazard for purposes of operating a response system. Furthermore, the term hazard is not limited to describing a target vehicle or other remote object. In some cases, for example, the term hazard can be used to describe one or more hazardous driving conditions that increase the likelihood of an accident. Further, as mentioned above, the term hazard or hazardous condition level can refer to a vehicular state. 
     Modifying control of one or more vehicle systems based on information from more than one vehicle system, the driver state, and in some embodiments, the driver state relative to the information from the vehicle systems (e.g., hazards, risks), allows for a customized response. This results in a level of control appropriate for the current situation (e.g., hazard, risk level) and the current driver state. For example, in some cases when a driver is fully attentive (e.g., not drowsy), control of some vehicle systems can be overridden or suppressed. This gives the driver full control of the vehicle. In some cases when a driver is somewhat attentive (e.g., somewhat drowsy) control of some vehicle systems may be slightly modified. This gives the driver some control of the vehicle. In other cases, where the driver is distracted (e.g., drowsy), some vehicle systems may be significantly modified. This gives the driver less control of the vehicle. Further, in some cases, when the driver is very distracted (e.g., very drowsy and/or possibly asleep), some vehicle systems may be modified to automatically control the vehicle, in a full or semi-autonomous mode. In this case, the driver has little to no control of the vehicle and most control or full control is passed to the vehicle. 
     Accordingly, the embodiments discussed herein will discuss general provisions for sensing driver state and modifying the operation of one or more vehicle systems based on the driver state. More specifically, embodiments providing intra-vehicle communication and control and embodiments providing semi-autonomous and/or fully autonomous control will be discussed. It is understood that the embodiments discussed herein can implement any of the vehicle systems, monitoring systems, and systems for determining driver state and/or combined driver state discussed above. Further, it is understood that methods and systems discussed herein are not limited to use with a driver. In other embodiments, these same methods and systems could be applied to any occupant of a vehicle. In other words, a response system can be configured to detect if various other occupants of a motor vehicle are distracted. Moreover, in some cases, one or more vehicle systems could be modified accordingly. 
     Referring now to the drawings,  FIG. 129  illustrates a schematic view of an embodiment of a response system  12900  for modifying control of one or more vehicle systems. The response system  12900  can include various vehicle systems that can be modified in response to driver state, including drowsy driving. The response system  12900  can be the same and/or similar to the response system  188  of  FIG. 1A . Further, in some cases, the response system  12900  can include a centralized control unit, such as an electronic control unit (ECU)  12902 . The ECU  12902  can be the same and/or similar to the ECU  106  of  FIGS. 1A and 1B . Examples of different vehicle systems that can be incorporated into the response system  12900  include any of the vehicle systems described above and shown in  FIG. 2  as well as any other vehicle systems. It should be understood that the systems shown in  FIG. 2  are only intended to be exemplary and in some cases, some other additional systems can be included. In other cases, some of the systems can be optional and not included in all embodiments. 
     In some embodiments, the response system  12900  includes the electronic power steering system  132 , the touch steering wheel system  134 , the visual devices  140 , the audio devices  144 , the tactile devices  148 , the user input devices  152 , the infotainment system  154 , the electronic stability control system  202 , the antilock brake system  204 , the brake assist system  206 , the automatic brake prefill system  208 , the EPB system  210 , the low speed follow system  212 , the cruise control system  214 , the automatic cruise control system  216 , the collision warning system  218 , the collision mitigation braking system  220 , the lane departure warning system  222 , the blind spot indicator system  224 , the lane keep assist system  226 , the lane monitoring system  228 , the navigation system  230 , the hands free portable device system  232 , the climate control system  234 , the electronic pretensioning system  236 , the vehicle mode selector system  238 , the turn signal control system  240 , the headlight control system  242 , and the failure detection system  244 , which are referred to collectively as the vehicle systems  126 . 
     In other embodiments, the response system  12900  can include additional vehicle systems. In still other embodiments, some of the systems included in  FIG. 129  can be optional. Moreover, in some cases, the response system  12900  can be further associated with various kinds of monitoring devices including any of the monitoring systems and devices discussed above (for example, optical devices, various types of position sensors, monitoring devices or systems, autonomic monitoring devices or systems, as well as any other devices or systems and systems shown in  FIG. 3 ). 
     The response system  12900  can also provisions for centralized control of, and/or communication between, various vehicle systems, using, for example, the ECU  12902 . The ECU  12902  can include a microprocessor, RAM, ROM, and software all serving to monitor and supervise components of the response system  12900  as well as any other components of a motor vehicle. The output of various devices is sent to the ECU  12902  where the device signals can be stored in an electronic storage, such as RAM. Both current and electronically stored signals can be processed by a central processing unit (CPU) in accordance with software stored in an electronic memory, such as ROM. The ECU  12902  can include some or all of the components of the ECU  106  shown in  FIG. 1B . 
     The ECU  12902  can include a number of ports that facilitate the input and output of information and power. The term “port” as used throughout this detailed description and in the claims refers to any interface or shared boundary between two conductors. In some cases, ports can facilitate the insertion and removal of conductors. Examples of these types of ports include mechanical connectors. In other cases, ports are interfaces that generally do not provide easy insertion or removal. Examples of these types of ports include soldering or electron traces on circuit boards. 
     All of the following ports and provisions associated with the ECU  12902  are optional. Some embodiments can include a given port or provision, while others can exclude it. The following description discloses many of the possible ports and provisions that can be used, however, it should be kept in mind that not every port or provision must be used or included in a given embodiment. 
     In some cases, the ECU  12902  can include a port  12904 , a port  12906 , a port  12908 , a port  12910 , a port  12912 , a port  12914 , a port  12916 , and a port  12918  for transmitting signals to and/or receiving signals from the electronic power steering system  132 , the touch steering wheel system  134 , the visual devices  140 , the audio devices  144 , the tactile devices  148 , the user input devices  152 , the infotainment system  154 , the electronic stability control system  202 , respectively. In some cases, the ECU  12902  can include a port  12920 , a port  12922 , a port  12924 , a port  12926 , a port  12928 , and a port  12930  for transmitting signals to and/or receiving signals from the antilock brake system  204 , the brake assist system  206 , the automatic brake prefill system  208 , the EPB system  210 , the low speed follow system  212 , the cruise control system  214 , respectively. 
     In some cases, the ECU  12902  can include a port  12932 , a port  12934 , a port  12936 , a port  12938 , a port  12940 , a port  12942 , a port  12944 , and a port  12946  for transmitting signals to and/or receiving signals from the automatic cruise control system  216 , the collision warning system  218 , the collision mitigation braking system  220 , the lane departure warning system  222 , the blind spot indicator system  224 , the lane keep assist system  226 , the lane monitoring system  228 , the navigation system  230 , respectively. In some cases, the ECU  12902  can include a port  12948 , a port  12950 , a port  12952 , a port  12954 , a port  12956 , a port  12958 , and a port  12960  for transmitting signals to and/or receiving signals from the hands free portable device system  232 , the climate control system  234 , the electronic pretensioning system  236 , the vehicle mode selector system  238 , the turn signal control system  240 , the headlight control system  242 , and the failure detection system  244 , respectively. 
     In some embodiments, the ECU  12902  can be configured to control one or more of vehicle systems  126 . For example, the ECU  12902  could receive output from one or more vehicle systems  126 , make control decisions, and provide instructions to one or more vehicle systems  126 . In such cases, the ECU  12902  can function as a central control unit. In other cases, however, the ECU  12902  could simply act as a relay for communication between two or more of vehicle systems  126 . In other words, in some cases, the ECU  12902  could passively transmit messages between two or more of vehicle systems  126  without making any control decisions. 
     As discussed herein, the methods and systems allow for communication between vehicle systems.  FIG. 130  illustrates a schematic view of an embodiment of a first vehicle system  13002  and a second vehicle system  13004 , which are in communication via a network  13006 . Generally, network  13006  can be any kind of network known in the art. Examples of different kinds of networks include, but are not limited to local area networks, wide area networks, personal area networks, controller area networks as well as any other kinds of networks. In some cases, network  13006  can be a wired network. In other cases, network  13006  can be a wireless network. 
     For purposes of clarity, only two vehicle systems are shown connected to one another using a network. However, in other cases, any other number of vehicle systems could be connected using one or more networks. For example, in some embodiments, some or all of the vehicle systems  126 , shown in  FIG. 129 , including the response system  12900  and ECU  12902 , could be connected through a network. In such a situation, each vehicle system of the vehicle systems  126  can function as a node within the network. Moreover, using a networked configuration allows hazard information to be shared between each system of the vehicle systems  126 . In some cases, a vehicle system can be configured to control another vehicle system by transmitting instructions over a network. It is understood that the network system described in  FIG. 130  can be implemented with the systems and methods discussed herein for communicating information between more than one vehicle system. 
     Referring now to  FIG. 131 , an embodiment of a process for generally controlling one or more vehicle systems in a motor vehicle is shown. In some embodiments, some of the following steps could be accomplished by a response system  12900  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  12902  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIG. 129 , including the response system  12900 . 
     In step  13102 , the ECU  12902  can communicate with one or more of vehicle systems  126 . In some cases, the ECU  12902  can receive various kinds of information from vehicle systems  126  related to driving conditions, vehicle operating conditions, target vehicle or target object information, hazard information, as well as any other information. In some cases, each system of vehicle systems  126  can transmit different kinds of information since each system can utilize different kinds of information while operating. For example, the cruise control system  214  can provide the ECU  12902  with information related to a current vehicle speed. However, the electronic power steering system  132  may not monitor vehicle speed and therefore may not transmit vehicle speed information to the ECU  12902 . In some cases, some systems may send overlapping information. For example, the multiple systems of vehicle systems  126  may transmit information gathered from remote sensing devices. Therefore, it will be understood that information received by the ECU  12902  from a particular vehicle system may or may not be unique relative to information received from other systems of vehicle systems  126 . 
     In some cases, the ECU  12902  can receive driver state information (such as a level of drowsiness as characterized using a driver state index). In some cases, driver state information could be received directly from vehicle systems  126 . In other cases, driver state information could be received from monitoring devices or systems as discussed above. It is understood that communication as discussed in step  13102  can be facilitated by the communication network  13006  shown in  FIG. 130  above. 
     Referring again to  FIG. 131 , in step  13104 , the ECU  12902  can evaluate potential hazards. In some cases, the potential hazard can be evaluated as a vehicular state. In some cases, one or more vehicle systems  126  can transmit hazard information to ECU  12902  that can characterize a given target vehicle, object or driving situation as a hazard. In other cases, the ECU  12902  can interpret data provided by one or more vehicle systems  126  to determine if there are any potential hazards. In other words, the characterization of a vehicle, object, or driving situation as a hazard can be accomplished within an individual vehicle system of vehicle systems  126  and/or by the ECU  12902 . In some cases, a target vehicle, object or driving situation can be considered a hazard by one system but not another. For example, information about a target vehicle traveling beside the host vehicle can be used by the blind spot indicator system  224  to categorize the target vehicle as a hazard, but using the same information the low speed follow system  212  may not categorize the target vehicle as a hazard, since the low speed follow system  212  is primarily concerned with other vehicles located in front of the host vehicle. 
     In situations where the ECU  12902  determines that a potential hazard exists, the ECU  12902  can decide to modify the control of one or more vehicle systems  126  in response to the potential hazard at step  13106 . In one embodiment, where the ECU  12902  determines that a potential hazard does not exist, the ECU  12902  can decide to modify and/or not modify the control of one or more vehicle systems  126 . In some cases, the ECU  12902  can modify the control of one vehicle system. In other cases, the ECU  12902  can modify the control of two or more vehicle systems substantially simultaneously. In some cases, the ECU  12902  can coordinate the modified operation of two or more vehicle systems in order to enhance the response of a vehicle to a potential hazard. For example, simultaneously modifying the operation of vehicle systems that passively warn a driver of hazards and vehicle systems that actively change some parameter of vehicle operation (such as speed, braking levels, deactivating cruise control, etc.) according to driver state can provide a more robust response to hazards. This configuration allows the ECU  12902  to provide responses that supply just the right level of assistance depending on the state of the driver. 
     In some embodiments, the ECU  12902  can maintain full control over all vehicle systems  126 . In other embodiments, however, some vehicle systems  126  can operate independently with some input or control from the ECU  12902 . In such cases, the ECU  12902  can receive information from systems that are already in a modified control mode, and can subsequently modify the operation of additional vehicle systems to provide a coordinated response to a potential hazard. Moreover, by analyzing the response of some vehicle systems, ECU  12902  can override automatic control of other vehicle systems in response to a hazard. For example if a first vehicle system detects a hazard, but a second vehicle system does not, the ECU  12902  can instruct the second vehicle system to behave as though a hazard is present. As another example if a first vehicle system detects a hazard, but a second vehicle system does not, the ECU  12902  can instruct the first vehicle system to behave as though a hazard is not present. As a further example, if a first or a second vehicle system detects a hazard, but the driver state indicates the driver is attentive or knows (e.g., confirms) the hazard is present, the ECU  12902  can instruct the first and/or second vehicle system to behave as though the hazard is not present. 
     In embodiments where the ECU  12902  acts in a passive manner, ECU  12902  can function to receive hazard warnings from one vehicle system and transmit the hazard warnings to one or more additional vehicle systems  126 . With this configuration, the ECU  12902  can distribute hazard warnings between two or more of the vehicle systems  126  to enhance the operation of the response system  12900 . 
     Referring now to  FIGS. 132 and 133 , other embodiments of processes for communicating information and controlling one or more vehicle systems in a motor vehicle are illustrated. The methods described with reference to  FIGS. 132 and 133  generally describe modifying one or more vehicle systems, wherein the modifying can include modifying the control of the vehicle at different levels, for example, no control, partial control, or full control of a vehicle system. In some embodiments, some of the following steps could be accomplished by a response system  12900  of the motor vehicle  100 . In some cases, some of the following steps can be accomplished by an ECU  12902  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIG. 129 , including the response system  12900 . 
     Referring now to  FIG. 132 , at step  13202 , the ECU  12902  can receive information from one or more of vehicle systems  126  and/or monitoring systems  300 . This information can include sensed information as well as information characterizing the operation of vehicle systems  126 . For example, in some cases, the ECU  12902  could receive information from electronic stability control system  202  including wheel speed information, acceleration information, yaw rate information as well as other kinds of sensed information utilized by electronic stability control system  202 . Additionally, in some cases, the ECU  12902  could receive information related to the operating state of electronic stability control system  202 . As an example, the ECU  12902  could receive information indicating that the electronic stability control system  202  is actively facilitating control of the vehicle by actuating one or more wheel brakes. 
     In some embodiments, the ECU  12902  can optionally receive driver state information from one or more of the vehicle systems  126  and/or monitoring systems  300  during step  13202 . For example, one or more of the vehicle systems  126  can determine a driver state index for a driver. In some cases, multiple different systems can send the ECU  12902  a driver state index or other driver state information. In other embodiments, the ECU  12902  can receive driver state information directly from one or more monitoring systems  300  rather than receiving driver state information from one of vehicle systems  126 . In such cases, the ECU  12902  can be configured to determine a driver state index according to the monitoring information. In still other embodiments, driver state information can be received from the vehicle systems  126  as well as independently from one or more monitoring systems  300 . 
     In step  13204 , the ECU  12902  can detect a potential hazard. In some embodiments, a hazard can be detected through information provided by one or more vehicle systems  126 . In some embodiments, the hazard is referred to as a vehicular state. As an example, the ECU  12902  can receive information from the blind spot indicator system  224  indicating that a target vehicle is traveling in the blind spot of the host vehicle. In this situation, the ECU  12902  can identify the target vehicle as a potential hazard. As another example, the ECU  12902  could receive information from collision warning system  218  indicating that a target vehicle can be traveling through an intersection approximately simultaneously with the host vehicle. In this situation, the ECU  12902  can identify the target vehicle as a potential hazard. It will be understood that a target vehicle or object could be designated as a potential hazard by one or more of vehicle systems  126  or by the ECU  12902 . In other words, in some cases, a vehicle system determines that an object is a potential hazard and sends this information to the ECU  12902 . In other cases, the ECU  12902  receives information about a target object from a vehicle system and determines if the object should be identified as a potential hazard. 
     After identifying a potential hazard, in step  13206 , the ECU  12902  can determine a risk level for the potential hazard. In other words, in step  13206 , the ECU  12902  determines how much of a risk a potential hazard poses. This step allows the ECU  12902  to make control decisions about potential hazards that pose the greatest risk and can reduce the likelihood of the ECU  12902  modifying operation of one or more vehicle systems in response to a target vehicle, object, or driving situation that does not pose much of a risk to a vehicle. Details of a method of determining a risk level for a potential hazard are discussed below and shown in  FIG. 133 , which provides several possible sub-steps associated with step  13206 . 
     The risk level determined in step  13206  could be characterized in any manner. In some cases, the risk level could be characterized by a range of numeric values (for example, 1 to 10, with 1 being the lowest risk and 10 being the highest risk). In some cases, the risk level could be characterized as either “high risk” or “low risk.” In still other cases, the risk level could be characterized in any other manner. 
     In step  13208 , the ECU  12902  determines if the risk level associated with a potential hazard is high. In some cases, the ECU  12902  determines if the risk level is high based on a predetermined risk level. For example, in situations where a 1 to 10 risk level scale is used, the predetermined risk level could be 8, so that any hazard having a risk level at 8 or above is identified to have a high risk level. In other cases, the ECU  12902  could use any other method to determine if the risk level identified during step  13206  is high enough to require further action. 
     If the risk level is not high, the ECU  12902  returns to step  13202 . Otherwise, the ECU  12902  proceeds to step  13210 . In step  13210 , the ECU  12902  can select one or more of the vehicle systems  126  to be modified in response to a potential hazard. In some cases, the ECU  12902  could select a single vehicle system. In other cases, the ECU  12902  could select two or more vehicle systems. Moreover, as discussed in further detail below, the ECU  12902  can coordinate the operation of two different vehicle systems of the vehicle systems  126 , so that each system is modified in an appropriate manner to enhance the ability of a drowsy driver to maintain good control of a vehicle. This allows some systems to enhance the operation and control of other systems. 
     In step  13212 , the ECU  12902  can determine the type of modified control for each system selected in step  13210 . In some cases, the ECU  12902  can use the driver state index of a driver to determine the control type. For example, as seen in  FIG. 132 , the ECU  12902  can use the driver state index determined in step  13214  to select a control type. An example of various control type settings according to the driver state index is shown in the form of lookup table  13216 . For example, when the driver state index is 1 or 2, the control type can be set to “no control.” In these situations, the ECU  12902  may not adjust the operation of any of vehicle systems  126 . When the driver state index of the driver is 3, which can indicate that the driver is somewhat drowsy, the ECU  12902  can set the control of one or more of the vehicle systems  126  to “partial control.” In the partial control mode, the control of one or more vehicle systems  126  can be slightly modified to help enhance drivability. When the driver state index of the driver is 4, which can indicate that the driver is very drowsy or even asleep, the ECU  12902  can set the control of one or more of the vehicle systems  126  to “full control.” In the “full control” mode, the ECU  12902  can substantially modify the control of one or more of the vehicle systems  126 . Using this arrangement, a vehicle system can be configured to provide additional assistance to a driver when the driver is very drowsy, some assistance when the driver is somewhat drowsy, and little to no assistance when the driver is relatively alert (not drowsy). In step  13218 , the ECU  12902  can modify the control of one or more selected systems of the vehicle systems  126 . In some cases, a vehicle system can be controlled according to the control type determined during step  13212 . 
       FIG. 133  illustrates one embodiment of a process for determining the risk level for a potential hazard. It will be understood that this method is only intended to be exemplary and in other embodiments, any other method could be used to evaluate the risk level for a potential hazard. In step  13302 , the ECU  12902  can determine the relative distance between the potential hazard and the host vehicle. In some cases, the ECU  12902  can determine the relative distance between the host vehicle and the hazard using a remote sensing device, including radar, lidar, cameras, as well as any other remote sensing devices. In other cases, the ECU  12902  could use GPS information for the host vehicle and the hazard to calculate a relative distance. For example, the GPS position of the host vehicle can be received using a GPS receiver within the host vehicle. In situations where the hazard is another vehicle, GPS information for the hazard could be obtained using a vehicle communication network or other system for receiving remote vehicle information. 
     Next, in step  13304 , the ECU  12902  can determine the host vehicle trajectory relative to the hazard. In step  13306 , the ECU  12902  can determine the hazard trajectory relative to the host vehicle. In some cases, these trajectories can be estimated using remote sensing devices. In other cases, these trajectories can be estimated from real-time GPS position information. In still other cases, any other methods for determining trajectories for a host vehicle and a hazard (such as a remote vehicle) could be used. 
     By determining the relative distances as well as relative trajectories of the host vehicle and hazard, the ECU  12902  can determine the probability that the host vehicle will encounter the hazard. In particular, using the relative distance as well as trajectory information, the ECU  12902  can estimate the probability that the host vehicle and the hazard can eventually collide. In step  13308 , the ECU  12902  can determine the risk level for the hazard, which is an indicator of the likelihood that the host vehicle will encounter the hazard. In some cases, the ECU  12902  classifies the potential hazard as presenting a high risk or a low risk to the host vehicle. 
       FIG. 134  illustrates an embodiment of a process for controlling one or more vehicle systems in response to potential hazards in situations where the vehicle systems can be in direct communication with one another, such as through a network. In some cases, certain steps of the process are associated with a first vehicle system  13402  and certain steps are associated with a second vehicle system  13404 . In some cases, steps associated with the first vehicle system  13402  are performed by the first vehicle system  13402  and steps associated with the second vehicle system  13404  are performed by the second vehicle system  13404 . However, in other cases, some steps associated with the first vehicle system  13402  can be performed by the second vehicle system  13404  or some other resource. Likewise, in other cases, some steps associated with second vehicle system  13404  can be performed by the first vehicle system  13402  or some other resource. In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. 
     In step  13406 , the first vehicle system  13402  can receive operating information. This information can include any kind of information including sensed information as well as information characterizing the operation of vehicle systems  126 . In one embodiment, the first vehicle system  13402  receives operating information required for the normal operation of the first vehicle system  13402 . For example, in an embodiment where the first vehicle system  13402  is a blind spot indicator system  224 , the first vehicle system  13402  could receive information from a camera monitoring the blind spot region beside the vehicle, information about any tracked objects within or near the blind spot region, current vehicle speed, as well as any other information used to operate blind spot indicator system  224 . 
     In step  13408 , the first vehicle system  13402  can determine the driver state index of a driver. This information could be determined according to various monitoring information received from one or monitoring devices, such as cameras, position sensors (such as head position sensors) autonomic monitoring systems or any other devices. In some cases, the driver state index could also be determined using information from a vehicle system. For example, a system could determine that a driver is drowsy by monitoring outputs from a lane departure warning system  222 , as previously discussed. 
     In step  13410 , the first vehicle system  13402  can detect a potential hazard. In some cases, the hazard is referred to as a vehicular state. In some embodiments, a hazard can be detected through information provided to the first vehicle system  13402 . For example, in the case where the first vehicle system  13402  is an automatic cruise control system, the first vehicle system  13402  can be configured to receive headway distance information through a camera, lidar, radar or other remote sensing device. In such cases, the first vehicle system  13402  can detect remote objects, such as a vehicle, using similar remote sensing techniques. In other cases, a hazard can be detected through information provided by any other vehicle system. 
     After identifying a potential hazard, in step  13412 , the first vehicle system  13402  can determine a risk level for the potential hazard. In other words, in step  13412 , the first vehicle system  13402  determines how much of a risk a potential hazard poses. This step allows the first vehicle system  13402  to make control decisions about potential hazards that pose the greatest risk and can reduce the likelihood that the operation of the first vehicle system  13402  will be modified in response to a target vehicle, object, or driving situation that does not pose much of a risk to a vehicle. Details of a method of determining a risk level for a potential hazard have been discussed previously. 
     In step  13414 , the first vehicle system  13402  determines if the risk level associated with a potential hazard is high. In some cases, the first vehicle system  13402  determines if the risk level is high based on a predetermined risk level. For example, in situations where a 1 to 10 risk level scale is used, the predetermined risk level could be 8, so that any hazard having a risk level at 8 or above is identified to have a high risk level. In other cases, the first vehicle system  13402  could use any other method to determine if the risk level identified during step  13412  is high enough to require further action. 
     If the risk level is high, the first vehicle system  13402  proceeds to step  13416 . Otherwise, the first vehicle system  13402  returns to step  13406 . In step  13416 , the control of the first vehicle system  13402  can be modified according to the current driver state index. In step  13418 , the first vehicle system  13402  determines if the second vehicle system  13404  should be informed of the potential hazard detected by the first vehicle system  13402 . In some cases, the second vehicle system  13404  can be informed of any hazards encountered by the first vehicle system  13402 . In other cases, however, one or more criteria could be used to determine if the second vehicle system  13404  should be notified of a potential hazard detected by the first vehicle system  13402 . In embodiments where multiple vehicle systems are in communication with one another, a vehicle system detecting a hazard could send information warning all the other vehicle systems of the hazard. 
     In step  13420 , the first vehicle system  13402  checks to see if the second vehicle system  13404  should be informed of the potential hazard. If second vehicle system should not be informed, the first vehicle system  13402  returns to step  13406 . Otherwise, the first vehicle system  13402  proceeds to step  13422  where information is submitted to the second vehicle system  13404 . In some cases, the submitted information includes a warning and/or instructions for the second vehicle system  13404  to check for a potential hazard. 
     In step  13424 , the second vehicle system  13404  receives information from the first vehicle system  13402 . This information can include information related to the potential hazard as well as any other information. In some instances, the information can include instructions or a request for the second vehicle system  13404  to check for any potential hazards. In some cases, the information can include operating information related to the first vehicle system  13402 . Next, in step  13426 , the second vehicle system  13404  can retrieve operating information. This operating information could include any type of information used during the operation of the second vehicle system  13404 , as well as operating information from any other system or device of the motor vehicle. 
     In step  13428 , the second vehicle system  13404  can check for potential hazards as advised or instructed by the first vehicle system  13402 . Then, in step  13430 , the second vehicle system  13404  can determine the risk level for the potential hazard using methods similar to those used by the first vehicle system  13402  during step  13412 . In step  13432 , the second vehicle system  13404  can determine if the risk level is high. If not, the second vehicle system  13404  returns to step  13426 . Otherwise, the second vehicle system  13404  proceeds to step  13434 . 
     In step  13434 , the driver state index of the driver can be determined. This can be determined using any of the methods described above. Moreover, in some cases, the driver state index can be retrieved directly from the first vehicle system  13402 . In step  13436 , the control of second vehicle system  13404  is modified according to the driver state index. This method can facilitate better system response to a hazard by coordinating the operation of multiple vehicle systems and modifying the operation of each system according to the driver state index. 
     As discussed above, the processes for controlling one or more vehicle systems can include communication (e.g., intra-vehicle communication) between various vehicle systems. The vehicle systems can independently collect information, determine hazards, determine risk levels, determine driver states, modify control of vehicle systems, and share this information with other vehicle systems. This allows the vehicle systems to work in coordination with one another.  FIG. 135A  illustrates another embodiment of a process for controlling one or more vehicle systems in a motor vehicle including a first vehicle system  13502  and a second vehicle system  13504 . In some embodiments, some of the following steps could be accomplished by a response system  12900  of the motor vehicle  100 . In some cases, some of the following steps can be accomplished by an ECU  12902  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. 
     At step  13508 , the method includes receiving information from a first vehicle system  13502 . In some embodiments, the method can also include receiving information from monitoring systems and/or other various vehicle systems (e.g., physiological information, behavioral information, vehicle information). At step  13510 , the method includes detecting a potential hazard based on the information from step  13508 . At step  13512 , the method includes detecting a risk level associated with the potential hazard. 
     At step  13514 , the method includes determining a driver state, for example, based on information from the first vehicle system  13502  and/or the second vehicle system  13504 . For example, information can be received from the second vehicle system  13504  at step  13522 . In some embodiments, the information received from the second vehicle system  13504  can include physiological information, behavioral information, and/or vehicle information. As discussed above, determining a driver state can include determining a driver state index. 
     At step  13516 , the method includes modifying control of the first vehicle system  13502  based on the driver state. Further, at step  13520 , the first vehicle system  13502  submits information to the second vehicle system  13504 . The information can include information about the potential hazard, the risk level, the driver state, and the control of the first vehicle system. The second vehicle system  13504  receives the information from the first vehicle system  13502  at step  13524 . Further, at step  13526 , the method includes modifying control of the second vehicle system  13504  based on the information from the first vehicle system  13502  and the information from the second vehicle system  13504 . 
     Although  FIG. 135A  illustrates two vehicle systems in communication with each other, more than two vehicle systems can be implemented. For example,  FIG. 135B  illustrates three vehicle systems for controlling one or more vehicle systems in a motor vehicle. For simplicity, like numerals in  FIGS. 135A and 135B  represent like elements. In  FIG. 135B  information from all three vehicle systems can be used to modify control of the one or more vehicle systems. For example, at step  13514 , the driver state can be based on information from the first vehicle system  13502 , the second vehicle system  13504  and/or the third vehicle system  13506 . Further, at step  13520 , in addition to submitting information to the second vehicle system  13504 , the method can include submitting information to the third vehicle system  13506 . 
     At step  13528 , the method can also include submitting information from the second vehicle system  13504  to the third vehicle system  13506 . At step  13530 , the method includes receiving information from the third vehicle system  13506 . At step  13532 , the method includes receiving information from the first vehicle system  13502  and/or the second vehicle system  13504 . At step  13534 , the method includes modifying control of the third vehicle system  13506  based on information from the first vehicle system  13502  and/or the second vehicle system  13504 . It is appreciated that the communication processes discussed in  FIGS. 135A and 135B  can be used for any of the methods and systems discussed herein for modifying control of vehicle systems. 
       FIGS. 136A, 136B, 137A, and 137B  are illustrative examples of controlling one or more vehicle systems in response to potential hazards in situations where the vehicle systems can be in direct communication with one another (e.g., intra-vehicle communication). More specifically,  FIGS. 136A, 136B, 137A, and 137B  illustrate exemplary embodiments of various operating modes of the blind spot indicator system  224  ( FIG. 2 ) and the electronic power steering system  132  ( FIG. 2 ). Referring now to  FIG. 136A , in this embodiment, the motor vehicle  100  is traveling on a roadway  13602 . The blind spot indicator system  224  can be used to monitor any objects traveling within a blind spot monitoring zone  13604 . For example, in the current embodiment, the blind spot indicator system  224  can determine that no object is inside of the blind spot monitoring zone  13604 . In particular, a target vehicle  13606  is just outside of the blind spot monitoring zone  13604 . In this case, no alert is sent to the driver  102 . 
     In  FIG. 136B , to change lanes, a driver  102  can turn the wheel  134  (e.g., a touch steering wheel  134 ). In this situation, with a driver  102  fully alert, the blind spot monitoring zone  13604  has a default size appropriate to the amount of awareness of an alert driver. Since the target vehicle  13606  is not inside the blind spot monitoring zone  13604  in  FIG. 136B , no warnings are generated and the driver  102  has complete freedom to steer the motor vehicle  100  into the adjacent lane. 
     Referring now to  FIGS. 137A and 137B , the motor vehicle  100  is shown driving on a roadway  13702 . As the driver  102  becomes drowsy, as shown schematically in  FIGS. 137A and 137B , the size of a blind spot monitoring zone  13704  (e.g., the blind spot monitoring zone  13604 ) is increased. At this point, a target vehicle  13706  is now in the enlarged monitoring zone  13704 , which results in a warning  13708 , generated by the blind spot indicator system  224 . Moreover, as seen in  FIG. 137B , to prevent the user from turning into the adjacent lane and potentially colliding with the target vehicle  13706 , the electronic power steering system  132  can generate a counter torque  13710  to prevent the driver  102  from turning the wheel  134 . This counter torque  13710  can be provided at a level to match the torque applied by the driver  102 , in an opposing direction, so that the net torque on the wheel  134  is approximately zero. This helps keep the motor vehicle  100  from entering the adjacent lane when a target vehicle is traveling in the blind spot of the driver  102 . In some cases, the warning indicator  13712  can also be activated to inform a driver that vehicle control has been modified by one or more vehicle systems. Using this arrangement, the blind spot indicator system  224  and the electronic power steering system  132  can operate in a coordinated manner to warn a driver of a hazard and further control the vehicle to help avoid a potential collision. 
       FIG. 138  illustrates an embodiment of a process of operating a blind spot indicator system and an electronic power steering system in response to driver state. In some embodiments, some of the following steps could be accomplished by a response system  12900  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  12902  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIG. 129 . 
     In step  13802 , the ECU  12902  can receive object information. The object could be a vehicle or any other object that can be tracked. In some cases, for example, the object could be pedestrian or biker. In step  13804 , ECU  12902  can detect a potential hazard. Next, in step  13806 , the ECU  12902  can determine if the object poses a hazard. A method of determining if an object poses a hazard for a vehicle has been discussed above and shown in  FIGS. 106 and 107 . In particular, step  10604 , step  10606 , step  10608 , and step  10610  of  FIG. 106  as well as each of the steps shown in  FIG. 107  provide an exemplary method to determine if the object poses a hazard. In some cases, the step of determining if the object poses a hazard includes checking the driver state index of a driver as discussed and shown in  FIGS. 106 and 107 . 
     In step  13808 , the ECU  12902  can determine the warning type, frequency, and intensity of an alert to warn the driver. In some cases, determining the warning type, frequency and intensity can proceed in a similar manner to step  10612  and step  10614  of  FIG. 106 . Next, the ECU  12902  can activate a blind spot warning indicator in step  13810 , to alert a driver of a potential hazard. 
     In step  13812 , the ECU  12902  determines if the object is still inside the blind spot monitoring zone. This step allows for the possibility that a driver has observed the blind spot warning indicator and adjusted the vehicle so that there is no longer an object in the blind spot. 
     If there is no longer an object in the blind spot monitoring zone, ECU  12902  can return to step  13802 . Otherwise, the ECU  12902  can proceed to step  13814 . In step  13814 , the ECU  12902  determines the trajectory of the tracked object. The trajectory of the object can be determined using any methods including remote sensing as well as GPS based methods. 
     In step  13816 , the ECU  12902  determines the relative distance between the motor vehicle and the tracked object. In step  13818 , the ECU  12902  determines if a crash is likely between the vehicle and the tracked object. If not, the ECU  12902  returns to step  13812  to continue monitoring the tracked object. Otherwise, the ECU  12902  proceeds to step  13820  to determine the type of power steering control to be used to help prevent the driver from changing lanes. 
     In parallel with step  13820 , the ECU  12902  can determine driver state index  13822  and use look-up table  13824  to select the appropriate type of control. For example, if the driver state index is 1 or 2, meaning the driver is relatively alert, no control is performed since it is assumed a driver will be aware of the potential threat posed by the object. If the driver state index has a value of 3, meaning the driver is somewhat drowsy, some partial steering feedback is provided to help resist any attempt by the user to turn the vehicle into the adjacent lane with the tracked object. If the driver state index has a value of 4, meaning the driver is very drowsy, full steering feedback is provided to substantially prevent the driver from moving into the adjacent lane. 
     After the power steering control type has been selected, the ECU  12902  can control the power steering system accordingly in step  13826 . In some cases, at step  13828 , the ECU  12902  can also activate a control warning to alert the driver that one or more vehicle systems are assisting with vehicle control. 
       FIG. 139  illustrates a schematic view of a further operating mode of the blind spot indicator system  224  and a brake control system. It should be understood that the brake control system could be any vehicle system with braking functions controlled by the ECU  12902 . For example, the brake control system can include, but is not limited to, an electronic stability control system  202 , an antilock brake system  204 , a brake assist system  206 , an automatic brake prefill system  208 , a low speed follow system  212 , an automatic cruise control system  216 , a collision warning system  218 , or a collision mitigation braking system  220 . 
     In the illustrated embodiment, the blind spot indicator system  224  includes provisions for cross-traffic alert, as is known in the art, that detects objects in the blind spot during normal driving and objects approaching from the sides of the vehicle (i.e., cross-traffic) when the vehicle is moving forward or reverse direction. For exemplary purposes,  FIGS. 138 and 139  will be described with reference to cross-traffic when the vehicle is in a reverse gear (i.e., when reversing out of a parking spot). However, it is appreciated that the systems and methods described herein can also be applicable to cross-traffic in front of the vehicle when the vehicle is moving in a forward direction. 
     Referring now to  FIG. 139 , the motor vehicle  100  is illustrated in a parking situation  13902  where the blind spot indicator system  224  and the brake control system, alone or in combination, can be used to improve a cross-traffic alert process. The blind spot indicator system  224  is used to monitor any objects, for example, a first target vehicle  13904  and/or a second target vehicle  13906 , traveling (i.e., approaching from the sides of the motor vehicle  100 ) within a blind spot monitoring zone  13908 . As discussed above, it is understood that the blind spot monitoring zone  13908  can also be located in front of the motor vehicle  100  for monitoring objects approaching from the sides of the motor vehicle  100  when the motor vehicle  100  in a forward direction. It is appreciated that the blind spot indicator system  224  can also include the functions described above with respect to  FIGS. 135-138 . For example, the blind spot monitoring zone  13908  can increase or decrease in size based on the amount of awareness of a driver of the motor vehicle  100 . Moreover, it is appreciated that the motor vehicle  100  can be traveling in reverse or forward at an angle (e.g., a parking angle) rather than a 90 degree angle as shown in  FIG. 139 . 
       FIG. 140  illustrates an embodiment of a process of operating a blind spot indicator system including cross-traffic alert with a brake control system. In some embodiments, some of the following steps could be accomplished by a response system  12900  of a motor vehicle. In some cases, some of the following steps can be accomplished by an ECU  12902  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. For purposes of reference, the following method discusses components shown in  FIG. 78 . 
     In step  14002 , the ECU  12902  can receive object information. The object could be a vehicle or any other object that can be tracked. In some cases, for example, the object could also be pedestrian or biker. With regards to a cross-traffic alert system, the object can be a vehicle (i.e., a first and second target vehicle  13904 ,  13906 ) in the potential path of a vehicle put in reverse gear. In step  14004 , ECU  12902  can detect a potential hazard. Next, in step  14006 , the ECU  12902  can determine if the object poses a hazard. A method of determining if an object poses a hazard for a vehicle has been discussed above and shown in  FIGS. 106 and 107 . In particular, step  10604 , step  10606 , step  10608 , and step  10610  of  FIG. 106  as well as each of the steps shown in  FIG. 107  provide an exemplary method to determine if the object poses a hazard. In some cases, the step of determining if the object poses a hazard includes checking the driver state index of a driver as discussed and shown in  FIGS. 106 and 107 . 
     In step  14008 , the ECU  12902  can determine the warning type, frequency, and intensity of an alert to warn the driver. In some cases, determining the warning type, frequency and intensity can proceed in a similar manner to step  10612  and step  10614  of  FIG. 106 . Next, the ECU  12902  can activate a blind spot warning indicator in step  14010 , to alert a driver of a potential hazard. 
     In step  14012 , the ECU  12902  determines if the object is still inside the blind spot monitoring zone. This step allows for the possibility that a driver has observed the blind spot warning indicator and adjusted the vehicle so that there is no longer an object in the blind spot. 
     If there is no longer an object in the blind spot monitoring zone, ECU  12902  can return to step  14002 . Otherwise, the ECU  12902  can proceed to step  14014 . In step  14014 , the ECU  12902  determines the trajectory of the tracked object. The trajectory of the object can be determined using any methods including remote sensing as well as GPS based methods. The trajectory can also be based on a parking angle relative to the vehicle and the object, when the vehicle is put in a reverse gear and is not travelling at a 90 degree angle. 
     In step  14016 , the ECU  12902  determines the relative distance between the motor vehicle and the tracked object. In step  14018 , the ECU  12902  determines if a crash is likely between the vehicle and the tracked object. If not, the ECU  12902  returns to step  14012  to continue monitoring the tracked object. Otherwise, the ECU  12902  proceeds to step  14020  to determine the type of brake control to be used to help prevent the driver from collision with the tracked object. 
     In parallel with step  14020 , the ECU  12902  can determine driver state index  14022  and use look-up table  14024  to select the appropriate type of brake control. For example, if the driver state index is 1 or 2, meaning the driver is relatively alert, no control is performed since it is assumed a driver will be aware of the potential threat posed by the object. If the driver state index has a value of 3, meaning the driver is somewhat drowsy, some partial brake control is provided to assist the driver. If the driver state index has a value of 4, meaning the driver is very drowsy, full brake control provided to substantially prevent the driver from moving into the cross-traffic. Brake control can include, but is not limited to, increasing or decreasing breaking pressure, or pre-charging or prefilling the brakes. 
     After the brake control type has been selected, the ECU  12902  can control the brake control system accordingly in step  14026 . In some cases, at step  14028 , the ECU  12902  can also activate a control warning to alert the driver that one or more vehicle systems are assisting with vehicle control. 
     It will be appreciated that the exemplary operational response and intra-vehicle communication of one more vehicle systems can also apply to methods and systems utilizing a plurality of driver states and a combined driver state. Thus, the driver state index discussed in the exemplary operational response and intra-vehicle communication can be substituted with more than one driver state and/or a combined driver state index as determined by the methods and systems discussed in Section III. 
       FIGS. 131-135A, 135B  discussed above, generally illustrate provisions for intra-vehicle communication and control and modifying various different vehicle systems in response to driver state based on one or more of a hazard, a risk level, a driver state and information from different vehicle systems. These embodiments provide for varied control of the vehicle and vehicle systems. As mentioned above, in some embodiments, the processes described above for controlling one or more vehicle systems can be used to provide semi-autonomous or fully autonomous control to the motor vehicle. In some embodiments, the semi-autonomous or fully autonomous controls provide intuitive convenience controls to the driver. In other embodiments, the semi-autonomous or fully autonomous controls provide safety controls (e.g., to avoid potential collisions and/or hazards) to the driver. It is understood that any of the systems and methods described above for determining driver states and modifying control of vehicle systems can be implemented in whole or in part with the systems and methods described herein. 
     The exemplary systems and methods discussed herein related to automatic control of vehicle systems, could in some embodiments, include a determination and/or check for an auto control mode status. As discussed above, the motor vehicle  100  can include a vehicle mode selector system  238  that modifies driving performance according to preset parameters related to the mode selected. In one embodiment, the modes provided by the vehicle mode selector system  238  include an auto control mode status. The auto control mode status can be managed, activated and/or deactivated via the vehicle mode selector system  238  and provides for a semi and/or fully automatic (e.g., autonomous) control of vehicle systems. In some embodiments, the auto control mode can be activated and/or deactivated by the driver. Accordingly, the driver has control as to whether automatic control of the vehicle systems can occur. In other embodiments, the auto control mode can be automatically activated by one or more vehicle systems, for example, based on driver state. Although not every method and system discussed herein provides for a determination and/or check for an auto control mode status, it is appreciated that the methods and systems discussed herein can allow for such determination and/or check. 
     Referring now to  FIG. 141 , an embodiment of a process for controlling one or more vehicle systems including auto control is illustrated. In some embodiments, some of the following steps could be accomplished by a response system  12900  of the motor vehicle  100 . In some cases, some of the following steps can be accomplished by an ECU  12902  of the motor vehicle  100 . In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. 
     At step  14102 , the method includes receiving monitoring information. For example, the ECU  12902  can receive monitoring information from one or more vehicle systems  126  and/or monitoring systems  300 . As discussed above, monitoring information can include physiological information, behavioral information and vehicular-sensed information, from various vehicle systems  126  and/or monitoring systems  300 . At step  14104 , the method includes detecting a potential hazard based on the monitoring information. In some embodiments, more than one potential hazard can be detected at step  14104 . In some embodiments, the ECU  12902  can detect the hazard based on information provided by one or more vehicle systems  126  and/or monitoring systems  300  (e.g., based on monitoring information from step  14102 ). In some embodiments, the hazard is referred to as a vehicular state. As an illustrative example, the ECU  12902  can receive information from the blind spot indicator system  224  indicating that a target vehicle is traveling in the blind spot monitoring zone of the motor vehicle  100 . In this situation, the ECU  12902  identifies the target vehicle as a potential hazard. It is understood that any of the systems and methods for detecting a potential hazard discussed above with  FIGS. 131-138  can be implemented. In some embodiments discussed herein, step  14104  is optional. Further, in other embodiments, step  14104  could be performed after step  14110 . 
     At step  14106 , the method includes determining a risk level associated with the potential hazard. In other words, in step  14106 , the ECU  12902  determines how much of a risk a potential hazard poses. It is understood that any of the systems and methods for determining a risk level discussed above with  FIGS. 131-138  can be implemented. Further, in some embodiments, step  14106  is optional. In other embodiments, step  14106  could be performed after step  14110 . 
     At step  14108 , the method includes determining an auto control status. For example, the ECU  12902  can receive information from the vehicle mode selector system  238  (e.g., at step  14102 ) to determine if an auto control status is set to ON. If the auto control status is determined to be ON, semi and/or full autonomous control of the motor vehicle  100  and/or one or more vehicle systems  126  is enabled. In some embodiments, step  14108  is optional. Further, in other embodiments, step  14108  could be performed after step  14110 . 
     At step  14110 , the ECU  12902  can determine a driver state and/or driver state index based on the monitoring information. The driver state can be determined in various ways as discussed in Section IV. In some embodiments, the driver state is based on monitoring information from one or more vehicle systems  126  and/or monitoring systems  300 . The driver state, in some embodiments, characterizes the attentiveness (e.g., alertness) of the driver in relation to the potential hazard detected. In some embodiments, determining a driver state can also include determining if the driver is distracted and/or drowsy. 
     In one embodiment, at step  14110 , the ECU  12902  can use the driver state and/or driver state index to determine a control type (e.g., a system status) as discussed in  FIG. 132  at step  13214  using the look-up table  13216 . Other exemplary control types will be discussed herein with reference to  FIGS. 143A, 143B, 143C, and 143D . At step  14112 , the ECU  12902  modifies control of one or more vehicle systems based at least in part on the driver state and/or the driver state index. In some embodiments, one or more vehicle systems are modified based at least in part on the driver state and/or the driver state index, the potential hazard, the risk level, and/or the auto control status. Further, the vehicle systems can be modified at step  14112  based on a control type and/or system status selected according to the driver state. 
     Another embodiment of a process for controlling one or more vehicle systems in a motor vehicle including auto control is shown in  FIG. 142 . At step  14202 , the method includes receiving monitoring information. For example, the ECU  12902  can receive monitoring information from one or more vehicle systems  126  and/or monitoring systems  300  as discussed above with  FIG. 141  at step  14102 . At step  14204 , the method includes determining if an auto control status is set to ON. For example, the ECU  12902  can receive information from the vehicle mode selector system  238  (e.g., at step  14202 ) to determine if an auto control status is set to ON. If the auto control status is set to ON, semi and/or full autonomous control of the motor vehicle  100  and/or one or more vehicle systems  126  is enabled. It is understood that in some embodiments, step  14204  is optional. If it is determined that the auto control status is set to OFF, the method can return to step  14202 . If it is determined that the auto control status is set to ON, the method proceeds to step  14206 . 
     At step  14206 , the ECU  12902  determines a driver state and/or a driver state index. The driver state can be determined in any of the various ways discussed in Section IV. In some embodiments that will be discussed in further detail herein, the driver state is based on monitoring information from one or more vehicle systems  126  and/or monitoring systems  300 . In some embodiments, determining a driver state can also include determining if the driver is distracted and/or drowsy. 
     At step  14208 , the method includes modifying control of one or more vehicle systems. For example, the ECU  12902  can modify one or more vehicle systems based on the driver state and/or driver state index. In some embodiments, control can be based on a look-up table, for example look-up table  14210 . More specifically, the system status and/or control parameters of the one or more vehicle systems are modified based on the driver state. For example, if the driver state index is 1 or 2, a vehicle system can be set to a system status of no change or standard control. In some embodiments, where the driver state index is 1 or 2, a vehicle system can be set to a system status of auto control. If the driver state index is 3, the vehicle system can be set to a system status of some change, partial control or semi-auto control. If the driver state index is 4, the vehicle system can be set to a system status of more change, full control, or auto control. It is understood that the method shown in  FIG. 142  can include other steps, for example, those shown in  FIG. 141  (e.g., detecting a potential hazard, determining a risk level). 
       FIGS. 143A, 143B, 143C, and 143D  illustrate exemplary look-up tables for status control based on a driver state index for various vehicle systems. It is appreciated that these look-up tables are exemplary in nature and other look-up tables discussed herein as well as other types of vehicle systems and status controls can be implemented. As indicated in  FIG. 143A  by look-up table  14302 , a control status for a low speed follow system can be selected according to driver state. If the driver state index is 1 or 2, the low speed follow system  212  status is set to standard. If the driver state index is 3 or 4, the low speed follow system  212  status is set to auto. It is appreciated that in some embodiments, which are described herein, when the auto control status is set to ON, and the driver state index is 1 or 2 (e.g., the driver is attentive), the low speed follow system  212  status can be set to auto to allow for autonomous control of the low speed follow system  212  when the driver is attentive. Further, in other embodiments, the low speed follow system  212  status can be set to ON or OFF based on the driver state (e.g.,  FIG. 96 , look-up table  9610 ). 
     As indicated in  FIG. 143B  by look-up table  14304 , a control status for a lane keep assist system based can be selected according to a driver state. If the driver state index is 1 or 2, the lane keep assist system  226  status is set to standard. If the driver state index is 3 or 4, the lane keep assist system  226  status is set to auto. It is appreciated that in some embodiments, which are described herein, when the auto control status is set to ON, and the driver state index is 1 or 2 (e.g., the driver is attentive), the lane keep assist system  226  status can be set to auto to allow for autonomous control of the lane keep assist system  226  when the driver is attentive. In some embodiments, the lane keep assist system  226  can vary from standard to low control based on the driver state (e.g.,  FIG. 102 , look-up table  10218 ). 
     As indicated in  FIG. 143C  by look-up table  14306 , a control status for an automatic cruise control system can be selected according to a driver state. If the driver state index is 1, the automatic cruise control system  216  status can be set to manual or OFF thereby requiring a manual switch/button input to modify a headway distance. If the driver state index is 2, a headway distance (e.g., control parameter) of the automatic cruise control system  216  can set to a minimum gap. If the driver state index is 3 or 4, a headway distance (e.g., control parameter) of the automatic cruise control system  216  can set to a maximum gap. It is appreciated that in some embodiments, which are described herein when the auto control status is set to ON, and the driver state index is 1 or 2 (e.g., the driver is attentive), the automatic cruise control system  216  can be set to auto to allow for autonomous control of the automatic cruise control system  216  while the driver is attentive. In other embodiments, the automatic cruise control system  216  can be set to ON or OFF and/or a distance setting can be set in accordance with the driver state (e.g.,  FIG. 94 , look-up tables  9408 ,  9420 ). 
     In another embodiment, modifying control of the one or more vehicle systems can include activating a visual indicator (e.g., visual devices  140 ) based on the driver state and the control type of the vehicle and/or vehicle systems. As an illustrative example, if the motor vehicle  100  and/or one or more vehicle systems  126  and the driver  102  is not distracted and/or drowsy, the light bar  1808  of the touch steering wheel  1802  (see  FIG. 18 ) can be activated to emit a green colored light thereby indicating the auto control status and driver state to the driver  102 . As another illustrative example, if the motor vehicle  100  and/or one or more vehicle systems  126  is in an auto control mode and the driver  102  is distracted and/or drowsy, the light bar  1808  of the steering wheel  1802  (see  FIG. 18 ) can be activated to emit a red colored light thereby indicating the auto control status and driver state to the driver  102 . In further example, if the motor vehicle  100  and/or one or more vehicle systems  126  is in an auto control mode with partial control (e.g., semi-autonomous control) and the driver  102  is not distracted and/or drowsy, the light bar  1808  of the steering wheel  1802  (See  FIG. 18 ) can be activated to emit a partially green colored light thereby indicating the auto control mode and driver state to the driver. 
     As indicated in  FIG. 143D  by look-up table  14308 , a control status for visual devices can be selected according to a driver state. In any of the above examples, when the light bar  1808  of the steering wheel  1802  is activated to emit a color, the response system  12900  can flash the light. For example, flash the red light to get the driver&#39;s attention. In addition, in any of the above examples, when the light bar  1808  of the steering wheel  1802  is activated to emit a color, the response system  12900  can control audio devices  144  to provide an audible sound. For example, when the light bar  1808  of the steering wheel  1802  is activated to emit a red colored light, the audio devices  144  can be activated to provide an audible sound indicating the auto control status and driver state to the driver  102 . Any color or sound combinations can be used. 
     In some embodiments, control of vehicle systems  126 , including vehicle system warnings, can be activated and/or deactivated based the driver state. For example, if the driver  102  is attentive (e.g., alert, aware) of potential hazards surrounding the motor vehicle  100 , some vehicle systems  126  and warnings can be deactivated (e.g., turned OFF). Accordingly, the driver  102  is given full control of the motor vehicle  100  and unnecessary warnings are suppressed since the driver  102  is attentive of any potential hazards. Referring now to  FIG. 144  a flow chart is shown of an embodiment for controlling one or more vehicle systems including suppressing and/or restricting vehicle systems and warnings. At step  14402 , the method includes the ECU  12902  receiving monitoring information from one or more vehicle systems  126  and/or one or more monitoring systems  300 . At step  14404 , the method includes determining if a potential hazard exists based on the monitoring information. If a potential hazard does not exist, the method can return to step  14402 . 
     If a potential hazard does exist, the method proceeds to step  14406 . At step  14406 , the ECU  12902  can determine a driver state and/or driver state index. The driver state index is based on the monitoring information received at step  14402 . The driver state index can be based on information from one or more vehicle systems  126  and/or one or more monitoring systems  300 . At step  14408 , the method includes determining if the driver is distracted based on the driver state index. If the driver not distracted (e.g., aware of the potential hazard, alert, attentive), at step  14410 , the method includes modifying control of one or more vehicle systems. More specifically at step  14410 , the system status of one or more vehicle systems  126  can be set to no control or turned OFF (e.g., disabled). In another embodiment, at step  14410 , the system status of one or more vehicle systems  126  can be set to auto control. Accordingly, modifying control of one or more vehicle systems at step  11410  can include suppressing one or more vehicle systems  126  and/or vehicle system warnings that would normally be triggered by the vehicle systems  126  based on the potential hazard. Further, modifying control of one or more vehicle systems  126  can include deactivating vehicle systems  126  and/or functions that would normally be triggered by the vehicle systems  126  based on the potential hazard. For example, the lane keep assist system  226  can be disabled (e.g., turned OFF) at step  14410  so that steering assistance is not provided, thereby allowing the driver  102  to have full control of steering. 
     If the driver is distracted, at step  14412 , the method includes modifying control of one or more vehicle systems  126 . More specifically, at step  14412 , modifying control of one or more vehicle systems  126  can include activating warnings of certain systems based on the potential hazard. Additionally, modifying control of one or more vehicle systems  126  at step  14412  can include setting a control parameter and/or a system status of one or more vehicle systems  126 . For example, the system status of the lane keep assist system  226  can be set to standard at step  14412 . In another embodiment, the system status of the lane keep assist system  226  can be set to auto. 
     Another embodiment of a process for controlling one or more vehicle systems including confirming a risk and/or hazard is shown in  FIG. 145 . It is appreciated that the method shown in  FIG. 145  could be implemented with any of the illustrative examples described above and with any vehicle systems  126  or monitoring systems  300  discussed previously. As discussed above, in some embodiments, although a hazard or risk is present, the driver may be aware of the hazard and risk. In these situations, the one or more vehicle systems  126  can be modified to account for confirmation of the potential hazard and/or risk by the driver  102 .  FIG. 145  illustrates a general method of confirming a potential hazard and modifying one or more vehicles based on the confirmation. 
     At step  14502 , the ECU  12902  can receive monitoring information from one or more vehicle systems  126  and/or one or more monitoring systems  300  as described in detail above. For example, the ECU  12902  can receive physiological information, behavioral information and vehicle information. At step  14504 , the ECU  12902  can detect a potential hazard as described in detail above based on the monitoring information received at step  14502 . At step  14506 , the ECU  12902  can determine a risk level, for example, based on the probability that the vehicle will encounter the hazard. It is understood that in some embodiments, step  14506  is optional and/or can be determined after step  14508 . 
     At step  14508 , the ECU  12902  determines if the potential hazard has been confirmed by the driver. Said differently, it is determined if the driver  102  is aware (e.g., attentive, alert) of the potential hazard. In another embodiment, a risk level may be determined, and at step  14508 , the method determines if the risk presented by the potential hazard has been confirmed by the driver  102 . To determine if the potential hazard has been confirmed, at step  14510  the method can include determining a driver state and/or driver state index based on the monitoring information. The driver state can be based on monitoring information from vehicle systems and/or monitoring systems, for example, the monitoring information received at step  14502 . Further, the driver state can be based on a plurality of driver states. In some embodiments, the driver state determined at step  14510  is based on an analysis of monitoring information relative to the potential hazard. 
     As discussed above, in some embodiments, step  14506  can include determining if a risk level is high. Thus, in one embodiment, determining if the potential hazard is confirmed at step  14508  can also be based on the risk level. Accordingly, if the risk level is high, even if it is determined that the driver state is attentive at step  14510 , the ECU  12902  can determine the potential hazard is not confirmed based on a high risk level. Thus, even if the driver  102  is aware of the potential hazard, if the risk level of the potential hazard is high, it is determined at step  14508  that the potential hazard is not confirmed. 
     If the potential hazard is not confirmed, at step  14512 , the ECU  12902  modifies the control of one or more vehicle systems. More specifically, at step  14512 , modifying control of one or more vehicle systems  126  can include activating warnings of certain vehicle systems  126  based on the potential hazard. Thus, modifying control of one or more vehicle systems  126  can include setting a control status of the one or more vehicle systems  126  to standard control or auto control. 
     If the potential hazard has been confirmed indicating that the driver  102  is aware of the potential hazard, at step  14514 , the method includes modifying one or more vehicle systems. More specifically, at step  14514 , if the potential hazard has been confirmed, vehicle systems and/or vehicle system warnings can be deactivated and/or overridden. Said differently, modifying control of one or more vehicle systems at step  14514  can include suppressing vehicle system warnings and/or functions that would normally be triggered by the vehicle systems based on the potential hazard. Thus, modifying control of one or more vehicle systems  126  can include setting a control status to no control or disabled (e.g., OFF). 
     A specific example will now be described with reference to  FIG. 145 . At step  14502 , monitoring information is received from one or more vehicle systems  126  and/or one or more monitoring systems  300 . For example, monitoring information can be received from a blind spot indicator system  224 . At step  14504 , the blind spot indicator system  224  can detect a hazard as an object in a blind spot monitoring zone of the motor vehicle  100 . The blind spot indicator system  224  can determine if the hazard poses a risk based on the methods described above at step  14506 . In some embodiments, at step  14506 , determining if the hazard poses a risk also includes determining if the risk level is high. 
     At step  14508 , the ECU  12902  can determine if the potential hazard is confirmed. In some embodiments, the determination at step  14508  is based on the monitoring information and a driver state and/or a driver state index determined at step  14510 . For example, the ECU  12902  can receive head movement information (e.g., a head look) at step  14502  from a head movement monitoring system  334  and/or eye gaze information from an eye/facial movement monitoring system  332 . Further, the ECU  12902  can receive information about a potential lane departure from a lane departure warning system  222  at step  14502 . 
     Based on this information, the ECU  12902  determines a driver state and/or driver state index at step  14510 . The driver state can be based on an analysis of the monitoring information (e.g., head movement, eye gaze, potential lane departure direction) relative to the potential hazard. In this example, the ECU  12902  may determine that a potential lane departure is in the same direction as the object (e.g., target vehicle) and blind spot monitoring zone, but the head look and/or eye gaze of the driver indicates the driver  102  is looking at the object (e.g., target vehicle) and the blind spot monitoring zone. Thus, the driver  102  is aware (e.g., alert, attentive) of the potential hazard. Accordingly, the ECU  12902  can determine driver state as attentive at step  14510 , and at step  14508 , the ECU  12902  determines the potential hazard is confirmed and the method can proceed to step  14514 . 
     In this example, at step  14514 , the ECU  12902  can disable (e.g., turn OFF) the lane departure warning system  222  and/or the blind spot indicator system  224 . Accordingly, warnings typically emitted by these systems will be suppressed. In another example, the ECU  12902  can set a control type of the lane keep assist system  226  to no control (e.g., disabled, turn OFF) so that no power steering assistance is provided. 
     In another illustrative example, the ECU  12902  can detect turn signal information from a turn signal control system  240  at step  14502 . Based on this information and other monitoring information, at step  14510 , the ECU  12902  determines a driver state and/or driver state index. In this example, the ECU  12902  may determine that a potential lane departure is in the same direction as the object and blind spot monitoring zone, but the turn signal information indicates a turn signal has been activated toward the object and the blind spot monitoring zone. In addition, the head look and/or eye gaze of the driver  102  indicates the driver has confirmed the potential hazard. Accordingly, the driver state is determined to be attentive at step  14510  and at step  14508  it is determined that the driver confirmed the potential hazard. However, in another embodiment, even if the driver state is determined to be attentive at step  14510 , if a risk level is determined and the risk level is determined to be high, the ECU  12902  may determine the potential hazard is not confirmed at step  14508 . 
     If the potential hazard is confirmed at step  14508 , at step  14514 , one or more vehicle systems are modified based on the driver state. For example, the ECU  12902  may turn off warnings from the lane departure warning system  222  and may turn off the lane keep assist system  226 . Accordingly, in this example, since the potential hazard has been confirmed, the ECU  12902  will modify the vehicle systems to allow the driver to continue with a potential lane departure and possibly change lanes (squeeze in front of the vehicle in the blind spot monitoring zone). If it is determined that the potential hazard is not confirmed at step  14508 , the driver is determined to be distracted and the lane departure warning system  222  and lane keep assist system  226  will operate to prevent the vehicle  100  from completing the lane change or warn the driver of the vehicle in the blind spot monitoring zone. 
     It is understood that in some embodiments, the modification or adjustment of one or more vehicle systems can be modified and/or adjusted again (e.g., back to an original state) based on a change in driver state. For example, in some embodiments where the ECU  12902  deactivates and/or turns OFF any vehicle systems  126 , the ECU  12902  can automatically reactivate and/or turn ON these vehicle systems upon detecting a change in driver state, for example a driver state that is distracted and/or drowsy. In other embodiments, the ECU  12902  can automatically check and/or determine a driver state at a predetermined time interval to determine if there is a change in driver state and the vehicle systems  126  should be modified again (e.g., reverted to an original status/state). Thus, in some examples, vehicle systems can be enabled and disabled within seconds based on the driver state. As an illustrative example, if the ECU  12902  determines the driver state as attentive and disables (e.g., turn OFF) the lane departure warning system  222  (e.g., suppressing warnings), the ECU  12902  can subsequently reactivate (e.g., enable, turn ON) the lane departure warning system  222  when the ECU  12902  determines the driver state is distracted. 
     The exemplary operational responses of the one or more vehicle systems described above can be implemented with the methods and systems for determining one or more driver states, determining a combined driver state, confirming one or more driver states, determining a vehicular state, as discussed above. Specific examples of controlling vehicle systems according to the methods of  FIGS. 141, 142, 144 and 145  will now be described. These examples are exemplary in nature and it is understood that other vehicle systems and combinations of vehicle systems can be implemented. Further, it is understood that some components of  FIGS. 141, 142, 144 and 145  can be omitted and/or rearranged into other configurations. In some embodiments, vehicle systems are modified for semi and/or automatic control based on a driver state where the driver state is determined relative to a potential hazard. In other embodiments, vehicle systems are modified for semi and/or automatic control based on a combined driver state. The combined driver state can be based on different types of behavioral information and vehicular-sensed information. Some of the controls and/or modifications of vehicle systems provide intuitive driver controls and/or convenience features allowing control customized to the driver and the driver state. 
     Referring now to  FIG. 146 , a method for operating a lane departure warning system in response to driver state is illustrated. In some embodiments, some of the following steps could be accomplished by a response system  12900  of the motor vehicle  100 . In some cases, some of the following steps can be accomplished by an ECU  12902  of a motor vehicle. In other embodiments, some of the following steps could be accomplished by other components of a motor vehicle, such as vehicle systems  126 . In still other embodiments, some of the following steps could be accomplished by any combination of systems or components of the vehicle. It will be understood that in some embodiments one or more of the following steps can be optional. 
     At step  14602 , the method includes the ECU  12902  receiving information from the lane departure warning system  222  (e.g., monitoring information). At step  14604 , the ECU  12902  determines if a potential lane deviation exists with respect to the motor vehicle  100  (e.g., a potential hazard) based on the information from the lane departure warning system  222 . In some embodiments, the potential lane deviation can be determined based on lane departure warning information as discussed above with  FIGS. 100 and 101 . If a potential lane deviation does exist, the method can proceed to step  14606 . Otherwise, the method can proceed back to step  14602 . 
     At step  14606 , the ECU  12902  receives head movement information, from, for example, the head movement monitoring system  334 , and/or eye gaze information from the eye/facial movement monitoring system  332 . In some embodiments, the head movement and/or eye gaze information can be received at step  14602 . The head movement information can include information about a head pose and a head look of the driver as discussed above in Section III (B) (2) and with  FIGS. 16A, 16B and 17 . Thus, at step  14608 , the ECU  12902  can analyze the head movement (e.g., head look) and/or the eye gaze relative to the potential hazard, for example, the potential lane deviation. More specifically, the ECU  12902  determines if a head look and/or eye gaze of the driver  102  is directed toward the potential lane deviation. 
     Accordingly, at step  14610 , the method includes determining a driver state and/or driver state index. For example, the driver state is determined based on the monitoring information relative to the potential hazard. In some embodiments, step  14610  can also include determining if the driver is attentive and/or distracted based on the driver state and/or driver state index. More specifically, in  FIG. 146 , the ECU  12902  determines the driver state based on at least the head movement information and/or eye gaze information received at step  14606  and the analysis of the head movement and/or eye gaze information relative to the lane deviation at step  14608 . Said differently, the driver state and/or the driver state index is based at least in part on the head movement and/or eye gaze information and the potential lane deviation. 
     Thus, in one embodiment, if the head look is a forward-looking head look, the driver state index is determined to be low (e.g., attentive) at step  14610 . Similarly, if the head look is directed in the same direction of the potential lane deviation, the driver state index is determined to be low (e.g., attentive) at step  14610 . However, if the head look is not forward-looking or is not directed to the same direction as the possible lane deviation, the driver state index is determined to be high (e.g., not attentive) at step  14610 . 
     Accordingly, at step  14612 , the ECU  12902  modifies one or more vehicle systems based on the driver state and/or driver state index determined at step  14610 . In one embodiment, the ECU  12902  modifies a control type (e.g., system status) of one or more vehicle systems  126 . For example, if the driver state index indicates an attentive driver state, the ECU  12902  can set the control type of the lane departure warning system  222  to disabled and/or no control (e.g., OFF). Accordingly, the warnings emitted by the lane departure warning system  222  are deactivated and/or suppressed. If the driver state index indicates a distracted driver state, the ECU  12902  can set the control type of the lane departure warning system  222  to enabled and/or standard control (e.g., ON). For example, the ECU  12902  can activate the warnings emitted by the lane departure warning system  222 . In another embodiment, if the driver state index indicates a distracted driver state, the ECU  12902  activates the warnings emitted by the lane departure warning system  222  and activates a lane keep assist system  226  (e.g., system status to ON) to provide lane keeping assistance. 
     Referring now to  FIGS. 147A and 147B , a schematic view of controlling a lane departure warning system according to the method of  FIG. 146  is shown. In  FIG. 147A , the motor vehicle  100  is travelling on a roadway  14702  and is approaching a centerline  14704 . The head look of the driver  102  is forward-looking relative to the motor vehicle  100 . Accordingly, based on the potential lane deviation of the motor vehicle  100  and the head look of the driver  102 , the ECU  12902  determines the driver state to be attentive. Thus, the ECU  12902  modifies the lane departure warning system  222  by setting the system status of the lane departure warning system  222  to no control or disabled (e.g., OFF). Therefore, the lane departure warning  14706  is deactivated. 
     In  FIG. 147B , the motor vehicle  100  is approaching the centerline  14704  and the head look of the driver  102  is not forward-looking (i.e., head down, head look down). Accordingly, the ECU  12902  determines the driver state to be distracted and modifies the lane departure warning system  222  by setting a system status to enabled and/or standard control (e.g., ON). Therefore, the lane departure warning  14706  is activated. 
     Referring now to  FIG. 148 , a method for operating a blind spot indicator system in response to driver state is illustrated. At step  14802 , the method includes the ECU  12902  receiving information from a blind spot indicator system  224  (e.g., monitoring information). At step  14804 , the ECU  12902  determines if a potential hazard exists based on the information from the blind spot indicator system  224 . For example, the ECU  12902  can detect a potential hazard as an object (e.g., a target vehicle) inside a blind spot monitoring zone of the motor vehicle  100 . If a potential hazard is not detected at step  14804 , the method can return to step  14802 . Otherwise, the method proceeds to step  14806 . 
     At step  14806 , the ECU  12902  receives head movement information and/or eye gaze information, for example from a head movement monitoring system  334  and/or an eye/facial movement monitoring system  332 . In some embodiments, the head and/or eye gaze movement information is received at step  14802 . The head movement information can include information about a head pose and a head look of the driver as discussed above in Section III (B) (2) and with  FIGS. 16A, 16B, 17 . Thus, at step  14808 , the ECU  12902  can analyze the head movement and/or eye gaze information relative to the target vehicle and/or blind spot monitoring zone (e.g., the potential hazard). Said differently, the ECU  12902  can determine a head movement (e.g., a head look) and/or eye gaze relative to the potential hazard, for example, the blind spot monitoring zone and/or the target vehicle. More specifically, the ECU  12902  determines if the head look and/or eye gaze is directed away from the blind spot monitoring zone and/or the target vehicle. 
     Accordingly, at step  14810 , the method includes determining a driver state and/or a driver state index. For example, the driver state is determined based on monitoring information relative to the potential hazard. In some embodiments, step  14810  can also include determining if the driver is attentive and/or distracted based on the driver state and/or driver state index. More specifically, in  FIG. 148 , the ECU  12902  determines the driver state based on at least the head movement and/or eye gaze information received at step  14806  and the analysis of the head movement and/or eye gaze relative to the target vehicle and/or blind spot monitoring zone at step  14808 . Said differently, the driver state and/or the driver state index is based at least in part on the head movement and/or eye gaze information and the target vehicle and/or blind spot monitoring zone. 
     For example, if the head look or eye gaze is a forward-looking head look or eye gaze, the driver state index is determined to be low (e.g., attentive) at step  14810 . If the head look or eye gaze is directed away from the object, the blind spot monitoring zone, and/or a forward way of the vehicle, the driver state index is determined to be high (e.g., not attentive) at step  14810 . 
     At step  14812 , the ECU  12902  modifies one or more vehicle systems based on the driver state and/or driver state index. In one embodiment, the ECU  12902  modifies a control type of one or more vehicle systems. For example, if the driver state index indicates an attentive driver state, the ECU  12902  can set the control type (e.g., system status) of the blind spot indicator system  224  to disabled and/or no control (e.g., OFF). Accordingly, the ECU  12902  deactivates warning signals emitted from the blind spot indicator system  224 . If the driver state index indicates a distracted driver state, the ECU  12902  can set the control type (e.g., system status) of the blind spot indicator system  224  to enabled and partial and/or full control (e.g., ON). Thus, the ECU  12902  activates the warning signals emitted from the blind spot indicator system  224 . In addition, if the driver state is distracted, the ECU  12902  can modify the activation time of the warning signals. For example, the ECU  12902  can increase the activation time of the warning signals, based in part, on the driver state and/or driver state index. 
     Referring now to  FIGS. 149A and 149B , a schematic view of controlling a blind spot indicator system in accordance with the method of  FIG. 148  is shown. In  FIG. 149A , the blind spot indicator system  224  detects a target vehicle  14902  is traveling on a road  14906  inside of a blind spot monitoring zone  14904  of the motor vehicle  100 . Here, the head look and/or eye gaze of the driver  102  is forward-looking relative to the motor vehicle  100 . Accordingly, based on the potential hazard with the target vehicle  14902  and the head look and/or eye gaze of the driver, the ECU  12902  determines the driver state to be attentive and controls the blind spot indicator system  224  by disabling the blind spot indicator system  224  and/or setting the control status of the blind spot indicator system  224  to no control (e.g., OFF). Accordingly, the blind spot indicator warning  14908  is deactivated (e.g., suppressed) by the ECU  12902 . 
     In  FIG. 149B , the blind spot indicator system  224  detects the target vehicle  14902  is traveling on the road  14906  inside of the blind spot monitoring zone  14904  of the motor vehicle  100 , but the head look and/or eye gaze of the driver  102  is directed away from the target vehicle  14902  and the blind spot monitoring zone  14904 . Accordingly, based on the potential hazard with the target vehicle  14902  and the head look and/or eye gaze of the driver  102 , the ECU  12902  determines the driver state to be distracted and controls the blind spot indicator system  224  by enabling the blind spot indicator system  224  and/or setting the control status of the blind spot indicator system  224  to partial and/or full control (e.g., ON). Accordingly, the blind spot indicator system warning  14908  is activated by the ECU  12902 . 
     Referring now to  FIG. 150 , a method for operating a blind spot indicator system and a lane departure warning system based on driver state is illustrated. At step  15002 , the method includes the ECU  12902  receiving information from the blind spot indicator system  224  (e.g., monitoring information). At step  15004 , the ECU  12902  detects a potential hazard based on the information from the blind spot indicator system  224 . For example, the ECU  12902  can detect a potential hazard as an object (e.g., a target vehicle) inside a blind spot monitoring zone. If a potential hazard is not detected at step  15004 , the method can return to step  15002 . Otherwise, the method proceeds to step  15006 . 
     At step  15006 , the ECU  12902  receives information from the lane departure warning system  222 , head movement information from a head movement monitoring system  334  and/or eye gaze information from an eye/facial movement monitoring system  332 . The information from the lane departure warning system  222  can include information about a potential lane deviation and a direction of the lane deviation. The head movement information can include information about a head pose and a head look of the driver as discussed above in Section III (B) (2) and with  FIGS. 16A, 16B and 17 . It is understood that the information from the lane departure warning system  222 , head movement information from a head movement monitoring system  334  and/or eye gaze information from an eye/facial movement monitoring system  332  can be received at step  15002 . 
     At step  15008 , the ECU  12902  can analyze the lane departure warning information and head movement and/or eye gaze information relative to the target vehicle and/or blind spot monitoring zone (e.g., the potential hazard). Said differently, the ECU  12902  can determine a direction of a potential lane deviation and a direction of a head movement (e.g., head look) and/or eye gaze relative to the potential hazard, for example, the blind spot monitoring zone and/or the target vehicle. 
     Accordingly, at step  15010 , the method includes determining a driver state and/or a driver state index. For example, the driver state is based on monitoring information relative to the potential hazard. In some embodiments, step  15010  can also include determining if the driver is attentive and/or distracted based on the driver state and/or the driver state index. More specifically, in  FIG. 150 , the ECU  12902  determines the driver state based on at least the lane departure warning information, head movement and/or eye gaze information received at step  15006 , and the analysis of the lane departure warning information and head movement and/or eye gaze information relative to the potential hazard at step  15008 . Said differently, the driver state and/or the driver state index is based at least in part on the lane departure warning information, the head movement and/or eye gaze information and the target vehicle and/or blind spot monitoring zone. 
     For example, if the head look and/or eye gaze is forward-looking and the lane departure warning system information indicates a possible lane deviation towards the object and/or blind spot monitoring zone, the driver state is determined to be distracted at step  15010 . Similarly, if the head look and/or eye gaze is not towards the object and/or blind spot monitoring zone and the lane departure warning system  222  information indicates a possible lane deviation towards the object and/or blind spot monitoring zone, the driver state is determined to be distracted at step  15010 . However, if the head look and/or eye gaze is directed to the object and/or blind spot monitoring zone and the lane departure warning system  222  information indicates a possible lane deviation towards the object and/or blind spot monitoring zone, the driver state is determined to be attentive at step  15010 . 
     At step  15012 , the ECU  12902  modifies one or more vehicle systems based on the driver state and/or driver state index. In one embodiment, the ECU  12902  modifies a control type (e.g., a system status) of one or more vehicle systems  126 . For example, if the driver state is attentive, the ECU  12902  can set the control type of the blind spot indicator system  224  and/or the lane departure warning system  222  to disabled and/or no control (e.g., OFF). Accordingly, the ECU  12902  deactivates warning signals emitted from the blind spot indicator system  224  and/or the lane departure warning system  222 . If the driver state index indicates a distracted driver state, the ECU  12902  can set the control type of the blind spot indicator system  224  and/or the lane departure warning system  222  to enabled and partial and/or full control (e.g., ON). Thus, the ECU  12902  activates the warning signals emitted from the blind spot indicator system  224  and/or the lane departure warning system  222 . In addition, if the driver state is distracted, the ECU  12902  can modify the activation time of the warning signals. For example, the ECU  12902  can increase the activation time of the warning signals, based in part, on the driver state and/or driver state index. 
     Referring now to  FIGS. 151A and 151B , a schematic view of controlling one or more vehicle systems in accordance with the method of  FIG. 150  is shown. In  FIG. 151A , the blind spot indicator system  224  detects a target vehicle  15102  is traveling inside of a blind spot monitoring zone  15104  of the motor vehicle  100 , the motor vehicle  100  is approaching a centerline  15106  of a road  15108 . Here, the head look of the driver  102  is forward-looking relative to the motor vehicle  100 . Accordingly, based on the potential hazard, the potential lane deviation, and the head look and/or eye gaze of the driver  102 , the ECU  12902  determines the driver state to be distracted. Thus, the ECU  12902  controls the blind spot indicator system  224  and the lane departure warning system  222  by enabling said systems and setting the control status of said systems to partial and/or full control (e.g., ON). Thus, the ECU  12902  activates the blind spot indicator system warning  15110  and lane departure warning  15112  since the driver state is distracted. 
     In  FIG. 151B , the blind spot indicator system  224  detects the target vehicle  15102  is traveling inside of the blind spot monitoring zone  15104  of the motor vehicle  100 , the motor vehicle  100  is approaching the centerline  15106  of the road  15108 . Here, the head look of the driver  102  is looking towards the blind spot monitoring zone  15104 . Accordingly, based on the potential hazard, the potential lane deviation, and the head look and/or eye gaze of the driver  102 , the ECU  12902  determines the driver state to be attentive. Thus, the ECU  12902  controls the blind spot indicator system  224  and the lane departure warning system  222  by disabling said systems and setting the control status of said systems to no control (e.g., OFF). Accordingly, the ECU  12902  deactivates the warnings  15110  and  15112  since the driver state is attentive. 
     Referring now to  FIG. 152 , a method of an embodiment of a process for controlling an idle mode of an engine based on driver state according to an exemplary embodiment is shown. As discussed above, the engine  104  of the motor vehicle  100  can include an idle stop function that is controlled by the ECU  12902  and/or the engine  104 . Specifically, the idle stop function includes provisions to automatically stop and restart the engine  104  to help maximize fuel economy depending on environmental and vehicle conditions. In some embodiments, the idle stop function can be activated based on a timer function. At step  15202 , the method includes receiving braking information (e.g., monitoring information), from, for example, the antilock brake system  204 . It is understood that the braking information can be received from any braking system and/or from the engine  104 . More specifically, braking information can include information from any sensors and/or vehicle systems. For example, the ECU  12902  can receive information that a brake switch (e.g., brake pedal) has been applied to determine if the driver  102  is currently braking. In another example, the ECU  12902  can use other vehicle information to determine if the brake pedal is depressed, the brake pedal is released, braking is being applied, braking rate, braking pressure, among others. In some embodiments described herein, braking information can also include information about acceleration, received, for example, from the ECU  12902 . For example, indication that an accelerator switch (e.g., an accelerator pedal) has been applied, accelerator pedal input, accelerator pedal input pressure/rate, among others. 
     At step  15204 , it is determined if the vehicle is stopped based on the braking information (e.g., the vehicle is at a complete stop). If the vehicle is not at a complete stop, the method can return to step  15202 . If the vehicle is at a complete stop, the method can proceed to step  15206 . At step  15206  it is determined if the idle mode function is set to ON. This determination can be based on the monitoring information received at step  15202 . For example, the monitoring information, to determine if the idle mode function status (e.g., ON/OFF), can be received from the engine  104  and/or the ECU  12902 . It is understood that in some embodiments, step  15206  can be optional. 
     If the determination at step  15206  is NO (i.e., the idle mode function is set to OFF), the method can return to step  15202 . Otherwise, the method proceeds to step  15208 . At step  15208 , the ECU  12902  receives hand contact information indicating hand contact of the driver with the steering wheel, for example, the touch steering wheel  134 . In one embodiment, the hand contact information can be received from the touch steering wheel system  134  and/or the EPS system  132 . In another embodiment, hand contact information can be received from optical sensors and analyzed, for example, by the gesture recognition monitoring system  330 . In some embodiments, the hand contact information can be received at step  15202 . It is understood that steps  15208  and  15210  can be part of determining a driver state based on behavioral information. 
     At step  15210 , it is determined if there is hand contact with the steering wheel based on the hand contact information. Said differently, it is determined if one or both hands are on the steering wheel  134 . If there is at least one hand on the steering wheel  134 , the method returns to step  15202 . Otherwise, the method proceeds to step  15212  where the ECU  12902  engages the idle mode function of the engine  104  (i.e., turns the engine OFF). 
     In order to disengage the idle mode function, at step  15214 , the method includes receiving hand contact information, similar to step  15208 . At step  15216 , it is determined if one or both hands are in contact with the steering wheel  134  based on the hand contact information. If the determination at step  15216  is NO (i.e., no hands on the steering wheel  134 ), the process returns to step  15214 . Otherwise, at step  15218 , the ECU  12902  disengages the idle mode function of the engine  104  (i.e., turns the engine ON). 
     Referring now to  FIG. 153 , a method for controlling a brake hold feature of an electric parking brake system is shown. At step  15302 , the ECU  12902  receives braking information (e.g., monitoring information), from, for example, the antilock brake system  204 . It is understood that the braking information can come from any of the braking systems, from the electric parking brake system  210  and/or from the engine  104 . At step  15304 , the ECU  12902  determines if the vehicle is stopped based on the braking information (e.g., the vehicle is at a complete stop). If the vehicle is not at a complete stop, the method can return to step  15302 . If the vehicle is at a complete stop, the method can continue to step  15306 . 
     At step  15306 , the ECU  12902  determines if the brake pedal of the motor vehicle  100  is released (e.g., not depressed) based on, for example, the braking information received at step  15302 . If the determination is NO, the method can return to step  15302 . If determination is YES, the method can continue to step  15308 . At step  15308 , hand contact information is received indicating hand contact of the driver with the steering wheel, for example, the touch steering wheel  134 . The hand contact information can be received by the ECU  12902  from the touch steering wheel system  134  and/or the EPS system  132 . In some embodiments, the hand contact information can be received at step  15302 . 
     At step  15310 , it is determined if there is hand contact with the steering wheel based on the hand contact information. Said differently, it is determined if one or both hands are on the touch steering wheel  134 . If there is at least one hand on the steering wheel  134 , the method returns to step  15302 . Otherwise, the method proceeds to step  15312  where the ECU  12902  engages the brake hold function of the electric parking brake system  210  (i.e. the vehicle  100  remains stopped without the driver  102  needing to engage the brake pedal or shift to park). 
     In order to disengage (e.g., release) the brake hold function, at step  15314 , the method includes receiving braking information and/or hand contact information, similar to steps  15302  and  15308 . At step  15316 , the ECU  12902  determines if an accelerator pedal of the motor vehicle  100  is engaged (e.g., depressed) or the brake pedal of the motor vehicle  100  is engaged (e.g., depressed) based on the braking information. If the determination at step  15316  is YES, the method proceeds to step  15318  where the ECU  12902  disengages (e.g., releases) the brake hold function. 
     If the determination at step  15316  is NO, the method proceeds to step  15320  where the ECU  12902  determines if there is hand contact with the steering wheel based on the hand contact information. Said differently, it is determined if one or both hands are on the steering wheel  134 . If there is at least one hand on the steering wheel  134 , the method proceeds to step  15318 . Otherwise, the method proceeds back to step  15314 . 
     Referring now to  FIG. 154 , a method for disengaging (e.g., releasing) an electric parking brake system is shown. At step  15402 , the method includes receiving electric parking brake information from the electric parking brake system  210 . At step  15404 , it is determined if the electric parking brake status is set to ON based on the information received at step  15402 . If the determination at step  15404  is NO (i.e., the electric parking brake status is set to OFF), the method returns to step  15402 . Otherwise, the method proceeds to step  15406 . 
     At step  15406 , the ECU  12902  receives hand contact information and braking information. The hand contact information can be received from the touch steering wheel system  134  and/or the EPS system  132 . The braking information can be received, for example, from the antilock brake system  204 . It is understood that in some embodiments, the braking information can be received from any braking system. In some embodiments, the hand contact and braking information can be received at step  15402 . 
     At step  15408 , it is determined If there is hand contact with the steering wheel. For example, it is determined if one or both hands are in contact with the touch steering wheel  134  based on the hand contact information. If the determination at step  15408  is NO (e.g., no hand contact with the touch steering wheel  134 ), the method returns to step  15402 . Otherwise, the method proceeds to step  15410 . At step  15410 , it is determined if the accelerator pedal of the motor vehicle  100  is engaged (e.g., depressed) or the brake pedal of the motor vehicle  100  is engaged (e.g., depressed) based on the braking information. If the determination at step  15410  is NO, the method returns to step  15402 . Otherwise, the method proceeds to step  15412 . At step  15412 , the ECU  12902  disengages (e.g., releases) the electric parking brake system  210 . 
     Referring now to  FIGS. 155A and 155B  methods for controlling vehicle systems based in part on hand contact transitions will be described. Specifically,  FIG. 155A  illustrates a method for controlling vehicle systems based on hand contact transitions according to one embodiment. At step  15502 , the ECU  12902  receives hand contact information (e.g., monitoring information). The hand contact information can be received from the touch steering wheel system  134  and/or the EPS system  132 . At step  15504 , the ECU  12902  determines if a hand contact transition with the steering wheel has occurred. For example, based on the hand contact information, it is determined if the number of hands in contact with the steering wheel  134  has changed. More specifically, in the embodiment shown in  FIG. 155A , it is determined if a transition has occurred from one hand in contact with the touch steering wheel  134  to two hands in contact with the touch steering wheel  134 . Alternatively, it can be determined if a transition from two hands in contact with the touch steering wheel  134  to one hand in contact with the touch steering wheel  134  has occurred. In some embodiments, at step  15504 , the ECU  12902  can determine if the transition has occurred within a predetermined period of time. 
     If a hand contact transition is not detected at step  15504 , the method returns to step  15502 . Otherwise, the method proceeds to step  15506 , where the ECU  12902  determines a driver state and/or driver state index. The driver state and/or driver state index is based on the hand contact transition detected at step  15504 . For example, a transition from one hand in contact with the steering wheel  134  to two hands in contact with the steering wheel  134  can indicate the driver state is attentive and the driver may be initiating a maneuver of the motor vehicle  100 . In some embodiments, the indication that the driver is initiating a maneuver with the motor vehicle  100  can be confirmed with steering information as will be described with  FIG. 155B . In another example, a transition from two hands in contact with the steering wheel  134  to one hand in contact with the steering wheel  134  can indicate the driver state is distracted. In some embodiments, although a transition from two hands in contact with the steering wheel  134  to one hand in contact with the steering wheel  134  has occurred, current steering information can be compared to stored steering information to determine the driver state as described with  FIG. 156 . It is understood that in some embodiments, step  15506  also includes determining if the driver state is attentive (e.g., alert) or distracted. 
     At step  15508 , the method includes modifying control of one or more vehicle systems based on the driver state. For example, if the driver state is determined to be attentive, the ECU  12902  can control the lane departure warning system  222  and/or the blind spot indicator system  224  by disabling these systems and/or setting the control type (e.g., system status) of these systems to no control (e.g., OFF). Accordingly, warnings emitted by the lane departure warning system  222  and/or the blind spot indicator system  224  are deactivated and/or suppressed. In another embodiment, if the driver state is determined to be attentive, the ECU  12902  can control the lane keep assist system  226  by disabling the system and/or setting the control type (e.g., system status) of this system to no control (e.g., OFF). In a further embodiment, the modification of the vehicle systems at step  15508  can be modified to the original control type (e.g., system status) after a period of time and/or after another hand contact transition is detected. 
       FIG. 155B  illustrates a specific implementation of controlling a vehicle mode based in part on a hand contact transition. At step  15510 , the method includes the ECU  12902  receiving vehicle mode information from, for example, the vehicle mode selector system  238 , and hand contact information, from, for example, the touch steering wheel system  134  and/or the EPS system  132 . At step  15512 , the ECU  12902  determines if a hand contact transition with the steering wheel has occurred. For example, based on the hand contact information, it is determined if the number of hands in contact with the touch steering wheel  134  has changed. More specifically, in the embodiment shown in  FIG. 155B , it is determined if a transition has occurred from two hands in contact with the touch steering wheel  134  to one hand in contact with the touch steering wheel  134 . 
     If the determination at step  15512  is NO, the method returns to step  15510 . If the determination at step  15512  is YES, the method proceeds to step  15514  where the ECU  12902  determines a driver state and/or driver state index. The driver state and/or driver state index is based on the hand contact transition detected at step  15512 . At step  15516 , the method includes modifying the vehicle mode (e.g., switching the vehicle mode) based on the vehicle mode received at step  15510  and the hand contact transition. Thus, the ECU  12902  can control the vehicle mode selector system  238  to switch a mode at step  15516 . In some embodiments, the vehicle mode is switched based on a look-up table  15518 . For example, if the vehicle mode received at step  15502  is a sport mode, the vehicle mode is switched to comfort mode. If the vehicle mode received at step  15502  is a normal mode, the vehicle mode is switched to comfort mode. This modification allows for intuitive vehicle control based on the driver state. 
     In some embodiments, it may not be safe to switch vehicle modes during a driving maneuver. Accordingly, in  FIG. 155B , after a determination of YES is made at step  15512 , the method can optionally proceed to step  15520 , which includes receiving steering information. The steering information can be analyzed to determine if the vehicle is currently in a maneuver and/or completing a maneuver. For example, a degree of yaw rate, steering angle, and/or lateral G movement can be compared to predetermined thresholds to determine if the vehicle is currently performing a maneuver (e.g., a turn, a sharp curve). Thus, at step  15522 , the method includes determining if a maneuver is in progress. If, the determination is NO, the method proceeds to step  15514 . If the determination is YES, the method proceeds to step  15524  where it is determined if the maneuver is complete. If the maneuver is complete, the method proceeds to step  15514 . Otherwise, the method returns to step  15520 . Accordingly, the vehicle mode can be modified and/or switch at an appropriate time to ensure a safe and smooth transition. 
     Referring now to  FIG. 156 , a method for controlling a power steering system of an electronic power steering system according to an exemplary embodiment is shown. At step  15602 , the method includes receiving steering information, from, for example, the EPS system  132  and/or the touch steering wheel system  134 . At step  15604 , the method includes determining a driver state and/or a driver state index based on the steering information. In some embodiments, at step  15606 , the driver state index can be based on comparing the steering information received at step  15602  to stored steering information for an identified driver. For example,  FIG. 24B  illustrates an embodiment for controlling one or more vehicle systems with identification of a driver. 
     Referring again to  FIG. 156 , at step  15608 , the method includes controlling the electronic power steering system  132  (e.g., a power steering status) and the lane keep assist system  226  (e.g., a control type and/or system status). More specifically, the power steering status is set and the lane keep assist system  226  is enabled (e.g., turned ON). In some embodiments, a look-up table  15610  can be used to set the power steering status. For example, if the driver state index is 1 or 2 (e.g., driver is attentive/not drowsy), the power steering status can be set to auto and more steering assistance is provided to the driver according to the lane keep assist system  226 . 
     Referring now to  FIG. 157 , a method for controlling a low speed follow system is shown. At step  15702 , the method includes receiving information from a low speed follow system (e.g., monitoring information). For example, the ECU  12902  can receive information from the low speed follow system  212 . At step  15704 , the method can include determining a possible hazard based on the information from the low speed follow system. For example, the low speed follow system  212  can identify a target vehicle in front of the motor vehicle  100  as a potential hazard. If a potential hazard is not detected at step  15704 , the method can return to step  15702 . Otherwise, the method proceeds to step  15706 . 
     At step  15706 , the method includes receiving head movement information (e.g., head look), for example, from a head movement monitoring system  334 , and/or eye gaze information, for example from an eye/facial movement monitoring system  332 , and/or hand contact information from a touch steering wheel system  134 . The head movement information can include information about a head pose and a head look of the driver as discussed above in Section III (B) (2) and with  FIGS. 16A, 16B and 17 . The hand contact information can include information about the contact and position of the driver&#39;s hands with respect to the touch steering wheel as described with  FIG. 18 . In some embodiments, the head movement information, eye gaze information and/or the hand contact information can be received at step  15702 . 
     At step  15708 , the ECU  12902  can analyze hand contact information, the eye gaze information and/or the head movement information relative to the information received from low speed follow system  212  (e.g., relative to the potential hazard). Said differently, the ECU  12902  can determine a trajectory and potential collision with a target vehicle, a direction of the head movement (e.g., a head look) and/or eye gaze relative to the target vehicle and hand contact with the steering wheel. Accordingly, at step  15710 , the method includes determining a driver state and/or driver state index. For example, the driver state is based on the monitoring information (e.g., the low speed follow system information, the hand contact information, the eye gaze information, and/or the head movement information) and the potential hazard. In some embodiments, step  15710  can also include determining if the driver is attentive and/or distracted based on the driver state and/or the driver state index. More specifically, in  FIG. 157 , the ECU  12902  determines the driver state based on at least the hand contact information, eye gaze information and/or head movement information received at step  15706  and the analysis of the hand contact information, eye gaze information and/or head movement information relative to the potential hazard at step  15708 . Said differently, the driver state and/or the driver state index is based at least in part on the low speed follow system information, the head movement information, the eye gaze information and/or the hand contact information. 
     For example, if the head position and contact information indicates the driver has at least one hand on the wheel and the head look is a forward-looking head look of the driver, the driver state is determined to be attentive at step  15710 . If the hand contact information indicates the driver has at least one hand on the wheel and the head look is a non-forward-looking head look of the driver, the driver state is determined to be distracted at step  15710 . If the hand contact information indicates the driver has no hands on the wheel, the driver state is determined to be distracted at step  15710 . 
     At step  15712 , the method includes controlling the low speed follow system based on the driver state and/or driver state index. More specifically, the ECU  12902  sets the low speed follow system status (e.g., control status/type) based on the driver state. For example, if the driver state is distracted, the ECU  12902  can set the control type of the low speed follow system  212  to standard control and modify the touch steering wheel  134  (e.g., at step  15714 ) to provide visual warnings (e.g., to put at least one hand on the wheel and/or look forward) at step  15714 . Accordingly, the visual warnings inform the driver  102  of the driver state. 
     If the driver state is attentive, the ECU  12902  can set the control type of the low speed follow system  212  to auto control. Accordingly, low speed follow system  212  in conjunction with the automatic cruise control system  216  will move relative to the target vehicle. Thus, the ECU  12902  can also control the automatic cruise control system  216  to slow down and/or increase a distance between the motor vehicle  100  and the target vehicle. Further, the ECU  12902  can control a lane keep assist system  226  (e.g., enable the lane keep assist system  226 ) based on the driver state to help keep the vehicle within the current lane markers. 
     Referring now to  FIGS. 158A and 158B , a schematic view of controlling a low speed follow system and a visual device (e.g., a visual device on a steering wheel) in accordance with the method of  FIG. 157  is shown. In  FIG. 158A , the motor vehicle  100  (e.g., host vehicle) is travelling behind a preceding vehicle  15802  (e.g., target vehicle). The vehicle  100  includes the automatic cruise control system  216  and the low speed follow system  212  is set to a status of ON. Here, the head look of the driver  102  is forward-looking relative to the motor vehicle  100  and one hand is in contact with the touch steering wheel  134 . Accordingly, based on the potential hazard with the target vehicle, the head movement information, and the hand contact information, the driver state is determined to be attentive. Accordingly, the ECU  12902  controls the low speed follow system  212  and/or the automatic cruise control system  216  to maintain a predetermined headway distance  15804  behind the preceding vehicle  15802  (e.g., standard control, auto control). In a stop and go situation, the motor vehicle  100  will move, without physical interaction (e.g., switching a button to engage the low speed follow system), in relation to the preceding vehicle  15802  when the driver is attentive. 
     In  FIG. 158B  the motor vehicle  100  (e.g., host vehicle) is travelling behind the preceding vehicle  15802  (e.g., target vehicle). The vehicle  100  includes the automatic cruise control system  216  and the low speed follow system  212  is set to a status of ON. Here, the head look of the driver  102  is forward-looking, but the driver  102  does not have any hands in contact with the touch steering wheel  134 . According, based on the potential hazard, the head movement, and the hand contact with the touch steering wheel  134 , the driver state is determined to be distracted. Therefore, the ECU  12902  can control the low speed follow system  212  by setting the system status to disabled and the ECU  12902  can control visual devices  140  (e.g., the light bar on the touch steering wheel  134 ) to provide warning signals  15806  to the driver  102 . 
     When the driver  102  contacts the steering wheel with at least one hand, as shown in  FIG. 158A , the motor vehicle  100  will move, in relation to the preceding vehicle  15802  (e.g., the driver state is determined to be attentive based on a forward head look of the driver and at least one hand in contact with the touch steering wheel system  134 ). This illustrative example shows how operation (e.g., ON, OFF) of a vehicle system can change within milliseconds based on the driver state. 
       FIG. 159  illustrates an alternative embodiment of the process of  FIG. 157 . At step  15902 , the method includes receiving low speed follow information (e.g., monitoring information), from, for example, the low speed follow system  212 . At step  15904 , it is determined if there is a potential hazard based on the information received at step  15902 , for example, a potential hazard with a preceding vehicle. If the determination at step  15904  is NO, the method returns to step  15902 . If the determination at step  15904  is YES, the method proceeds to step  15906 . At step  15906 , the method includes receiving hand contact information, from, for example, the EPS system  132 , and/or the touch steering wheel system  134 . In some embodiments, the hand contact information can be received at step  15902 . 
     At step  15908 , the ECU  12902  determines if there is hand contact with the steering wheel. More specifically, it is determined if at least one hand is in contact with the steering wheel based on the information received at step  15904 . If NO, at step  15908 , the ECU  12902  sets the system status of the low speed follow system  212  to manual control. Accordingly, the low speed follow system  212  will not be activated without a manual input from the driver. Further, similar to the method of  FIG. 157 , a visual indicator can be activated based on the status of the low speed follow system  212  and the driver state (e.g., the hand contact determination at step  15908 ). For example, a light bar of the touch steering wheel  134  (See.  FIG. 18 ) can be activated to emit a red color thereby indicating to the driver that the low speed follow system is in a manual (e.g., not standard) state. 
     If it is determined that at least one hand is on the steering wheel, at step  15908 , the method includes receiving head movement and/or eye gaze information at step  15912  from the head movement monitoring system  334  and/or eye/facial movement monitoring system  332 . The head movement information can include information about a head pose and a head look of the driver as discussed above in Section III (B) (2) and with  FIGS. 16A, 16B and 17 . It is understood that the information from the head movement and/or eye gaze information from the head movement monitoring system  334  and/or eye/facial movement monitoring system  332  can be received at step  15912 . At step  15914 , it is determined if the head look and/or eye gaze is forward-looking based on the head movement information and/or eye gaze information. 
     If the head look and/or eye gaze is not forward-looking, the method proceeds to step  15910 . If the head look and/or eye gaze is forward-looking at step  15914 , then at step  15916 , the method includes the ECU  12902  setting the low speed follow system  212  status to auto control (e.g., turned ON, standard control). Accordingly, the low speed follow system  212  will be activated and move automatically based on the preceding vehicle. For example, in a stop and go situation, if the motor vehicle  100  is stopped and the preceding vehicle is stopped, the host vehicle will automatically move according to the preceding vehicle when the preceding vehicle moves without manual input from the driver. Further, a visual indicator can be activated based on the status of the low speed follow system and the driver state (e.g., hand contact, eye gaze and/or head look). For example, a light bar of the touch steering wheel  134  (See  FIG. 18 ) can be activated to emit a green color thereby indicating to the driver that the low speed follow system  212  is in an auto state. 
     Referring now to  FIG. 160 , a method for operating an automatic cruise control system in response to a driver state is illustrated. At step  16002 , the method includes the ECU  12902  receiving information from an automatic cruise control system  216  (e.g. monitoring information). At step  16004 , the ECU  12902  determines if a potential hazard exists based on the information from the automatic cruise control system  216 . For example, the ECU  12902  can detect a potential hazard as an object (e.g., a target vehicle) in front of the motor vehicle  100 . If a potential hazard does not exist, the method returns to step  16002 . Otherwise, the method proceeds to step  16006 . 
     At step  16006 , the method includes receiving head movement information (e.g., head look), for example from a head movement monitoring system  334  and/or eye gaze information, for example from an eye/facial movement monitoring system, and hand contact information from a touch steering wheel system  134 . The head movement information can include information about a head pose and a head look of the driver as discussed above in Section III (B) (2) and with  FIGS. 16A, 16B, and 17 . The hand contact information can include information about the contact and position of the driver&#39;s hands with respect to the steering wheel as described with  FIG. 18 . It is understood that the head movement information, eye gaze information and the hand contact information can be received at step  16002 . It should be noted that steps  16002  and  16004  are optional. In other words, the method can begin at step  16006  with receiving hand contact, eye gaze and/or head movement information as discussed below. 
     At step  16008 , the ECU  12902  can analyze the hand contact information, eye gaze information and/or the head movement information relative to the information received from the automatic cruise control system  216  (e.g., relative to the potential hazard). Said differently, the ECU  12902  can determine a head movement (e.g., head look) and/or eye gaze relative to the potential hazard, for example, the target vehicle, and hand contact relative to the touch steering wheel  134 . Accordingly, at step  16010 , the method includes determining a driver state and/or driver state index. For example, the driver state is determined based on monitoring information relative to the potential hazard. More specifically, in  FIG. 160 , the ECU  12902  determines the driver state based on at least the head movement information and/or eye gaze information, hand contact information received at step  16006 , and the analysis of the head movement information and/or eye gaze information, and hand contact information relative to the target vehicle at step  16008 . Said differently, the driver state and/or the driver state index is based at least in part on the head movement information and/or the eye gaze information, the hand contact information, and the target vehicle (e.g., the potential hazard). 
     In some embodiments, step  16010  can also include determining if the driver is attentive and/or distracted based on the driver state and/or driver state index. For example, if the hand contact information indicates the driver  102  has at least one hand on the touch steering wheel  134  and the head look and/or eye gaze is a forward-looking head look and/or eye gaze of the drive  102 , the driver state is determined to be attentive at step  16010 . If the hand contact information indicates the driver  102  has at least one hand on the touch steering wheel  134  and the head look and/or eye gaze is a non-forward-looking head look and/or eye gaze of the driver  102 , the driver state is determined to be distracted at step  16010 . 
     At step  16012 , the ECU  12902  modifies one or more vehicle systems based on the driver state. In one embodiment, the ECU  12902  modifies a control type of one or more vehicle systems including, for example, the lane keep assist system  226  and the automatic cruise control system  216 . For example, if the driver state is distracted, the ECU  12902  can set the control type (e.g., system status) of the automatic cruise control system  216  to partial and/or full control (e.g., ON). Thus, the ECU  12902  can control the automatic cruise control system  216  to slow down and/or increase a space between the motor vehicle  100  and the target vehicle automatically. Further, if the driver state is distracted, the ECU  12902  can set the control type of the lane keep assist system  226  to partial and/or full control (e.g., ON). Thus, the lane keep assist system  226  can provide assistance to keep the motor vehicle  100  within the current lane markers. In this way, the vehicle  100  can continue to drive within the current lane at its set cruise speed without requiring the driver  102  to be actively driving the vehicle (e.g., hands on the wheel, foot on the accelerator pedal, etc., while still requiring the driver  102  to be monitoring the progress of the vehicle (e.g. looking forward)). 
     Referring now to  FIGS. 161A and 161B , a schematic view of controlling one or more vehicle systems in accordance with the method of  FIG. 160  is shown. In  FIG. 161A , the motor vehicle  100  is travelling behind a preceding vehicle  16102  with automatic cruise control system  216  system status set to ON. Here, the head look of the driver  102  is forward-looking relative to the motor vehicle  100  and one hand is in contact with the touch steering wheel  134 . Based on the target vehicle, the head movement information and/or eye gaze information and the hand contact information, the ECU  12902  determines the driver state as attentive and the ECU  12902  sets the automatic cruise control system  216  to a medium gap. Therefore, the motor vehicle  100  maintains a predetermined headway distance  16104  behind the preceding vehicle  16102 . 
     In  FIG. 161B , the head look of the driver  102  is not forward-looking relative to the motor vehicle  100  (e.g., head looking down) and one hand is in contact with the touch steering wheel  134 . Based on the target vehicle, the head movement information and/or the eye gaze information, and the hand contact information, the ECU  12902  determines the driver state as distracted and the ECU  12902  sets the automatic cruise control system  216  to a maximum gap. Accordingly, the motor vehicle  100  controls the operation of the automatic cruise control system  216  so that the automatic cruise control system  216  increases the headway distance to a second headway distance  16106 . In another embodiment, the ECU  12902  sets the automatic cruise control system  216  to manual therefore requiring the driver the manually set control parameters of the automatic cruise control system  216 . 
     In  FIG. 161C , the motor vehicle  100  is travelling behind a preceding vehicle  16102  with automatic cruise control system  216  system status set to ON. Here, the head look of the driver  102  is forward-looking relative to the motor vehicle  100  and two hands are in contact with the touch steering wheel  134 . Based on the target vehicle, the head movement information and/or the eye gaze information, and the hand contact information, the ECU  12902  determines the driver state as attentive and the ECU  12902  sets the automatic cruise control system  216  to a minimum gap. Accordingly, the motor vehicle  100  controls the operation of the automatic cruise control system  216  so that the automatic cruise control system  216  decreases the headway distance to a third headway distance  16108 . As can be seen, since the driver  102  in  FIG. 161C  has both hands on the touch steering wheel  134 , the third headway distance (e.g., minimum gap) is smaller than the headway distance  16104  in  FIG. 161A  where the drier  102  only has one had on the touch steering wheel  134 . 
       FIG. 162  illustrates a method for controlling an automatic cruise control system and a lane keep assist system according to another exemplary embodiment. At step  16202 , the method includes receiving automatic cruise control information (e.g., monitoring information) from, for example, the automatic cruise control system  216 . At step  16204 , it is determined if a potential hazard exists. For example, it is determined if a potential hazard exists with a preceding vehicle based on the information from the automatic cruise control system  216 . If the determination at step  16204  is NO, the method returns to step  16202 . If the determination at step  16204  is yes, the method proceeds to step  16206 . It should be noted that steps  16202  and  16204  are optional. In other words, the method can begin at step  16206  with receiving hand contact and head movement information as discussed below. 
     At step  16206 , the method includes the ECU  12902  receiving hand contact information from the touch steering wheel system  134  and head movement information from the head movement monitoring system  334  and/or eye gaze information from the eye/facial movement monitoring system  332 . In some embodiments, the hand contact information, the head movement information and/or the eye gaze information can be received at step  16202 . The head movement information can include information about a head pose and a head look of the driver as discussed above in Section III (B) (2) and with  FIGS. 16A, 16B and 17 . 
     At step  16208 , the method includes determining if there is hand contact (e.g., at least one hand) with the steering wheel based on the hand contact information. More specifically, in the embodiment shown in  FIG. 162  it is determined if both hands are off the touch steering wheel  134 . If at least one hand is detected on the touch steering wheel  134 , the method proceeds to step  16214 . Otherwise, the method proceeds to step  16210 . At step  16210 , the method includes the ECU  12902  setting the lane keep assist system  226  status to auto control. Further, at step  16212 , the method includes setting the automatic cruise control system  216  status based on at least one of head look and head look duration (e.g., based on the head movement information). For example, if the head look is forward-looking, the headway distance of the automatic cruise control system  216  is set to a minimum gap. If the head look is in a non-forward-looking direction with a duration of more than a predetermined number of seconds (e.g., 2 seconds), the headway distance of the automatic cruise control system  216  is set to a medium gap. If the head look is in any direction with a duration of less than a predetermined number of seconds (e.g., 2 seconds), the headway distance of the automatic cruise control system  216  is set to a minimum gap. 
     Returning to step  16208 , if there at least one hand on the steering wheel, at step  16214 , the ECU  12902  sets the ECU  12902  sets the automatic cruise control system  216  to manual control (e.g., the headway distance is set by manual input). At step  16216 , the method includes setting a status of the lane keep assist system  226  based on at least one of hand contact, head look and head look duration (e.g., based on the head movement information). For example, if the left hand or right hand is detected on the wheel and the head look is forward-looking, the lane keep assist system  226  status is set to standard control. If the left hand or right hand is detected on the wheel and the head look is in a non-forward-looking direction for more than predetermined amount of time (e.g., 2 seconds), the lane keep assist system  226  status is set to auto control. In this way, the vehicle  100  can continue to drive within the current lane at its set cruise speed without requiring the driver  102  to be actively driving the vehicle (e.g., hands on the wheel, foot on the accelerator pedal, etc., while still requiring the driver  102  to be monitoring the progress of the vehicle (e.g. looking forward)). 
     As discussed briefly above, the lane keep assist system  226  in an auto control status can automatically control the electronic power steering system  132  to keep the vehicle in a predetermined lane based on identifying and monitoring lane markers of the predetermined lane. In some embodiments, there may be a break in the lane markers and/or the lane markers may not be identifiable. Accordingly, the control parameters of the lane keep assist system  226  can be modified based on a driver state in an auto control mode. Referring now to  FIG. 163  a method for controlling an automatic cruise control system and a lane keep assist system is shown. At step  16302 , the method includes receiving lane keep assist system and/or navigation information (e.g., monitoring information). At step  16304 , the method includes determining if there is a break in lane markers adjacent to the vehicle based on the monitoring information received at step  16302 . If the determination at  16304  is NO, the method returns to step  16302 . Otherwise, the method proceeds to step  16306 . At step  16306 , the method includes receiving blind spot indicator system information from the blind spot indicator system  224  and head movement information from the head movement monitoring system  334 . It is understood that the blind spot indicator information and the head movement information can be received at step  16302 . It should be understood that eye gaze information may be used instead of or in addition to head movement information to determine where the driver  102  is looking. At step  16308 , it is determined if there is a potential hazard (e.g., a target vehicle in a blind spot monitoring zone) relative to the break. If the determination at step  16308  is YES, the method returns to step  16302 . Otherwise, the method proceeds to step  16310  where the cruise control system  216  and the lane keep assist system  226  are modified based on head movement, the current lane and the break in the lane. 
       FIG. 164  illustrates a more detailed example of the method of  FIG. 163 . At step  16402 , the method includes receiving lane keep assist system information and/or navigation information, for example from the lane keep assist system  226  and/or the navigation system  230  (e.g., monitoring information). At step  16404 , it is determined if there is a break in the adjacent lane markers. The break can be identified, for example, by optical sensors of the lane keep assist system  226  and/or information from the navigation system  230 . For example, a break may be identified if the adjacent (e.g., adjacent to the motor vehicle  100 ) lane markers are not identifiable by the lane keep assist system (e.g., the lane markers are not clear, are obstructed, have faded away). In another embodiment, a break may occur based on current traffic patterns, for example, an exit off a highway. If the determination at step  16404  is NO, the method proceeds back to step  16402 . If the determination at step  16404  is YES, the method proceeds to step  16406 . At step  16406 , the method includes receiving head movement information. In some embodiments, the head movement information can be received by the head monitoring system  334  and the head movement information can be received at step  16402 . It should be understood that eye gaze information may be used instead of or in addition to head movement information to determine where the driver  102  is looking. 
     At step  16408  it is determined if the head look is forward-looking based on the head movement information. If YES, at step  16410 , the method includes the ECU  12902  controlling the automatic cruise control system  216  and the lane keep assist system  226  to maintain the motor vehicle system in the current lane according to the head look for the side of the vehicle without a break in the adjacent lane. Thus, the ECU  12902  can set the control status of the automatic cruise control system  216  and the lane keep assist system  226  to auto control, and the lane keep assist system  226  will maintain the vehicle in the current lane based on the adjacent lane marker without the break. 
     If NO, at step  16408 , the method includes determining if the head look is directed towards the break in the adjacent lanes at step  16412 . If NO, at step  16414 , the method proceeds to step  16410 . If YES, at step  16412 , the method includes receiving information from a blind spot indicator system  224  at step  16414 . At step  16416 , it is determined if a potential hazard exists relative to the break in the adjacent lanes based on the information received at step  16414 . For example, a potential hazard relative to the break exists if there is a target vehicle in a blind spot monitoring zone of the motor vehicle  100  in the same direction of the break in the adjacent lanes. 
     If YES, at step  16416 , the ECU  12902  modifies the automatic cruise control system  216  and lane keep assist system  226  according to the head look and the break in the adjacent lane at step  16418 . Accordingly, the lane keep assist system  226  can allow the vehicle to move according to the head look of the driver and break in the adjacent lanes. If NO, at step  16416 , the method proceeds to  16410  for maintaining the vehicle in the current lane via the automatic cruise control system  216  and lane keep assist system  226  in the current lane based on lane marker information (e.g., from the lane keep assist system) for the side of the vehicle without a break in the adjacent lane. It is appreciated that a visual indicator can also be provided to the driver based on the driver state and the system control of the vehicle. 
     Referring now to  FIGS. 165A and 165B , an illustrative example according to the method of  FIG. 164  is shown. Here, the motor vehicle  100  is travelling in a current lane  16502  with an adjacent left lane marker  16504  and an adjacent right lane marker  16506 . As the motor vehicle  100  approaches a break  16508  in the adjacent right lane marker  16506 , the ECU  12902  can determine a head look of the driver based on head movement information. In  FIG. 165A , the driver  102  has a head look directed forward (e.g., not towards the break  16508 ). Accordingly, the ECU  12902  controls the automatic cruise control system  216  and lane keep assist system  226  to maintain the motor vehicle  100  position in the current lane  16502 . Thus, the lane keep assist system  226  will use the adjacent left lane marker  16504  (e.g., the adjacent lane without the break) to guide the motor vehicle  100 . 
     In  FIG. 165B , the driver  102  has a head look directed towards the break  16508 . Additionally, a target vehicle  16510  is a predetermined distance  16512  forward of the motor vehicle  100 . If the target vehicle  16510  does not present a hazard, the ECU  12902  controls the automatic cruise control system  216  and lane keep assist system  226  based on the head look of the driver and the break  16508 , thereby controlling the vehicle to turn right. 
     While various embodiments have been described, the description is intended to be exemplary, rather than limiting and it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible that are within the scope of the embodiments. Accordingly, the embodiments are not to be restricted except in light of the attached claims and their equivalents. In addition, various modifications and changes can be made within the scope of the attached claims. 
     In accordance with one aspect, a method of controlling vehicle systems in a motor vehicle includes receiving monitoring information from one or more monitoring systems and determining a plurality of driver states based on the monitoring information from the one or more monitoring systems. The method also includes determining a combined driver state index based on the plurality of driver states and modifying control of one or more vehicle systems based on the combined driver state index. 
     Determining the combined driver state index is based on at least one selected of the plurality of driver states, at least one different selected of the plurality of driver states, and at least one other different selected of the plurality of driver states. Further, determining the combined driver state index is based on at least a first driver state selected from the plurality of driver states, a second driver state selected from the plurality of driver states, and a third driver state selected from the plurality of driver states. 
     Determining the combined driver state index includes aggregating the at least one selected of the plurality of driver states, the at least one different selected of the plurality of driver states, and the at least one other different selected of the plurality of driver states. In another embodiment, determining the combined driver state index includes aggregating the first driver state selected from the plurality of driver states, the second driver state selected from the plurality of driver states and the third driver state selected from the plurality of driver states. In a further embodiment, determining the combined driver state index includes determining an average of the at least one selected of the plurality of driver states, the at least one different selected of the plurality of driver states, and the at least one other different selected of the plurality of driver states. In an additional embodiment, determining the combined driver state index includes determining an average of the first driver state selected from the plurality of driver states, the second driver state selected from the plurality of driver states, and the third driver state selected from the plurality of driver states. 
     The plurality of driver states being at least one of the following driver state types: a physiological driver state, a behavioral driver state, or a vehicular-sensed driver state. The plurality of driver states are based on at least one of physiological information, behavioral information, and vehicular-sensed information. More specifically, the physiological driver state is based on physiological information, the behavioral driver state is based on behavioral information, and the vehicular-sensed driver state is based on vehicle information. 
     In one embodiment, the at least one selected of the plurality of driver states is a physiological driver state, the at least one different selected of the plurality of driver states is a behavioral driver state, and the at least one other different selected of the plurality of driver states is a vehicular-sensed driver state. Further, the at least one selected of the plurality of driver states is based on physiological information, the at least one different selected of the plurality of driver states is based on behavioral information, and the at least one other different selected of the plurality of driver states is based on vehicular-sensed information. The physiological information, the behavioral information and the vehicular-sensed information are types of monitoring information received from one or more monitoring systems. 
     In one embodiment, the first driver state selected from the plurality of driver states is a physiological driver state, the second driver state selected from the plurality of driver states is a behavioral driver state, and the third driver state selected from the plurality of driver states is a vehicular-sensed driver state. In another embodiment, the first driver state selected from the plurality of driver states is a based on physiological information, the second driver state selected from the plurality of driver states is based on behavioral information, and the third driver state selected from the plurality of driver states is based on vehicular-sensed information. 
     In a further embodiment, at least one selected of the plurality of driver states is a physiological driver state and the at least one different selected of the plurality of driver states is a behavioral driver state. The physiological driver state and the behavioral driver state are based on information from one of the monitoring systems. The one of the monitoring systems includes a sensor for receiving physiological information and behavioral information. The physiological driver state is based on the physiological information and the behavioral driver state is based on the behavioral information. In one embodiment, the physiological information is heart rate information and the behavioral information is head movement information. Further, the sensor is an optical sensor for receiving the physiological information and the behavioral information. 
     Determining the combined driver state also includes determining if the combined driver state indicates a distracted driver state. More specifically, determining the combined driver state includes determining if the first driver state selected from the plurality of driver states indicates a distracted driver state and the second driver state selected from the plurality of driver states indicates a distracted driver state. 
     Upon determining at least one of the first driver state selected from the plurality of driver states state or the second driver state selected from the plurality of driver states indicates a distracted driver state, the combined driver state is determined to indicate a distracted driver state. Upon determining at least one of the first driver state selected from the plurality of driver states or the second driver state selected from the plurality of driver states indicates a non-distracted driver state, the combined driver state is determined to indicate a non-distracted driver state. Further, upon determining the third driver state selected from the plurality of driver states indicates a distracted driver state, the combined driver state is determined to indicate a distracted driver state. 
     In one embodiment, determining the combined driver state is based on at least two selected of the plurality of driver states. The at least two selected of the plurality of driver states being the same driver state type. For example, the at least one selected of the plurality of driver states and the at least one different selected of the plurality of driver states are the same driver state type. As another example, the first driver state selected from the plurality of driver states and the second driver state selected from the plurality of driver states are the same driver state type. Further, the third driver state selected from the plurality of driver states is a different driver state than the first driver state and the second driver state. Accordingly, in one embodiment, the first driver state selected from the plurality of driver states and the second driver state selected from the plurality of driver states are behavioral driver states and the third driver state is a physiological driver state or a vehicular-sensed driver state. 
     In accordance with another embodiment, a method of controlling vehicle systems in a motor vehicle includes receiving monitoring information from one or more monitoring systems and determining a plurality of driver states based on the monitoring information from the one or more monitoring systems. The plurality of driver states being at least one of the following types of driver states: physiological driver state, behavioral driver state, and vehicular-sensed driver state. The method also includes determining a combined driver state index based on the plurality of driver states and modifying control of one or more vehicle systems based on the combined driver state index. Determining the combined driver state index is based on at least a first driver state selected from the plurality of driver states, a second driver state selected from the plurality of driver states and a third driver state selected from the plurality of driver states. The first driver state, the second driver state, and the third driver state are each a different type of driver state. In one embodiment, the first driver state and the second driver state are the same type of driver state and the third driver state is a different type of driver state than the first driver state and the second driver state. 
     Further, determining the combined driver state index includes comparing the one or more of the plurality of driver states to at least one threshold and includes comparing at least one of the first driver state, the second driver state and the third driver state to respective thresholds, and determining the combined driver state index based on the comparison. In one embodiment, determining the combined driver state index further includes comparing the first driver state to a first driver state threshold, comparing the second driver state to a second driver state threshold and comparing the third driver state to a third driver state threshold, and determining the combined driver state based on the comparison. Upon determining the first driver state meets the first driver state threshold and the second driver state meets the second driver state threshold, the combined driver state index is based on the first driver state and the second driver state. 
     Further, determining the combined driver state index includes confirming at least one selected of the plurality of driver states with at least one different selected of the plurality of driver states, and confirming the at least one selected of the plurality of driver states, the at least one different selected of the plurality of driver states, with at least another one of the plurality of driver states. Confirming includes determining if the at least one selected of the plurality of driver states and the at least one different selected of the plurality of driver states indicate a distracted driver state. Upon determining the at least one selected of the plurality of driver states and the at least one different selected of the plurality of driver states indicate a distracted driver state, determining the combined driver state index is based on the at least one selected of the plurality of driver states and the at least one different selected of the plurality of driver states. 
     In one embodiment, confirming the at least one selected of the plurality of driver states with the at least one different selected of the plurality of driver states further includes comparing the at least one selected of the plurality of driver states to a first threshold and comparing the at least one different selected of the plurality of driver states to a second threshold. The first threshold and the second threshold indicate a distracted driver state. Upon determining the at least one selected of the plurality of driver states meets the first threshold and the at least one different selected of the plurality of driver states meets the second threshold, determining the combined driver state index is based on the at least one selected of the plurality of driver states and the at least one different selected of the plurality of driver states. The first driver state threshold, the second driver state threshold and the third driver state threshold are values that indicate a distracted driver state. In one embodiment, the first driver state threshold, the second driver state threshold and the third driver state threshold are pre-determined thresholds based on at least one of: the type of driver state, the monitoring information used to determine the plurality of driver states, and an identity of the driver. 
     In one embodiment, the method includes modifying the first driver state threshold, the second driver state threshold and the third driver state threshold based on at least one of: the type of driver state, the monitoring information used to determine the plurality of driver states, and the identity of the driver. The threshold, the first driver state threshold, the second driver state threshold and the third driver state threshold are determine and/or modified based on the identity of the driver, the identity of the driver determined by one of the monitoring systems. In another embodiment, the threshold, the first driver state threshold, the second driver state threshold and the third driver state threshold is determine and/or modified based on learned baseline data associated with the driver. In a further embodiment, the threshold, the first driver state threshold, the second driver state threshold and the third driver state threshold are determine and/or modified based on normative data for other drivers with similar characteristics of the driver. In still another embodiment, the threshold, the first driver state threshold, the second driver state threshold and the third driver state threshold is determine and/or modified based on a pattern of monitoring information over a period of time associated with the driver. In some embodiments, the first driver state threshold, the second driver state threshold and the third driver state threshold is determined and/or modified based on monitoring information indicating an inattentive driver. 
     In one embodiment, the first driver state is a vehicular-sensed driver state based on steering wheel monitoring information and the first driver state threshold is a number of steering wheel jerks over the period of time that indicates the driver is distracted. In another embodiment, the first driver state is a behavioral driver state based on head movement monitoring information and the first driver state threshold is a number of head nods based on the head movement monitoring information over the period of time that indicates the driver is distracted. 
     In accordance with a further embodiment, a method of controlling vehicle systems in a motor vehicle includes receiving monitoring information from a plurality of monitoring systems and determining a plurality of driver states based on the monitoring information from the plurality of monitoring systems. The method also includes determining a combined driver state index based on the plurality of driver states and modifying control of one or more vehicle systems based on the combined driver state index. The method further includes determining a potential hazard based on monitoring information from one or more vehicle systems. Additionally, the method includes determining if the driver is distracted based on the combined driver state index. The method also includes determining an auto control status of the vehicle or one or more vehicle systems. 
     Upon determining the driver is not distracted, modifying control of one or more vehicle systems includes changing a control status of one or more vehicle systems to no control. Upon determining the driver is distracted and the auto control status is set to auto, modifying control of one or more vehicle systems includes changing a control status of one or more vehicle systems to auto control. 
     Determining the combined driver state index is based on analyzing head movement information and hand contact information relative to the potential hazard. The head movement information and the hand contact information are received from the plurality of monitoring systems. 
     In one embodiment, upon determining the potential hazard is a lane deviation based on monitoring information from a lane departure warning system, determining the combined driver state index includes analyzing head movement information relative to the lane deviation. In another embodiment, upon determining the potential hazard is a target vehicle in a blind spot monitoring zone of the vehicle based on monitoring information from a blind spot indicator system, determining the combined driver state index includes analyzing head movement information or hand contact information relative to the target vehicle or the blind spot monitoring zone. 
     In another embodiment, upon determining the potential hazard is a preceding vehicle in front of the vehicle based on monitoring information from an automatic cruise control system, determining the combined driver state index includes analyzing head movement information or hand contact information relative to the preceding vehicle. Analyzing head movement information includes determining a head look direction in relation to a direction of the hazard. Analyzing hand contact information includes determining contact of a least one hand of a driver with a steering wheel of the vehicle. Upon determining the head look direction is forward-looking relative to the vehicle or the head look direction is directed in the same direction as the direction of the hazard, the combined driver state index is determined to be attentive, and modifying control of the one or more vehicle systems includes setting a control status of the one or more vehicle systems to no control. Upon determining the head look direction is forward-looking relative to the vehicle or the head look direction is directed in the same direction as the direction of the hazard and upon determining at least one hand of the driver is in contact with the steering wheel, the combined driver state index is determined to be attentive, and modifying control of the one or more vehicle systems includes setting a control status of the one or more vehicle systems to no control. 
     In another embodiment, upon determining the potential hazard is a preceding vehicle based on monitoring information from a low speed follow system and the auto control mode is set to ON, determining the combined driver state index includes analyzing head movement information or hand contact information. Upon determining at least one hand of a driver is in contact with a steering wheel of the vehicle and a direction of a head look of the driver based on the head monitoring information is in a forward-looking direction relative to the vehicle, a control status of the low speed follow system is set to auto control. Further, upon determining no hand contract with a steering wheel of the vehicle, a control status of a lane keep assist system is set to auto control and a control status of an automatic cruise control status is set based on the head monitoring information. The head monitoring information includes a head look direction and a head look duration. In a further embodiment, upon determining at least one hand is in contact with a steering wheel of the vehicle, a control status of an automatic cruise control system is set to manual control and a control status of a lane keep assist system is set based on the head monitoring information. The head monitoring information includes a head look direction and a head look duration.