Abstract:
A predictive enhanced maneuverability system providing enhanced timely delivery of vehicle performance selection of chassis, and steering modes for potential predicted safety collisions is disclosed. The primary inputs of the disclosed invention include a determination of the proximity to a preceding vehicle, the density of the surrounding traffic, a forward collision warning alert, and the predictive enhanced maneuverability decision sub-system for vehicle mode selection. The system of the disclosed invention provides a customized vehicle dynamics chassis and steering dynamic mode output, based on a predicted decision about vehicle potential for collision, for improved driver maneuverability and safety. In addition, the disclosed invention provides an improved system and method for incorporating the time dependent headway, forward collision warning alert, and the traffic density for chassis collision-mode embedded decision-making. The predictive enhanced maneuverability decision-module allows vehicle dynamics mode selection to be tailored based on proximity to a potential collision.

Description:
TECHNICAL FIELD 
     The disclosed invention relates generally to adaptive systems for automotive vehicles. More particularly, the disclosed invention relates to a predictive enhanced maneuverability arrangement that provides timely delivery of vehicle performance selection between chassis and steering modes for potential predicted safety collisions. 
     BACKGROUND OF THE INVENTION 
     Automotive technology capable of delivering automatic vehicle mode adaptation based on the driver, the vehicle, and environmental conditions is a developing area of technology. While variations of adaptive technologies are known, in some known instances the automatic vehicle mode demonstrates adaptive vehicle dynamics and powertrain mode selection from, for example, sporty, normal, and comfort to enhance the overall driving experience. 
     However, development of adaptive technologies is still in the early stage and other opportunities to augment known adaptive vehicle systems exist. These advancements may be achieved by leveraging predictive sensing and information capabilities on vehicles to cover more scenarios for improved driver convenience and safety. 
     The challenge is to develop additional methods that can in real-time predict situations to enhance the automotive mode selection for the vehicle. For example, it is beneficial to have a method that would intelligently select the chassis steering and suspension combination for enhanced maneuverability for a predicted potential collision. 
     Innovative vehicle technologies provide significant opportunities for enhanced adaptive vehicle systems to meet the needs of tailored vehicle performance and customization. 
     SUMMARY OF THE INVENTION 
     The disclosed invention overcomes several of the problems of the prior art by providing an improved method and system in the form of a predictive enhanced maneuverability system including a dedicated module to augment known adaptive vehicle systems. The predictive enhanced maneuverability system according to the disclosed invention provides enhanced timely delivery of vehicle performance selection of chassis, and steering modes for potential predicted safety collisions. 
     The primary inputs of the disclosed invention include a determination of the proximity to a preceding vehicle, the density of the surrounding traffic, a forward collision warning alert, and the predictive enhanced maneuverability decision sub-system for vehicle mode selection. 
     The predictive enhanced maneuverability system of the disclosed invention offers several distinct advantages over the known art. Particularly, the system of the disclosed invention provides a customized vehicle dynamics chassis and steering dynamic mode output, based on a predicted decision about vehicle potential for collision, for improved driver maneuverability and safety. 
     In addition, the disclosed invention provides an improved system and method for incorporating the time dependent headway, forward collision warning alert, and the traffic density for chassis collision-mode embedded decision-making. The predictive enhanced maneuverability decision-module allows vehicle dynamics mode selection to be tailored based on proximity to potential collision. 
     When the system of the disclosed invention is in operation, highly predictive risk scenarios from longitudinal situations are given priority for driver safety. In addition, surrounding traffic density computed from environmental sensors including blind spot information systems are leveraged for the traffic density input. Furthermore, the time dependent headway and forward collision warning alert decision-level combination provide additional reliability to ensure reliable mode transition when enhanced vehicle maneuverability is required. 
     The above advantages and other advantages and features will be readily apparent from the following detailed description of the preferred embodiments when taken in connection with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a more complete understanding of this invention, reference should now be made to the embodiments illustrated in greater detail in the accompanying drawings and described below by way of examples of the invention wherein: 
         FIG. 1  illustrates a block diagram of the predictive enhanced maneuverability system of the disclosed invention; 
         FIG. 2  illustrates a potential collision scenario that may be encountered by a vehicle in which the driver may need to maneuver from the vehicle ahead; 
         FIG. 3  illustrates a potential collision scenario with traffic that may be encountered by a vehicle in which the driver may need to maneuver from the vehicle ahead; 
         FIG. 4  is a predictive enhanced maneuverability decision-making surface plot depicting normalized suspension mode output; and 
         FIG. 5  is a decision making surface plot depicting normalized steering mode output. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
     In the following figures, the same reference numerals will be used to refer to the same components. In the following description, various operating parameters and components are described for different constructed embodiments. These specific parameters and components are included as examples and are not meant to be limiting. 
     In general, the disclosed invention provides a tailored, adaptive vehicle system under various vehicle, driver and environment scenarios. The predictive enhanced maneuverability (PEM) system of the disclosed invention intelligently selects the chassis steering and suspension combination for enhanced maneuverability for a predicted potential collision. 
     Referring to  FIG. 1 , a block diagram of the predictive enhanced maneuverability decision-making system, generally illustrated as  10 , is shown. The predictive enhanced maneuverability decision-making system  10  receives a number of inputs including a time dependent headway (TDH) input  12 , a traffic density (TRD) input  14 , and a forward collision warning alert (FCWA) input  16 . The time dependent headway input  12 , the traffic density input  14 , and the forward collision warning alert input  16  represent vehicle environment situational characterization. 
     A predictive enhanced maneuverability decision-making module  18  receives information from the time dependent headway input  12 , the traffic density input  14 , and a forward collision warning alert input  16  and determines the chassis suspension and steering modes  20 . The predictive enhanced maneuverability decision-making module  18  also receives status information from the vehicle system  22 . Reliable inputs for the predictive enhanced maneuverability decision module  18  are significant to assure correct mode selection decisions. 
     The predictive enhanced maneuverability mode selection is executed only during situations when critical countermeasure maneuvers are required to avoid potential collision. The predictive enhanced maneuverability decision-making module may apply a rule-based computational approach to determine the tailored mode selection for potential collision. As shown in  FIG. 1 , the predictive enhanced maneuverability rule-based sub-system  10  includes a knowledge base and facts for determining the recommended chassis and steering mode  20 . 
     For example, each predictive enhanced maneuverability rule specifies a recommendation of the output chassis mode, and has the IF (condition), THEN (action) structure. When the condition part of a rule is satisfied, the action part is executed. Each rule may specify a recommendation of the output chassis mode (original, normal, sport). Original means the mode is not changed and retains the last mode. 
     A general rule implemented by the predictive enhanced maneuverability is of the form,
 
{If TDH is  x   i  and TDR is  y   i  and FCWA is  z   i  then chassis mode is  m   i }  (1)
 
{If TDH is  x   i  and TDR is  y   i  and FCWA is  z   i  then suspension mode is  s   i }  (2)
 
     The TDH is obtained from recursive computation of the current and mean time dependent headway. 
     
       
         
           
             
               
                 
                   
                     T 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     D 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     
                       H 
                       curr 
                     
                   
                   = 
                   
                     
                       ( 
                       
                         
                           
                             r 
                             p 
                           
                           ⁡ 
                           
                             ( 
                             k 
                             ) 
                           
                         
                         - 
                         
                           
                             r 
                             f 
                           
                           ⁡ 
                           
                             ( 
                             k 
                             ) 
                           
                         
                       
                       ) 
                     
                     
                       
                         v 
                         f 
                       
                       ⁡ 
                       
                         ( 
                         k 
                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   3 
                   ) 
                 
               
             
           
         
       
     
     where r p (k) is the position of the preceding vehicle at any time instant k, r f (k) is the position of the following vehicle and v f (k) is the velocity of the following vehicle. The mean time dependent headway, TDH m (k), may be obtained from
 
TDH M ( k )=TDH M ( k− 1)+α(TDH curr −TDH M ( k− 1))  (4)
 
     Alpha is chosen to obtain longer-term headway information compared to the forward collision warning alert responds. The forward collision warning alert is obtained from the forward collision warning alert system on certain vehicles. The forward collision warning alert is obtained from 
               F   ⁢           ⁢   C   ⁢           ⁢   W   ⁢           ⁢   A     =     {           1   ·     z     -   D                 if   ⁢           ⁢   F   ⁢           ⁢   C   ⁢           ⁢   W   ⁢           ⁢   alert   ⁢           ⁢   is   ⁢           ⁢   ON     =   1             0       otherwise                 
D is the number of sample delays when the FCW alert is generated.
 
     The delay pipeline is incorporated when the FCW alert is produced to avoid limit cycling should repeated alerts occur and to hold the signal for effective decision-making. By combining the TDH and FCWA in decision-making, increased assurance of predictive close following is obtained for the predictive enhanced maneuverability. The predictive enhanced maneuverability decision-making system then avoids reaction to spurious forward collision warning alerts. 
     Traffic conditions provided by the TRD is based on information obtained continuously from, for example, a blind spot detection system or side detection system, the following assumptions are made: 
     (i) traffic density around the operating vehicle is highly correlated with vehicles passing the host vehicle; 
     (ii) the traffic density is estimated and quantified by signal processing and real-time computation of input signals indicative of cars entering or exiting the blind spot. 
     The real-time exponential signal generation functions for the left and right sides of the vehicle are given by
 
 R _TDE new   =ff·R _TDE old +(1 −ff )· y   r   (6)
 
 L _TDE new   =ff·L _TDE old +(1 −ff )· y   l   (7)
 
where R_TDE new  and L_TDE new  are the vehicle right side and vehicle left side traffic density estimates, respectively, with values between 0 and 1. R_TDE old  and L_TDE old  are the previous one sample estimates of R_TDE new  and L_TDE new , respectively. The current right and left, blind spot information system (BLIS) alert input signals are given by y r  and y l  respectively, and ff is the exponential forgetting factor. R_TDE new  and L_TDE new  values close to one indicate high traffic density.
 
     The predictive enhanced maneuverability decision-making system  10  of the disclosed invention may play a role in vehicle operation under a number of different collision scenarios. One such situation is illustrated in  FIG. 2  in which a potential collision scenario is depicted on a roadway  30  in which a host vehicle  32  is shown in relation to a preceding vehicle  34  and an adjacent vehicle  36 . 
     The host vehicle  32  includes a short-range sensor  38  and a long-range sensor  40 . The short-range sensor  38  has a short-range field of view  42  while the long-range sensor  40  has a long-range field of view  44 . The host vehicle  32  also includes a first side sensor  46  and a second side sensor  48 . The first side sensor  46  has a short-range field of view  50  and the second side sensor  48  has a short-range field of view  52 . In operation the short-range sensor  38 , the long-range sensor  40 , the first side sensor  46  and the second side sensor  48  are active whenever the host vehicle  32  is in operation. 
     In the scenario illustrated in  FIG. 2 , the driver of the host vehicle  32  may need to maneuver from the preceding vehicle  34  ahead. The proximity of the preceding vehicle  32  is sensed by the long-range sensor  40  as being within the long-range field of view  44 . 
     With the predictive enhanced maneuverability decision-making system  10  of the disclosed invention identifying a potential collision scenario, if the forward collision warning alert is ON and both the time dependent headway (TDH) and the traffic density (TDR) are low as illustrated in  FIG. 2 , then both the chassis and the steering are assigned sport mode. 
     Another scenario in which the predictive enhanced maneuverability decision-making system  10  of the disclosed invention may play a role in vehicle operation is illustrated in  FIG. 3 . In this figure, a potential collision scenario is depicted on a roadway  53  in which the host vehicle  32  is shown in relation to a near preceding vehicle  54  and a distant preceding vehicle  56 . In addition, adjacent vehicles  58 ,  60  and  62  are illustrated as being on the roadway  53 . As discussed above with respect to  FIG. 2 , the short-range sensor  38 , the long-range sensor  40 , the first side sensor  46  and the second side sensor  48  are active whenever the host vehicle  32  is in operation. 
     The driver of the host vehicle  52  shown in  FIG. 3  may need to maneuver from the preceding vehicles  54  and  56  ahead taking into particular consideration the adjacent vehicle  58 . In such a potential collision scenario, the relative nearness of the near preceding vehicle  54  is sensed by the short-range sensor  38  while the proximity of the adjacent vehicle  58  is sensed by the first side sensor  46 . All of this information is incorporated by the predictive enhanced maneuverability decision-making system  10  of the disclosed invention. If the forward collision warning alert is ON and the time dependent headway (TDH) is low but the traffic density (TDR) is high as illustrated in  FIG. 3 , then the chassis is in sport mode while the steering is assigned normal mode. 
       FIG. 4  illustrates the predictive enhanced maneuverability decision-making surface plot for suspension-mode outputs based on time dependent headway (TDH), traffic density (TRD), and a fixed high forward collision warning alert (FCWA) (1.0). Time dependent headway numbers closer to 0.0 represent situations where the predicted host vehicle time dependent headway is relatively closer to a preceding vehicle, while values closer to 1 represent the vehicle further away from a preceding vehicle. Traffic density values closer to 1 represent predicted higher traffic density. 
     Accordingly, sport-mode (output &gt;0.7) is selected for the suspension mode when the time dependent headway is low and the traffic density is high for predicted potential collision scenarios. 
       FIG. 5  illustrates the predictive enhanced maneuverability decision-making surface plot for steering-mode outputs based on time dependent headway (TDH), traffic density (TRD) and fixed high forward collision warning alert (FCWA) (1.0). Sport steering-mode (steer-mode value &gt;0.7) is selected for predicted potential collisions, when the traffic density is low and the time dependent headway is low. The steering mode is left in the original mode or normal mode if the host vehicle is further away from the preceding vehicle. 
     The predictive enhanced maneuverability system of the disclosed invention as set forth above provides an intelligent system and means to select chassis steering and suspension combinations for enhanced maneuverability with predicted environmental scenario inputs. 
     The foregoing discussion discloses and describes exemplary embodiments of the present invention. One skilled in the art will readily recognize from such discussion, and from the accompanying drawings and claims that various changes, modifications and variations can be made therein without departing from the true spirit and fair scope of the invention as defined by the following claims.