Patent Publication Number: US-2020290620-A1

Title: Method and apparatus for high definition map based vehicle control for assisted driving

Description:
BACKGROUND 
     The present disclosure relates generally to programming autonomous motor vehicle control systems. More specifically, aspects of this disclosure relate to systems, methods and devices for behavior planning using high definition map and radar sensor data for longitudinal and latitudinal control for autonomous vehicles in a complicated environment. 
     The operation of modern vehicles is becoming more automated, i.e. able to provide driving control with less and less driver intervention. Vehicle automation has been categorized into numerical levels ranging from Zero, corresponding to no automation with full human control, to Five, corresponding to full automation with no human control. Various automated driver-assistance systems, such as cruise control, adaptive cruise control, and parking assistance systems correspond to lower automation levels, while true “driverless” vehicles correspond to higher automation levels. 
     Appropriate situation awareness is essential for autonomous driving due to safety concerns. Even though it is desirable to put all available information into autonomous driving decision process; however, for practical implementation, input data to the system should be limited and manageable; therefore the decision process needs to be well-designed for both efficiency and sufficiency for decision making. An autonomous vehicle generally must generate a data structure to perceive situations around the vehicle. Through sensors mounted on the autonomous driving vehicle, a huge amount of information is delivered to the system; therefore, efficient analysis of all perception data for safe driving is crucial. 
     Typically, in an assisted driving control system, all available data is collected and combined in a three dimensional map, trajectory data about surrounding objects is calculated, the future locations of the objects are predicted, and a safe path for the controlled vehicle is estimated. All of this computation is processor intensive and requires excessive time and power which limits the performance of an assisted driving vehicle. It would be desirable to provide a realistic and light assisted driving control system for reinforced learning based active training for autonomous vehicle longitudinal and lateral control with reduced sensor data. 
     The above information disclosed in this background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. 
     SUMMARY 
     Disclosed herein are autonomous vehicle control system training systems and related control logic for provisioning autonomous vehicle control, methods for making and methods for operating such systems, and motor vehicles equipped with onboard control systems. By way of example, and not limitation, there is presented an automobile with onboard vehicle control learning and control systems. 
     In accordance with an aspect of the present invention, a method for controlling a vehicle comprising determining a following distance between a host vehicle and a lead vehicle and a lead vehicle speed, generating a lane change request in response to the following distance, a host vehicle speed and the lead vehicle speed, determining an available lane in response to an image and the lane change request, generating a lane change command in response to the available lane, and generating a control signal in response to the lane change request and a map data, and controlling the vehicle to execute a lane change action in response to the control signal. 
     In accordance with another aspect of the present invention wherein the control signal is further generated in response to a global positioning system data. 
     In accordance with another aspect of the present invention wherein the host vehicle speed is reduced in response to the available lane indicating that a lane is not available. 
     In accordance with another aspect of the present invention wherein the following distance is determined in response to a radar signal. 
     In accordance with another aspect of the present invention wherein the image is generated by a side view camera mounted on the host vehicle. 
     In accordance with another aspect of the present invention wherein the control signal is generated in response to a lane change action episode and the map data. 
     In accordance with another aspect of the present invention further comprising updating a lane change episode in response to the control. 
     In accordance with another aspect of the present invention an apparatus comprising a first processor for calculating a following distance in response to a radar data file and for generating a change lane request in response to the following distance being less than a threshold value, a second processor for receiving the change lane request and for determining a lane availability in response to an image and the change lane request and for generating a lane change control signal in response to the lane availability, a third processor for calculating a lane change route in response to a map data, and the lane change control signal, a memory for storing an episode generated in response to the radar data, the lane change request, the lane availability compiler and the lane change route, and a vehicle controller executing a lane change in response to the episode. 
     In accordance with another aspect of the present invention wherein the first processor is a longitudinal processor for maintaining the following distance in an adaptive cruise control system. 
     In accordance with another aspect of the present invention wherein the second processor is a latitudinal processor for performing a lane centering operation in an adaptive cruise control system. 
     In accordance with another aspect of the present invention wherein the third processor is a lane change processor for performing the lane change in an adaptive cruise control system. 
     In accordance with another aspect of the present invention wherein the radar data file is generated in response to a vehicular adaptive cruise control data log. 
     In accordance with another aspect of the present invention wherein the lane change is executed before the following distance reaches a minimum value. 
     In accordance with another aspect of the present invention wherein the episode is generated in response to multiple lane change actions. 
     In accordance with another aspect of the present invention a vehicular control system comprising a memory for storing a lane change episode and a map data, a radar sensor for detecting a distance to a lead vehicle, a first processor for generating a lane change request in response to the distance, a camera for generating an image of an adjacent lane, a second processor for determining a lane availability in response to the image and for generating a lane change command in response to the lane availability, a third processor for determining a lane change route in response to the lane change command, the episode, the map data and for generating a lane change control signal in response to the lane change route, and a vehicle controller for executing the lane change in response to the lane change control signal. 
     In accordance with another aspect of the present invention wherein the first processor is a longitudinal processor for maintaining the following distance in an adaptive cruise control system. 
     In accordance with another aspect of the present invention wherein the second processor is a latitudinal processor for performing a lane centering operation in an adaptive cruise control system. 
     In accordance with another aspect of the present invention wherein the third processor is a lane change processor for controlling the lane change in an adaptive cruise control system. 
     In accordance with another aspect of the present invention wherein the vehicular control system is operative to perform an adaptive cruise control function in an assisted driving equipped vehicle. 
     In accordance with another aspect of the present invention wherein the third processor is further operative to update the episode according to a reinforced learning algorithm. 
     The above advantage and other advantages and features of the present disclosure will be apparent from the following detailed description of the preferred embodiments when taken in connection with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The above-mentioned and other features and advantages of this invention, and the manner of attaining them, will become more apparent and the invention will be better understood by reference to the following description of embodiments of the invention taken in conjunction with the accompanying drawings. 
         FIG. 1  shows an operating environment that comprises a mobile vehicle communication and control system for a motor vehicle according to an exemplary embodiment. 
         FIG. 2  shows a block diagram illustrating a system for high definition map based vehicle control for assisted driving according to an exemplary embodiment. 
         FIG. 3  shows a flow chart illustrating a method for high definition map based vehicle control system training for assisted driving according to another exemplary embodiment. 
         FIG. 4  shows a block diagram illustrating an exemplary implementation of a system for high definition map based vehicle control for assisted driving in a vehicle. 
         FIG. 5  shows a flow chart illustrating a method for high definition map based vehicle control for assisted driving according to another exemplary embodiment 
     
    
    
     The exemplifications set out herein illustrate preferred embodiments of the invention, and such exemplifications are not to be construed as limiting the scope of the invention in any manner. 
     DETAILED DESCRIPTION 
     Embodiments of the present disclosure are described herein. It is to be understood, however, that the disclosed embodiments are merely examples and other embodiments can take various and alternative forms. The figures are not necessarily to scale; some features could be exaggerated or minimized to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but are merely representative. The various features illustrated and described with reference to any one of the figures can be combined with features illustrated in one or more other figures to produce embodiments that are not explicitly illustrated or described. The combinations of features illustrated provide representative embodiments for typical applications. Various combinations and modifications of the features consistent with the teachings of this disclosure, however, could be desired for particular applications or implementations. 
       FIG. 1  schematically illustrates an operating environment that comprises a mobile vehicle communication and control system  100  for a motor vehicle  12 . The communication and control system  10  for the vehicle  12  generally includes one or more wireless carrier systems  60 , a land communications network  62 , a computer  64 , a networked wireless device  57  including but not limited to a smart phone, tablet, or wearable device such as a watch, and a remote access center  78 . 
     The vehicle  12 , shown schematically in  FIG. 1 , includes a propulsion system  13 , which may in various embodiments include an internal combustion engine, an electric machine such as a traction motor, and/or a fuel cell propulsion system. Vehicle  12  is depicted in the illustrated embodiment as a passenger car, but it should be appreciated that any other vehicle including motorcycles, trucks, sport utility vehicles (SUVs), recreational vehicles (RVs), marine vessels, aircraft, etc., can also be used. 
     The vehicle  12  also includes a transmission  14  configured to transmit power from the propulsion system  13  to a plurality of vehicle wheels  15  according to selectable speed ratios. According to various embodiments, the transmission  14  may include a step-ratio automatic transmission, a continuously-variable transmission, or other appropriate transmission. The vehicle  12  additionally includes wheel brakes  17  configured to provide braking torque to the vehicle wheels  15 . The wheel brakes  17  may, in various embodiments, include friction brakes, a regenerative braking system such as an electric machine, and/or other appropriate braking systems. 
     The vehicle  12  additionally includes a steering system  16 . While depicted as including a steering wheel for illustrative purposes, in some embodiments contemplated within the scope of the present disclosure, the steering system  16  may not include a steering wheel. 
     The vehicle  12  includes a wireless communications system  28  configured to wirelessly communicate with other vehicles (“V2V”) and/or infrastructure (“V2I”). In an exemplary embodiment, the wireless communication system  28  is configured to communicate via a wireless local area network (WLAN) using IEEE 802.11 standards or by using cellular data communication. However, additional or alternate communication methods, such as a dedicated short-range communications (DSRC) channel, are also considered within the scope of the present disclosure. DSRC channels refer to one-way or two-way short-range to medium-range wireless communication channels specifically designed for automotive use and a corresponding set of protocols and standards. 
     The propulsion system  13 , transmission  14 , steering system  16 , and wheel brakes  17  are in communication with or under the control of at least one controller  22 . While depicted as a single unit for illustrative purposes, the controller  22  may additionally include one or more other controllers, collectively referred to as a “controller.” The controller  22  may include a microprocessor such as a central processing unit (CPU) or graphics processing unit (GPU) in communication with various types of computer readable storage devices or media. Computer readable storage devices or media may include volatile and nonvolatile storage in read-only memory (ROM), random-access memory (RAM), and keep-alive memory (KAM), for example. KAM is a persistent or non-volatile memory that may be used to store various operating variables while the CPU is powered down. Computer-readable storage devices or media may be implemented using any of a number of known memory devices such as PROMs (programmable read-only memory), EPROMs (electrically PROM), EEPROMs (electrically erasable PROM), flash memory, or any other electric, magnetic, optical, or combination memory devices capable of storing data, some of which represent executable instructions, used by the controller  22  in controlling the vehicle. 
     The controller  22  includes an automated driving system (ADS)  24  for automatically controlling various actuators in the vehicle. In an exemplary embodiment, the ADS  24  is a so-called Level Four or Level Five automation system. A Level Four system indicates “high automation”, referring to the driving mode-specific performance by an automated driving system of all aspects of the dynamic driving task, even if a human driver does not respond appropriately to a request to intervene. A Level Five system indicates “full automation”, referring to the full-time performance by an automated driving system of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver. In an exemplary embodiment, the ADS  24  is configured to control the propulsion system  13 , transmission  14 , steering system  16 , and wheel brakes  17  to control vehicle acceleration, steering, and braking, respectively, without human intervention via a plurality of actuators  30  in response to inputs from a plurality of sensors  26 , which may include GPS, RADAR, LIDAR, optical cameras, thermal cameras, ultrasonic sensors, and/or additional sensors as appropriate. 
       FIG. 1  illustrates several networked devices that can communicate with the wireless communication system  28  of the vehicle  12 . One of the networked devices that can communicate with the vehicle  12  via the wireless communication system  28  is the networked wireless device  57 . The networked wireless device  57  can include computer processing capability, a transceiver capable of communicating using a short-range wireless protocol, and a visual display. The computer processing capability includes a microprocessor in the form of a programmable device that includes one or more instructions stored in an internal memory structure and applied to receive binary input to create binary output. In some embodiments, the networked wireless device  57  includes a GPS module capable of receiving GPS satellite signals and generating GPS coordinates based on those signals. In other embodiments, the networked wireless device  57  includes cellular communications functionality such that the networked wireless device  57  carries out voice and/or data communications over a wireless carrier system using one or more cellular communications protocols, as are discussed herein. The visual display may also include a touch-screen graphical user interface. 
     The wireless carrier system is preferably a cellular telephone system that includes a plurality of cell towers  70  (only one shown), one or more mobile switching centers (MSCs), as well as any other networking components required to connect the wireless carrier system with the land communications network  62 . Each cell tower  70  may include sending and receiving antennas and a base station, with the base stations from different cell towers being connected to the MSC either directly or via intermediary equipment such as a base station controller. The wireless carrier system can implement any suitable communications technology, including for example, digital technologies such as CDMA (e.g., CDMA2000), LTE (e.g., 4G LTE or 5G LTE), GSM/GPRS, or other current or emerging wireless technologies. Other cell tower/base station/MSC arrangements are possible and could be used with the wireless carrier system. For example, the base station and cell tower could be co-located at the same site or they could be remotely located from one another, each base station could be responsible for a single cell tower or a single base station could service various cell towers, or various base stations could be coupled to a single MSC, to name but a few of the possible arrangements. 
     Apart from using the wireless carrier system, a second wireless carrier system in the form of satellite communication can be used to provide uni-directional or bi-directional communication with the vehicle  12 . This can be done using one or more communication satellites  66  and an uplink transmitting station coupled to the communications network  62 . Uni-directional communication can include, for example, satellite radio services, wherein programming content (news, music, etc.) is received by the transmitting station, packaged for upload, and then sent to the satellite  66 , which broadcasts the programming to subscribers. Bi-directional communication can include, for example, satellite telephony services using the satellite  66  to relay telephone communications between the vehicle  12  and the communications network  62 . The satellite telephony can be utilized either in addition to or in lieu of the wireless carrier system  60 . 
     The communications network  62  may be a conventional land-based telecommunications network connected to one or more landline telephones and connects the wireless carrier system  60  to the remote access center  78 . For example, the communications network  62  may include a public switched telephone network (PSTN) such as that used to provide hardwired telephony, packet-switched data communications, and the Internet infrastructure. One or more segments of the communications network  62  could be implemented through the use of a standard wired network, a fiber or other optical network, a cable network, power lines, other wireless networks such as wireless local area networks (WLANs), or networks providing broadband wireless access (BWA), or any combination thereof. Furthermore, the remote access center  78  need not be connected via land network, but could include wireless telephony equipment so that it can communicate directly with a wireless network, such as a wireless carrier system. 
     The remote access center  78  is designed to provide the wireless communications system  28  of the vehicle  12  with a number of different system functions and, according to the exemplary embodiment shown in  FIG. 1 , generally includes one or more switches, servers, databases, live advisors, as well as an automated voice response system (VRS). These various remote access center components are preferably coupled to one another via a wired or wireless local area network. The switch, which can be a private branch exchange (PBX) switch, routes incoming signals so that voice transmissions are usually sent to either the live adviser by regular phone or to the automated voice response system using VoIP. The live advisor phone can also use VoIP as indicated by the broken line in  FIG. 1 . VoIP and other data communication through the switch is implemented via a modem (not shown) connected between the switch and the network. Data transmissions are passed via the modem to the server and/or the database. The database can store account information such as subscriber authentication information, vehicle identifiers, profile records, behavioral patterns, and other pertinent subscriber information. Data transmissions may also be conducted by wireless systems, such as 802.11x, GPRS, and the like. Although the illustrated embodiment has been described as it would be used in conjunction with a manned remote access center using the live advisor, it will be appreciated that the remote access center can instead utilize the VRS as an automated advisor, or a combination of the VRS and the live advisor can be used. 
     The disclosed methods can be used with any number of different systems and is not specifically limited to the operating environment shown here. The architecture, construction, setup, and operation of the system  100  and its individual components is generally known. Other systems not shown here could employ the disclosed methods as well. 
     Turning now to  FIG. 2 , a block diagram illustrating an exemplary implementation of a system for high definition map based vehicle control for assisted driving  200  is shown. The exemplary system  200  is operative to generate control data for vehicular assisted driving systems. The exemplary system  200  is operative to use reinforcement learning (RL) to generate a control algorithm for autonomous vehicle control by applying reinforcement learning (RL) methods to train a control algorithm that can autonomously learn how to perform lane change actions using a reduced amount of input data. Unlike rule-based algorithms, RL algorithms can learn to deal with unpredictable and changeable situations based on errors and trials during the training process. Unlike supervised learning, RL does not need a large amount of labeled data to train a data-based model. The exemplary system  200  is operative to develop a flexible mapping function from environment states to agent actions according to recorded experience, similar to how human drivers learn to drive. 
     Previously, RL methods encounter difficulty with high-dimensional state space problems such as autonomous vehicle decision-making in complicated urban environments. To overcome this problem, previous RL algorithms required a long training period to get an acceptable result. For difficult problems with high-dimensional state spaces, these algorithms could not guarantee convergence of the loss function and satisfactory performance during a limited training period. 
     The current system addresses these problems by receiving data indicative of a radar data collected by a radar sensor  240  by an assisted driving vehicle. The radar data may be collected and stored by an assisted driving or autonomous driving vehicle. Alternatively, the radar data may be simulated by a simulation algorithm or manually generated. In this exemplary embodiment, the radar data may be stored in a format similar to data received from a radar sensor  240 . In addition, in this exemplary embodiment illustrating a system operative to perform a simulation of a lane change operation, the radar sensor  240  may be a memory for storing the radar data. The radar data may then be coupled to a longitudinal processor  210 . 
     The longitudinal processor  210  is operative to receive the radar data indicative of radar data collected by a radar sensor  240  and to simulate an adaptive cruise control operation. For example, the radar data may indicate that a lead vehicle is located 50 meters ahead of the host vehicle in the same driving lane. The lead vehicle may be traveling at a simulated rate of 55 miles per hour and the host vehicle may be traveling at a simulated rate of 60 miles per hour. The adaptive cruise control simulation may have an exemplary following distance set at 30 meters. After a certain elapsed time, the longitudinal processor may determine that a reduction in speed or a lane change is required when the following distance approaches 30 meters. At this point, the longitudinal processor  210  may generate a lane change request control signal and couple this lane change request control signal to a latitudinal processor  220  requesting a lane change. 
     The latitudinal processor  220  is operative to receive the lane change request from the longitudinal processor  210 . The latitudinal processor  220  is then operative to request data indicative of simulated vehicles traveling in a lane to the left of the host vehicle. This data may be supplied by the radar sensor  240 , a simulated camera sensor  245  or other source of simulated data. The latitudinal processor  220  is then operative to determine if there is sufficient room in the adjacent target lane for the host vehicle to safely execute a lane change operation. For example, the latitudinal processor  220  may determine if there is a simulated vehicle is within 30 meters behind or ahead of the host vehicle in the adjacent target lane, indicative of a safe area. In no vehicle is detected within the safe area, the latitudinal processor  220  may couple a signal to a lane change processor  230  indicating a request for a lane change to the left of the host vehicle. If the latitudinal processor  220  determines the presence of a vehicle within the safe area of the left lane, the latitudinal processor  220  then similarly checks the right lane. If no vehicle is detected within the safe area, the latitudinal processor  220  may couple a signal to a lane change processor  230  indicating a request for a lane change to the right of the host vehicle. If the latitudinal processor  220  determines the presence of a vehicle within the safe area of the right lane, the latitudinal processor  220  then may couple a control signal back to the longitudinal processor  210  indicating that no lane change is possible. The longitudinal processor  210  may then be operative to reduce the speed of the host vehicle to maintain the following distance from the lead vehicle by generating a control signal for coupling to a throttle controller  255 . The longitudinal processor  210  may further be operative to execute a control signal to couple to a braking controller  260  in order to reduce the speed of the host vehicle. 
     The lane change processor  230  is operative to receive map data from a map data source  250 , such as a memory or a network, and to execute a lane change operation in response to the request from the latitudinal processor  220 . For example, the lane change processor  230  may be operative to determine an optimal lane change route between a closest middle point in the current lane and a target point on the adjacent target lane and to generate a control signal coupled to a vehicle steering controller  270  such that the lane change is executed in a desired time duration. For example, if it is desirable that a lane change be executed in three seconds, the lane change processor will determine a lane change route that is three second long. Then the target point is approached, the lane change processor  230  is then operative to couple a control signal back to the latitudinal processor  220  which is then operative to center the host vehicle on the new lane. Once the host vehicle is centered on the new lane, the latitudinal processor  220  may then generate a control signal to indicate to the longitudinal processor  210  that the host vehicle is centered in the new lane at that a reduction is speed may not be required in view of the lead vehicle. 
     The system further comprises a memory  235  for storing an episode generated in response to a combination of at least two of the radar data, the lane change request, the available lane determination and the optimal lane change route. The episode is then used to control an assisted driving vehicle. 
     Turning now to  FIG. 3 , a flow chart illustrating an exemplary implementation of a method for high definition map based vehicle control system training for assisted driving  300  is shown. The method is operative to perform a training iteration for a reinforced learning algorithm for generating a control system for an assisted driving vehicle. In this exemplary method, the host vehicle, lead vehicle and proximate vehicles may be computer generated in order to train the reinforced learning algorithm. The method is first operative to start the training iteration  301 . The method then retrieves the data representative of radar signal  305  at a first time step and simulates a longitudinal assisted driving action  310 , determining a distance to a lead vehicle in the lane in front of the host vehicle. The method is operative to calculate a distance to the lead vehicle and a speed or velocity of the lead vehicle. The method the determines if a lane change is to be made in response to the velocity and distance to the lead vehicle. If the distance is less than a predetermined following distance, or the host vehicle is traveling faster than the lead vehicle and the distance is nearing the following distance, the method is then operative to determine that a lane change is desired  325 . 
     Simultaneous with the longitudinal assisted driving action  310 , the method is operative to retrieve data  315  to be used perform a latitudinal assisted driving action  320 . This data may include image data, radar data, or the like, of the areas proximate to the host vehicle. The latitudinal assisted driving action  320  may include a lane keep action wherein the latitudinal assisted driving action  320  is operative to keep the host vehicle centered in the current lane. The latitudinal assisted driving action  320  may perform this action in response to a left lane marker, a right lane marker, both lane markers, map data, GPS information or the like. The method is then operative to determine if the desire for a lane change  325  has been determined by the longitudinal assisted driving action. If no lane change has been desired  325  the method is then operative to return to the start of the method  301 . 
     If a lane change is desired  325 , the method is operative to first determine if there is an available space in the lane to the left of the current lane  330 . In this exemplary embodiment, a lane may be determined to be clear and safe for a lane change action if there are no vehicles within 30 meters ahead of or behind the host vehicle. The 30 meter safe distance may be determines in response to engineering design specifications and is not limiting to the presently disclosed method and systems. The safe distance may be any distance and may vary based on host vehicle speed, adjacent vehicle speeds, traffic density, geographical location or the like. If the left lane is determined to be clear  330 , a lane change is requested from a lane change algorithm. If the left lane is not clear, the method is then operative to check if there is an available space in the lane to the right of the current lane  340 . Similarly as described with respect to the left lane, if the lane is clear a lane change is requested from a lane change algorithm. If the right lane is not clear, the method is operative to generate a request for reduced speed which is coupled to the longitudinal assisted driving action  310 . The method is then operative to return to the start of the method  301  with the longitudinal driving action speed set to the reduced speed in response to the speed of the lead vehicle and the predetermined following distance. 
     If it is determined that a target lane is clear, either the left or right lane, the method is then operative to engage a lane change algorithm for performing the lane change  350 . The lane change algorithm is then operative to request or retrieve map data  355 . In addition, the lane change algorithm may determine a GPS location of the host vehicle. The map data may indicate the lane locations. The lane change algorithm is then operative to determine an optimal lane change path  360  in response to the closest middle point on the current lane, a target point on the center of the desired lane, and the target time for making the lane change. The target time may be determined in response to the speed of the host vehicle, proximate vehicles, geographical location, etc. In this exemplary embodiment, the target time for the lane change may be three seconds. Once the optimal lane change path is determined, a control signal indicative of the lane change path is coupled to a simulated vehicle controller  365  for simulating the lane change. The results of the lane change action are stored to an assisted driving control algorithm, and a score determined in response to a reward policy for the action. The method is then operative to return to the start of the method  301 . The assisted driving control algorithm may then be coupled to an assisted driving control algorithm in a vehicle for use in controlling the vehicle in response to an actual driving environment. 
     Turning now to  FIG. 4 , a block diagram illustrating an exemplary implementation of a system for high definition map based vehicle control for assisted driving  400  in a vehicle is shown. The system  400  is implemented in a host vehicle, and includes an antenna  435 , a radar  440 , a camera  450 , a memory  455 , a longitudinal controller  410 , a latitudinal controller  420 , a lane change controller  430 , a vehicle controller  460 , a steering mechanism  490 , a throttle mechanism  480  and a braking mechanism  470 . 
     In this exemplary embodiment, the longitudinal controller  410  is operative to perform the functions associated with adaptive cruise control for a vehicle. The longitudinal controller  410  is first operative to receive a user input indicative of a desired speed of the host vehicle. For example, the user input may be indicative of a desired speed of seventy miles per hour. The longitudinal controller  410  is further operative to receive data from the radar  240  indicative of a distance to a lead vehicle driving in the lane ahead of the host vehicle. Over time, the longitudinal controller  410  calculates the speed of the lead vehicle and compares the lead vehicle speed to the speed of the host vehicle. The longitudinal controller  410  may determine as a result of the comparison that the following distance will be less than a threshold distance and therefore a lane change or a reduction of speed for the host vehicle is required. The longitudinal controller  410  may then request a lane change from the latitudinal controller  420 . 
     In response to a lane change request from the longitudinal controller  410 , the latitudinal controller  420  may first determine if the next leftmost lane is a valid lane change destination. In this exemplary embodiment, the latitudinal controller  420  is operative to receive data from the camera  450  facing the left lane and to determine if a proximate vehicle is within a safe lane change distance, such as 30 meters, of the host vehicle. If no proximate vehicle is within the safe lane change distance, the latitudinal controller  420  is operative to send a control signal to the lane change controller  430  requesting a lane change to the next leftmost lane. If a proximate vehicle is within the left lane, the latitudinal controller  420  repeats the operation with respect to the right lane. The latitudinal controller  420  is again operative to receive data from the camera  450  and to determine if a proximate vehicle is within a safe lane change distance in the next rightmost lane. If no proximate vehicle is within the safe lane change distance in the next rightmost lane, the latitudinal controller  420  sends a control signal to the lane change controller  430  requesting a lane change to the next rightmost lane. If a proximate vehicle is within the safe lane change distance in the next rightmost lane, the latitudinal controller  420  is operative to send a control signal back to the longitudinal controller  410  indicating that a lane change is not possible. 
     If the longitudinal controller  410  receives a control signal from the latitudinal controller  420  that a lane change is not possible, the latitudinal controller  420  sends a control signal to the vehicle controller  460  to request a reduction in speed of the host vehicle to match that of the lead vehicle. The vehicle controller  460  is then operative to control the throttle mechanism  480  and/or the braking mechanism  470  in order to reduce the speed of the host vehicle. When the longitudinal controller  410  determines that the host vehicle speed matches that of the lead vehicle and that the desired following distance is maintained, the longitudinal controller  410  generates another control signal to couple to the vehicle controller  460  to request that the current speed be maintained. 
     The lane change controller  430  is operative to control a lane change action in response to a request for a lane change, global positioning system (GPS) data and high definition map data. If the lane change controller  430  receives a request for a lane change, the lane change, the lane change controller  430  retrieves the high definition map data from either the memory  455  or via wireless network through the antenna  435 . T lane change controller  430  retrieves the GPS data via the antenna  435  or the memory  455 . The lane change controller  430  first determines the optimal lane change time based on at least one of user input, vehicle speed, and geographical location. For example, the lane change controller may determine that the optimal lane change time is three seconds. The lane change controller  430  then determines an optimal path between the closest middle point on the current lane and a target point on the target lane that is the optimal lane change time away. lane change controller  430  then generates a control signal indicative of the optimal path to the vehicle controller  460 . The vehicle controller  460  then generates a control signal to couple to the steering mechanism  490  in order to perform the lane change action. The lane change controller  430  is then operative to monitor the location of the host vehicle within the lanes. Once the host vehicle reaches target point, the lane change controller  430  then generates a first control signal to couple to the latitudinal controller  420  to request that latitudinal control be resumed by the latitudinal controller  420 . The lane change controller  430  may further generate a second control signal to couple to the vehicle controller that the lane change operation has been completed and lateral control has been resumed by the latitudinal controller  420 . 
     Turning now to  FIG. 5 , a flow chart illustrating an exemplary implementation of a system for high definition map based vehicle control for assisted driving  500  in a host vehicle is shown. The method is first operative to perform the longitudinal control  510  in the adaptive cruise control. The method then checks if a lane change is desired  525  in response to a determined host vehicle speed and a following distance to a lead vehicle. If no lane change is desired, the method is then operative to perform a lane keep algorithm  520  according to the adaptive cruise control to maintain host vehicle centering within the current lane. The method then returns to performing the longitudinal control  510 . 
     If a lane change is desired  525 , the method is then operative to determine if a lane is available to either the left or the right of the host vehicle. Lane availability is determined in response to location of proximate vehicles within the adjacent lanes. If no lane is available  530 , the speed to the host vehicle is reduced in order to maintain a desired following distance with respect to the lead vehicle. If a lane is available  530 , the method is then operative to execute the lane change action  550  to the available adjacent lane. When the host vehicle arrives in the center of the available adjacent lane, the method then returns to performing the longitudinal control  510 . 
     While at least one exemplary embodiment has been presented in the foregoing detailed description, it should be appreciated that a vast number of variations exist. It should also be appreciated that the exemplary embodiment or exemplary embodiments are only examples, and are not intended to limit the scope, applicability, or configuration of the disclosure in any way. Rather, the foregoing detailed description will provide those skilled in the art with a convenient road map for implementing the exemplary embodiment or exemplary embodiments. It should be understood that various changes can be made in the function and arrangement of elements without departing from the scope of the disclosure as set forth in the appended claims and the legal equivalents thereof.