Full speed range adaptive cruise control system for determining adaptive launch time of a vehicle

Abstract

A full-speed range adaptive cruise control system for stopping a vehicle at an intersection includes one or more controllers that execute instructions to receive positioning data and situational data related to the vehicle. The one or more controllers determine, based on the positioning data and the situational data, that the vehicle is approaching and will stop at the intersection, wherein the vehicle is part of a platoon that includes one or more surrounding vehicles. In response to determining that the vehicle has stopped, the controller determines a position of the vehicle within the platoon and a total length of the platoon. The controller calculates an adaptive start time based on at least the position of the vehicle within the platoon, the total length of the platoon, the situational data, and a timing delay associated with the platoon.

Description

Technical Field

[0001] This disclosure relates to a full-speed adaptive cruise control system for determining the adaptive start time of a vehicle stopped at an intersection. The adaptive start time is further customized based on user preferences, environmental factors, and dynamic input factors. Background Technology

[0002] Many vehicles include various driver assistance systems that support the driver in different ways. For example, adaptive cruise control (ACC) systems can alleviate the driver's burden from conventional longitudinal vehicle control by ensuring an acceptable distance between the lead vehicle and the vehicle in front. Adaptive cruise control systems are either full-speed adaptive cruise control (FSRA) or speed-limited adaptive cruise control (LSRA). Full-speed adaptive cruise control systems can bring the vehicle to a complete stop.

[0003] While driver assistance systems potentially enhance driver comfort and satisfaction, their success depends not only on their reliability but also on driver acceptance. For example, a full-speed adaptive cruise control system can resume drive from a stop based on the movement of vehicles immediately preceding it and those ahead of it at a traffic light, and can be further input from the driver or user. Therefore, if the vehicle immediately preceding it is part of a queue at a traffic light, a timing delay can be employed that is associated with the forward movement of the vehicle resuming drive from a stop. This timing delay is established because once the traffic light changes from red to green, the first vehicle in the queue may take approximately two to three seconds to resume drive, and each vehicle after the first may also take approximately one to two seconds before resuming drive. However, the delay decreases after a certain point in the queue (typically the fifth or sixth vehicle). If the vehicle is equipped with an autonomous drive system, a delayed start from a stop can generate dissatisfaction or even cause the driver to disregard autonomous control. Furthermore, if the vehicle resumes drive too early, it can cause driver anxiety. Similarly, if the vehicle is manually driven and the notification instructing the driver to reactivate the system is generated either too early or too late, it can confuse the driver.

[0004] Therefore, while current full-speed adaptive cruise control systems achieve their intended purpose, there is a need in the art for an improved method to determine when to start the vehicle from a stop. Summary of the Invention

[0005] According to several aspects, a full-speed adaptive cruise control system for a vehicle stopped at an intersection is disclosed. The full-speed adaptive cruise control system includes one or more controllers that execute instructions to receive vehicle-related positioning data and scenario data. The one or more controllers determine, based on the positioning data and scenario data, that the vehicle is approaching the intersection and will stop at the intersection, wherein the vehicle is part of a queue comprising one or more surrounding vehicles. In response to determining that the vehicle has stopped, the one or more controllers determine the vehicle's position within the queue and the total length of the queue. The one or more controllers calculate an adaptive start time based on at least the vehicle's position within the queue, the total length of the queue, the scenario data, and a timing delay associated with the queue, wherein the adaptive start time indicates when the vehicle resumes actuation after stopping at the intersection.

[0006] In another respect, timing delay refers to the amount of time measured from the following times and points in time: the time when the traffic signal at the intersection changes from red to green, and the time when the vehicle resumes driving.

[0007] On the other hand, timing delay refers to the amount of time measured from the following times and points in time: the time when the lead vehicle in the queue resumes driving, and the point in time when the vehicle resumes driving.

[0008] On the other hand, one or more controllers execute instructions to estimate the position of vehicles in the queue and the total length of the queue based on historical vehicle data and near real-time data related to vehicle traffic within the intersection.

[0009] In one aspect, historical vehicle data includes information related to vehicle location, travel position, and speed relative to vehicle traffic within the intersection, while near real-time data includes on-site traffic information representing the current trajectory of vehicle traffic within the intersection.

[0010] On the other hand, one or more controllers execute instructions to customize the value of the adaptive startup time based on user preferences, where customizing the adaptive startup time involves either increasing or decreasing the value of the adaptive startup time.

[0011] In another aspect, one or more controllers execute instructions to determine user preferences based on physical responses observed by one or more vehicle systems, which are part of the vehicle and are executed by the user, when the vehicle resumes driving from a stop, wherein the physical responses represent the user's mental state.

[0012] In one aspect, one or more controllers execute instructions to customize the value of the adaptive startup time based on one or more environmental factors, wherein customizing the adaptive startup time involves either increasing or decreasing the value of the adaptive startup time.

[0013] On the other hand, one or more environmental factors refer to one or more of the following: road conditions, road geometry, lighting conditions, and pedestrian access within intersections.

[0014] On the other hand, one or more controllers execute instructions to customize the value of the adaptive startup time based on dynamic input factors, where customizing the adaptive startup time involves either increasing or decreasing the value of the adaptive startup time.

[0015] In one aspect, dynamic input factors represent events being performed by one or more surrounding vehicles in the queue, where the event either increases or decreases the adaptive start time.

[0016] On the other hand, adaptive start time refers to the automatic start time when a vehicle is pushed from a stop at an intersection.

[0017] On another front, the full-speed adaptive cruise control system includes an indicator that communicates electronically with one or more controllers, and one or more of the controllers execute instructions to instruct the indicator to generate a notification instructing the driver of the vehicle to reactivate the full-speed adaptive cruise control system.

[0018] In one aspect, one or more controllers execute instructions to calculate an adaptive stopping time, where the adaptive stopping time represents when a vehicle stops at an intersection.

[0019] On the other hand, the adaptive stopping time is determined based on at least the position of the vehicle within the queue and the total length of the queue.

[0020] In one aspect, one or more controllers execute instructions to further determine the adaptive stop time based on scenario data and timing delays associated with the queue.

[0021] On the other hand, a method is disclosed for determining the adaptive start time of a vehicle stopped at an intersection using a full-speed adaptive cruise control system. The method includes receiving vehicle-related positioning data and scenario data by one or more controllers. The method includes determining, based on the positioning data and scenario data, that the vehicle is approaching the intersection and will stop at the intersection, wherein the vehicle is part of a queue comprising one or more surrounding vehicles. In response to determining that the vehicle has stopped, the method includes determining the vehicle's position within the queue and the total length of the queue. Finally, the method includes calculating, by one or more controllers, an adaptive start time based on at least the vehicle's position within the queue, the total length of the queue, the scenario data, and a timing delay associated with the queue, wherein the adaptive start time represents when the vehicle resumes drive after stopping at the intersection.

[0022] On the other hand, the method customizes the adaptive startup time based on at least one of the following: user preferences, environmental factors, and dynamic input factors.

[0023] In another aspect, the method includes customizing the adaptive startup time by either increasing or decreasing the value of the adaptive startup time.

[0024] On the other hand, the method includes calculating an adaptive stopping time, where the adaptive stopping time represents when the vehicle stops at the intersection.

[0025] Furthermore, the present invention relates to the following technical solutions.

[0026] Option 1. A full-speed adaptive cruise control system for vehicles stopped at an intersection, the full-speed adaptive cruise control system comprising:

[0027] One or more controllers, the controllers executing instructions to:

[0028] Receive positioning data and context data related to the vehicle;

[0029] Based on location data and context data, it is determined that the vehicle is approaching an intersection and will stop at the intersection, wherein the vehicle is part of a queue that includes one or more surrounding vehicles;

[0030] In response to determining that the vehicle has stopped, the position of the vehicle within the queue and the total length of the queue are determined; and

[0031] An adaptive start time is calculated based on at least the position of the vehicle within the queue, the total length of the queue, the scenario data, and a timing delay associated with the queue, wherein the adaptive start time indicates when the vehicle resumes drive after stopping at the intersection.

[0032] Option 2. The full-speed adaptive cruise control system according to Option 1, wherein the timing delay represents a time quantity measured from the following times and points in time: the time when the traffic signal at the intersection switches from red to green, and the time when the vehicle resumes driving.

[0033] Option 3. The full-speed adaptive cruise control system according to Option 1, wherein the timing delay represents a time quantity measured from the following times and points in time: the time when the lead vehicle in the queuing resumes driving, and the time when the vehicle resumes driving.

[0034] Option 4. The full-speed adaptive cruise control system according to Option 1, wherein the one or more controllers execute instructions to:

[0035] The position of the vehicle in the queue and the total length of the queue are estimated based on historical vehicle data and near real-time data related to vehicle traffic within the intersection.

[0036] Option 5. The full-speed adaptive cruise control system according to Option 4, wherein the historical vehicle data includes information related to vehicle position, travel position and speed relative to the vehicle traffic within the intersection, and the near real-time data includes on-site traffic information representing the current trajectory of the vehicle traffic within the intersection.

[0037] Option 6. The full-speed adaptive cruise control system according to Option 1, wherein the one or more controllers execute instructions to:

[0038] The value of the adaptive startup time is customized based on user preferences, wherein customizing the adaptive startup time involves either increasing or decreasing the value of the adaptive startup time.

[0039] Option 7. The full-speed adaptive cruise control system according to Option 6, wherein the one or more controllers execute instructions to:

[0040] When the vehicle resumes driving from a stop, the user preference is determined based on physical responses observed by one or more vehicle systems, which are part of the vehicle and are executed by the user, wherein the physical responses represent the user's mental state.

[0041] Option 8. The full-speed adaptive cruise control system according to Option 1, wherein the one or more controllers execute instructions to:

[0042] The value of the adaptive startup time is customized based on one or more environmental factors, wherein customizing the adaptive startup time involves either increasing or decreasing the value of the adaptive startup time.

[0043] Option 9. The full-speed adaptive cruise control system according to Option 8, wherein the one or more environmental factors represent one or more of the following: road conditions, road geometry, lighting conditions, and pedestrian traffic within the intersection.

[0044] Option 10. The full-speed adaptive cruise control system according to Option 1, wherein the one or more controllers execute instructions to:

[0045] The value of the adaptive startup time is customized based on dynamic input factors, wherein customizing the adaptive startup time involves either increasing or decreasing the value of the adaptive startup time.

[0046] Option 11. The full-speed adaptive cruise control system according to Option 10, wherein the dynamic input factor represents an event being performed by one or more surrounding vehicles in the queue, wherein the event either increases or decreases the adaptive start time.

[0047] Option 12. The full-speed adaptive cruise control system according to Option 1, wherein the adaptive start time represents the automatic start time when the vehicle is pushed from a stop at the intersection.

[0048] Option 13. The full-speed adaptive cruise control system according to Option 1, wherein the full-speed adaptive cruise control system includes an indicator that electronically communicates with the one or more controllers, and wherein the one or more controllers execute instructions to:

[0049] The indicator generates a notification instructing the driver of the vehicle to reactivate the full-speed adaptive cruise control system.

[0050] Option 14. The full-speed adaptive cruise control system according to Option 1, wherein the one or more controllers execute instructions to:

[0051] Calculate the adaptive stopping time, where the adaptive stopping time indicates when the vehicle stops at the intersection.

[0052] Option 15. The full-speed adaptive cruise control system according to Option 14, wherein the adaptive stop time is determined based on at least the position of the vehicle within the queue and the total length of the queue.

[0053] Option 16. The full-speed adaptive cruise control system according to Option 14, wherein one or more controllers execute instructions to further determine the adaptive stop time based on the scenario data and the timing delay associated with the queue.

[0054] Option 17. A method for determining the adaptive start time of a vehicle stopped at an intersection via a full-speed adaptive cruise control system, the method comprising:

[0055] One or more controllers receive positioning data and context data related to the vehicle;

[0056] Based on location data and context data, it is determined that the vehicle is approaching an intersection and will stop at the intersection, wherein the vehicle is part of a queue that includes one or more surrounding vehicles;

[0057] In response to determining that the vehicle has stopped, the position of the vehicle within the queue and the total length of the queue are determined; and

[0058] The adaptive start time is calculated by the one or more controllers based on at least the position of the vehicle within the queue, the total length of the queue, the scenario data, and the timing delay associated with the queue, wherein the adaptive start time indicates when the vehicle resumes drive after stopping at the intersection.

[0059] Option 18. The method according to Option 17, wherein the method comprises:

[0060] The adaptive startup time is customized based on at least one of the following: user preferences, environmental factors, and dynamic input factors.

[0061] Option 19. The method according to Option 18, wherein the method comprises:

[0062] The adaptive startup time is customized by either increasing or decreasing its value.

[0063] Option 20. The method according to Option 17, wherein the method comprises:

[0064] Calculate the adaptive stopping time, where the adaptive stopping time indicates when the vehicle stops at the intersection.

[0065] Further areas of application will become apparent from the description provided herein. It should be understood that this description and specific examples are intended for illustrative purposes only and are not intended to limit the scope of this disclosure. Attached Figure Description

[0066] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of this disclosure in any way. Wherein:

[0067] Figure 1 This is a schematic diagram of a vehicle including the disclosed full-speed adaptive cruise control system according to an exemplary embodiment;

[0068] Figure 2 It stops at the intersection according to the exemplary embodiment. Figure 1 A schematic diagram of the vehicle shown; and

[0069] Figure 3 This is a flowchart illustrating a method for calculating the adaptive start-up time of a vehicle, according to an exemplary embodiment. Detailed Implementation

[0070] The following description is exemplary in nature and is not intended to limit this disclosure, application, or purpose.

[0071] refer to Figure 1An exemplary full-speed adaptive cruise control system 12 for a vehicle 10 is shown. The vehicle 10 can be any type of vehicle, such as, but not limited to, a sedan, truck, SUV, van, or motorhome. The full-speed adaptive cruise control system 12 includes one or more controllers 20 that communicate electronically with multiple vehicle sensors 22, one or more vehicle systems 24, and one or more external vehicle networks 26 that communicate wirelessly with the one or more controllers 20. Figure 1 In the example shown, the multiple vehicle sensors 22 include one or more cameras 30, one or more radar sensors 32, an inertial measurement unit (IMU) 34, a global positioning system (GPS) 36, and a lidar 38; however, it should be appreciated that additional sensors may also be used. The external vehicle network 26 may include, but is not limited to, cellular networks, dedicated short-range communication (DSRC) networks, vehicle-to-everything (V2X) infrastructure networks, and cellular V2X (C-V2X). It should be appreciated that while this disclosure is intended for a full-speed adaptive cruise control system 12, any other type of system performing automatic longitudinal control, including the ability to bring the vehicle to a complete stop and automatically resume traction across the entire speed range, may also be used.

[0072] Figure 2 This is an illustration of an exemplary four-way intersection 50, in which vehicle 10 is stopped at intersection 50. Figure 2 The diagram also shows a queue 52 of vehicles 54 surrounding the intersection 50. (See diagram 52 for details.) Figure 2 As seen, vehicle 10 is part of a queue 52 that includes one or more surrounding vehicles 54. (Reference) Figure 1 and Figure 2 As explained below, the full-speed adaptive cruise control system 12 determines the adaptive start time for vehicle 10. The adaptive start time indicates when vehicle 10 resumes drive after coming to a stop at intersection 50. Specifically, the full-speed adaptive cruise control system 12 includes an automatic recovery mode, where controller 20 instructs vehicle 10 to accelerate from a stop to a set speed. The adaptive start time is determined based on at least the position of vehicle 10 within queue 52, the total length of queue 52, scenario data, and timing delays associated with queue 52. The total length of queue 52 is represented by the number of vehicles. For example, in... Figure 2In the illustrated embodiment, vehicle 10 is at the end of the queue, and the total length of queue 52 is four vehicles. In this embodiment, the adaptive start time is further based on historical vehicle data and near-real-time data relating to traffic within intersection 50. In this embodiment, the full-speed adaptive cruise control system 12 customizes the value of the adaptive start time based on one or more user factors, one or more environmental factors, and one or more dynamic input factors. Also explained below, in one embodiment, the full-speed adaptive cruise control system 12 further determines the adaptive stop time based on at least the position of vehicle 10 within queue 52 and the total length of queue 52.

[0073] In such Figure 2 In the illustrated embodiment, the queue 52 of surrounding vehicles 54 is shown stopped at traffic signal 56; however, it should be understood that surrounding vehicles 54 could also stop at traffic signs. Although Figure 2 Four-way intersection 50 is shown, but it should be understood that intersection 50 can be any other type of traffic stop where vehicles come to a complete stop at traffic lights or traffic signs (such as, for example, three-way stop or two-way stop).

[0074] In one embodiment, vehicle 10 includes an automatic drive feature that allows vehicle 10 to automatically start from a stop at intersection 50. Therefore, the adaptive start time refers to the automatic start time when vehicle 10 is propelled from a stop at intersection 50 by the full-speed adaptive cruise control system 12. In another embodiment, vehicle 10 can be manually started by the driver from a stop at intersection 50. Specifically, in one embodiment, the full-speed adaptive cruise control system 12 includes an indicator 60 that communicates electronically with controller 20. In this embodiment, controller 20 instructs the indicator 60 to generate a notification instructing the driver of vehicle 10 to reactivate the full-speed adaptive cruise control system 12. In one embodiment, the notification may be a light instructing the driver to lightly depress the accelerator to reactivate the full-speed adaptive cruise control system 12; however, it should be appreciated that the indicator 60 may also include other means of generating the notification. For example, in another embodiment, the indicator 60 may be a speaker generating an audio notification or a motor generating tactile vibrations on the accelerator pedal or seat.

[0075] One or more vehicle systems 24 may include systems such as, but not limited to, automatic drive systems, driver monitoring systems (DMS), braking systems, and engine start-stop systems. The engine start-stop system automatically shuts off and restarts the internal combustion engine of vehicle 10 to save fuel. The engine start-up time and engine stop-down time of the engine start-stop system are functions of adaptive start-up time and adaptive stop-down time. Specifically, for example, if the adaptive start-up time is relatively short in duration, the engine start-stop system may not stop the engine in some cases. It should be appreciated that adjusting the engine start-up time and stop-down time for the engine start-stop system based on the adaptive start-up time and adaptive stop-down time can enhance fuel economy.

[0076] As mentioned above, the external vehicle network 26 may include cellular networks, DSRC networks, and V2X networks. The V2X network collects data such as, but not limited to, signal phase and timing (SPaT) data, including the current state of traffic signals, intersection map data (MAP) representing the road geometry of the intersection, historical vehicle data, near-real-time data, and pedestrian information. Historical vehicle data pertains to traffic within intersection 50 and may be stored on one or more databases 62 located remotely from vehicle 10. It should be understood that historical vehicle data includes information collected from multiple vehicles already operating within a specific intersection. Historical vehicle data includes historical trajectory data, which includes, but is not limited to, information relating to various factors such as, but not limited to, vehicle position, travel position, and speed of vehicle traffic within intersection 50. In one embodiment, historical vehicle data may further represent timing-based historical trajectory data, such as trajectory data based on the time of day or the number of days in a week. Near-real-time data includes on-site traffic information representing the current trajectory of vehicle traffic within intersection 50 and may be received by controller 20 from the external vehicle network 26, such as from cellular networks or V2X.

[0077] Continue to refer to Figure 1 and Figure 2 The controller 20 receives location data and situational data related to the vehicle 10 from multiple vehicle sensors 22, one or more vehicle systems 24, and an external vehicle network 26. The location data represents the vehicle's position, and the situational data includes information providing the controller 20 with situational awareness of the surrounding environment and includes information such as, but not limited to, SPAT data, MAP data, data related to driver attention from the DMS, and object detection data. The controller 20 monitors the location data and situational data and determines that the vehicle 10 is approaching and will stop at intersection 50. Figure 2As seen, vehicle 10 is part of queue 52 located at intersection 50. In response to determining that vehicle 10 has stopped, controller 20 determines the position of vehicle 10 within queue 52 and the total length of queue 52.

[0078] In a non-limiting embodiment, the total length of queue 52 is included as part of network messages (such as V2X messages) received by controller 20. Therefore, controller 20 determines the total length of queue 52 based on V2X messages. Alternatively, in another approach, controller 20 estimates the total length of queue 52 based on the road geometry at intersection 50, where the road geometry of intersection 50 includes information such as, but not limited to, stop bar distance, the number of lanes 68 at the intersection, and the permitted direction of travel for each of the lanes 68. It should be appreciated that if controller 20 determines the total length of queue 52 based on road geometry, the total length of queue 52 does not include any surrounding vehicles 54 located behind vehicle 10. In one embodiment, controller 20 uses one or more lookup tables to estimate the position of vehicle 10 within queue 52 based on the total length of queue 52. This lookup table may provide an estimate of the number of surrounding vehicles 54 located in front of vehicle 10 based on the distance to the stop bar. In one embodiment, the lookup table may be updated based on historical vehicle data.

[0079] In one embodiment, controller 20 further estimates the position of vehicle 10 within queue 52 and the total length of queue 52 based on historical vehicle data and near real-time data related to traffic within intersection 50. This is because the distribution of surrounding vehicles 54 may vary based on historical factors such as, but not limited to, the location of intersection 50, time of day, and number of days in a week. For example, some intersections 50 near schools or office buildings may be more congested on weekdays than on weekends.

[0080] Continue to refer to Figure 1 and Figure 2The controller 20 then calculates an adaptive start time based on the vehicle 10's position within queue 52, the total length of queue 52, scenario data, and a timing delay associated with queue 52, where the adaptive start time indicates when vehicle 10 resumes drive after stopping at intersection 50. A timing delay associated with queue 52 is established when a surrounding vehicle 54 upstream of vehicle 10 in the queue resumes drive from a stop. The timing delay represents a time measureable from the time when traffic signal 56 changes from red to green, and when vehicle 10 resumes drive from a stop once the vehicle immediately preceding it in queue 52 moves forward. Alternatively, if a traffic sign is used instead of traffic signal 56, the timing delay represents a time measureable from the time when the leading surrounding vehicle 54 in queue 52 resumes drive, and when vehicle 10 resumes drive from a stop once the vehicle immediately preceding it in queue 52 moves forward.

[0081] In such Figure 2 In the example shown, once traffic signal 56 changes from red to green, the first surrounding vehicle 54 in queue 52 may take two to three seconds to resume driving. The two surrounding vehicles 54 following the first may also take an additional one to two seconds before resuming driving. Therefore, in this example, the timing delay is between approximately four seconds and approximately seven seconds.

[0082] In one embodiment, controller 20 determines the timing delay based on one or more lookup tables, wherein the timing delay is selected based on the position of vehicle 10 within queue 52. In one embodiment, controller 20 adds relatively small time increments to the timing delay. For example, an increment of approximately 0.05 seconds may be added to the timing delay. In one embodiment, controller 20 further determines the timing delay based on vehicle classification. In one embodiment, vehicle classification refers to weight class, where weight class can represent light vehicles, medium vehicles, or heavy vehicles. For example, heavy vehicles (such as urban rail transit buses) affect the timing delay of vehicle 10 within queue 52 in a different way than passenger cars because heavy vehicles take longer to resume drive from a stop and also occupy more space within lane 68.

[0083] In one embodiment, controller 20 also calculates an adaptive stopping time for vehicle 10. The adaptive stopping time indicates when vehicle 10 stops at intersection 50. The adaptive stopping time is determined based on at least the position of vehicle 10 within queue 52 and the total length of queue 52. In one embodiment, controller 20 further determines the adaptive stopping time based on the position of vehicle 10 within queue 52, the total length of queue 52, scenario data, and timing delays associated with queue 52.

[0084] The controller 20 further customizes the adaptive start time based on one or more of the following: user preferences, environmental factors, and dynamic input factors. It should be understood that customizing the adaptive start time involves either increasing or decreasing the value used for the adaptive start time. When vehicle 10 resumes drive from a stop at intersection 50, the controller 20 determines user preferences based on physical reactions observed by the vehicle system 24, which is executed by the user. Physical reactions represent the user's mental state. Some examples of physical reactions representing a user's mental state include, but are not limited to: the driver attempting to manually resume drive from a stop, the driver manually releasing vehicle 10 while resuming drive from a stop, and physical reactions performed by users of vehicle 10. The driver can manually release vehicle 10 by performing actions such as, for example, attempting to press the brake pedal to ignore the full-speed adaptive cruise control system 12. In this example, the driver's mental state is that vehicle 10 is resuming drive too quickly. Physical reactions performed by one or more users of vehicle 10 can be detected by in-cabin cameras, such as cameras included as part of the DMS. Some examples of physical reactions include facial expressions and various body movements. For example, if controller 20 determines that the driver always presses the brake pedal when vehicle 10 resumes drive, controller 20 customizes the adaptive start time based on user preference to resume drive at a later time. Therefore, controller 20 can increase the adaptive start time.

[0085] The controller 20 determines environmental factors based on wireless data received from the external vehicle network 26 and inputs from various vehicle sensors 22. Environmental factors represent one or more of the following: road conditions, road geometry, lighting conditions, and pedestrian access at intersection 50. Some examples of road conditions include, for instance, icy or wet road surfaces, which can increase adaptive start time. Some examples of road geometry include determining whether lane 68 is a turning lane, which also increases adaptive start time. Lighting conditions refer to daylight conditions, twilight or reduced lighting conditions, and nighttime conditions. For example, the controller can customize the adaptive start time by increasing the start time during nighttime conditions due to limited visibility.

[0086] Controller 20 determines dynamic input factors based on data received from one or more vehicle systems 24 and an external vehicle network 26, where dynamic inputs represent events performed by one or more surrounding vehicles 54 within queue 52, where such events either increase or decrease the adaptive start time. For example, controller 20 may receive data from external vehicle network 26 indicating that one of the surrounding vehicles 54 upstream of vehicle 10 in queue 52 is performing emergency braking or sudden braking. In this example, the event is emergency braking by one of the surrounding vehicles 54 upstream of queue 52, and controller 20 customizes the adaptive start time by increasing it. In another example, controller 20 receives data from external vehicle network 26 indicating that one or more surrounding vehicles 54 downstream of vehicle 10 in queue 52 are using their horns to signal vehicle 10 to resume drive. In this example, the event is surrounding vehicle 54 using its horn, and controller 20 customizes the adaptive start time by decreasing it.

[0087] In one embodiment, controller 20 customizes the adaptive startup time based on user preferences, environmental factors, and dynamic input factors, wherein Equation 1 is used to determine this customization:

[0088] Adaptive startup time + a I *f1 (user preferences) + b I *f2 (environmental factors) + c I *f3 (Dynamic Input Factors) Equation 1,

[0089] Where a I b I and c I The weighting coefficients are determined experimentally based on the calibration process, and f1, f2, and f3 represent the functions.

[0090] In another embodiment, controller 20 customizes the adaptive stop time based on one or more of the following: user preference, environmental factors, and dynamic input factors. Environmental factors may include road conditions that make stopping the vehicle challenging, such as icy or snowy conditions. Furthermore, dynamic input factors may include the cyclic timing of traffic light 56. For example, if controller 20 receives SPAT data indicating that traffic light 56 ​​is about to turn red, it increases the adaptive stop time; and if SPAT data indicates that traffic light 56 ​​is about to turn green, it decreases the adaptive stop time.

[0091] In one embodiment, controller 20 customizes the adaptive stopping time based on user preferences, environmental factors, and dynamic input factors, wherein Equation 2 is used to determine this customization:

[0092] Adaptive startup time + a S *f1 (user preferences) + b S *f2 (environmental factors) + c S *f3 (Dynamic Input Factors) Equation 2,

[0093] Where a S b S and c S The weighting coefficients are determined experimentally based on the calibration process, and f1, f2, and f3 represent the functions.

[0094] Figure 3 This is a flowchart illustrating a method 200 for determining adaptive startup time. (Typically, this is a reference...) Figures 1 to 3 Method 200 may begin at block 202. In block 202, controller 20 receives location and contextual data relating to vehicle 10 from multiple vehicle sensors 22, one or more vehicle systems 24, and an external vehicle network 26. Method 200 may then proceed to decision block 204.

[0095] In decision box 204, controller 20 monitors location data and scenario data, and continues doing so until it determines that vehicle 10 is approaching and about to stop at intersection 50. Method 200 can then proceed to box 206.

[0096] In box 206, controller 20 determines the position of vehicle 10 within queue 52 and the total length of queue 52. Method 200 can then proceed to box 208.

[0097] In block 208, controller 20 calculates an adaptive start time based on at least the vehicle's position within queue 52, the total length of queue 52, scenario data, and a timing delay associated with queue 52, where the adaptive start time indicates when vehicle 10 resumes drive after stopping at intersection 50. Method 200 can then proceed to block 210.

[0098] In block 210, controller 20 customizes the adaptive startup time based on at least one of the following: user preferences, environmental factors, and dynamic input factors described above. As mentioned above, in various embodiments, the adaptive startup time can be used to determine the engine start and stop times for the engine start-stop system. Method 200 can then terminate.

[0099] Referring generally to the accompanying drawings, the disclosed system provides various technical effects and benefits by offering a method for determining the adaptive start-up time of a vehicle. The disclosed adaptive start-up time is determined based on at least the vehicle's position within the queue, the total length of the queue, scenario data, and timing delays associated with the queue. In contrast, some currently available systems can only resume drive from a stop in response to the detection of a green traffic signal and that the vehicle ahead has moved forward, without considering the timing delays observed when the vehicle queue resumes drive. In embodiments, the adaptive start-up time can be further customized based on user preferences, environmental factors, and dynamic input factors. Finally, the adaptive start-up time and adaptive stop-down time can be used to determine the engine start-up and stop times for an engine start-stop system, thereby enhancing fuel economy.

[0100] A controller can refer to or be part of electronic circuitry, combinational logic circuitry, a field-programmable gate array (FPGA), a processor (shared, dedicated, or grouped) that executes code, or some or all of the above, such as in a system-on-a-chip. Additionally, the controller can be microprocessor-based (such as a computer) having at least one processor, memory (RAM and / or ROM), and associated input and output buses. The processor can operate under the control of an operating system residing in memory. The operating system can manage computer resources so that computer program code implemented as one or more computer software applications (such as applications residing in memory) can have instructions that are executed by the processor. In alternative embodiments, the processor can directly execute the application, in which case the operating system can be omitted.

[0101] The description in this disclosure is exemplary in nature only, and variations thereof that do not depart from the spirit and scope of this disclosure are intended to fall within its scope. Such variations should not be considered as departing from the spirit and scope of this disclosure.

Claims

1. A full-speed adaptive cruise control system for a vehicle stopped at an intersection, the full-speed adaptive cruise control system comprising: One or more controllers that communicate electronically with an engine start-stop system, wherein the controllers execute instructions to: Receive positioning data and context data related to the vehicle; Based on location data and context data, it is determined that the vehicle is approaching an intersection and will stop at the intersection, wherein the vehicle is part of a queue that includes one or more surrounding vehicles; In response to determining that the vehicle is approaching an intersection and is about to stop at the intersection, the position of the vehicle in the queue and the total length of the queue are determined; The adaptive start time is calculated based on at least the position of the vehicle within the queue, the total length of the queue, the scenario data, and the timing delay associated with the queue, wherein the adaptive start time indicates when the full-speed adaptive cruise control system commands the vehicle to resume drive after stopping at the intersection, and wherein the engine start time and engine stop time of the engine start-stop system are functions of the adaptive start time and adaptive stop time. as well as Based on the adaptive start time command, the full-speed adaptive cruise control system automatically starts the vehicle from a stop at the intersection.

2. The full-speed adaptive cruise control system according to claim 1, wherein the timing delay represents a time quantity measured from the following times and points in time: the time when the traffic signal at the intersection switches from red to green, and the time when the vehicle resumes driving.

3. The full-speed adaptive cruise control system according to claim 1, wherein the timing delay represents a time quantity measured from the following times and points in time: the time when the lead vehicle in the convoy resumes driving, and the time when the vehicle resumes driving.

4. The full-speed adaptive cruise control system according to claim 1, wherein the one or more controllers execute instructions to: The position of the vehicle in the queue and the total length of the queue are estimated based on historical vehicle data and near real-time data related to vehicle traffic within the intersection.

5. The full-speed adaptive cruise control system of claim 4, wherein the historical vehicle data includes information relating to vehicle position, travel position and speed relative to the vehicle traffic within the intersection, and the near real-time data includes on-site traffic information representing the current trajectory of the vehicle traffic within the intersection.

6. The full-speed adaptive cruise control system according to claim 1, wherein the one or more controllers execute instructions to: The value of the adaptive startup time is customized based on user preferences, wherein customizing the adaptive startup time involves either increasing or decreasing the value of the adaptive startup time.

7. The full-speed adaptive cruise control system according to claim 6, wherein the one or more controllers execute instructions to: When the vehicle resumes driving from a stop, the user preference is determined based on physical responses observed by one or more vehicle systems, which are part of the vehicle and are executed by the user, wherein the physical responses represent the user's mental state.

8. The full-speed adaptive cruise control system according to claim 1, wherein the one or more controllers execute instructions to: The value of the adaptive startup time is customized based on one or more environmental factors, wherein customizing the adaptive startup time involves either increasing or decreasing the value of the adaptive startup time.

9. The full-speed adaptive cruise control system of claim 8, wherein the one or more environmental factors represent one or more of the following: road conditions, road geometry, lighting conditions, and pedestrian traffic at the intersection.

10. The full-speed adaptive cruise control system of claim 1, wherein the one or more controllers execute instructions to: The value of the adaptive startup time is customized based on dynamic input factors, wherein customizing the adaptive startup time involves either increasing or decreasing the value of the adaptive startup time.

11. The full-speed adaptive cruise control system of claim 10, wherein the dynamic input factor represents an event being performed by one or more surrounding vehicles in the queue, wherein the event either increases or decreases the adaptive start time.

12. The full-speed adaptive cruise control system according to claim 1, wherein the adaptive start time represents the automatic start time when the vehicle is propelled from a stop at the intersection.

13. The full-speed adaptive cruise control system of claim 1, wherein the full-speed adaptive cruise control system includes an indicator that electronically communicates with the one or more controllers, and wherein the one or more controllers execute instructions to: The indicator generates a notification instructing the driver of the vehicle to reactivate the full-speed adaptive cruise control system.

14. The full-speed adaptive cruise control system according to claim 1, wherein the one or more controllers execute instructions to: Calculate the adaptive stopping time, where the adaptive stopping time indicates when the vehicle stops at the intersection.

15. The full-speed adaptive cruise control system of claim 14, wherein the adaptive stop time is determined based on the position of at least the vehicle within the queue and the total length of the queue.

16. The full-speed adaptive cruise control system of claim 14, wherein the one or more controllers execute instructions to further determine the adaptive stop time based on the scenario data and the timing delay associated with the queue.

17. A method for determining the adaptive start time of a vehicle stopped at an intersection via a full-speed adaptive cruise control system, the method comprising: One or more controllers receive positioning data and context data related to the vehicle; Based on location data and context data, it is determined that the vehicle is approaching an intersection and will stop at the intersection, wherein the vehicle is part of a queue that includes one or more surrounding vehicles; In response to determining that the vehicle is approaching an intersection and is about to stop at the intersection, the position of the vehicle in the queue and the total length of the queue are determined; The adaptive start time is calculated by the one or more controllers based on at least the position of the vehicle in the queue, the total length of the queue, the scenario data, and the timing delay associated with the queue, wherein the adaptive start time indicates when the full-speed adaptive cruise control system commands the vehicle to resume drive after stopping at the intersection, and wherein the engine start time and engine stop time of the engine start-stop system are functions of the adaptive start time and adaptive stop time. as well as The full-speed adaptive cruise control system is commanded by one or more controllers, based on the adaptive start time, to automatically start the vehicle from a stop at the intersection.

18. The method of claim 17, wherein the method comprises: The adaptive startup time is customized based on at least one of the following: user preferences, environmental factors, and dynamic input factors.

19. The method of claim 18, wherein the method comprises: The adaptive startup time is customized by either increasing or decreasing its value.

20. The method of claim 17, wherein the method comprises: Calculate the adaptive stopping time, where the adaptive stopping time indicates when the vehicle stops at the intersection.

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