Vehicle tracking control method and device

Abstract

The embodiment of the invention discloses a vehicle tracking control method and device, and the method comprises the steps: obtaining the perception information in a vehicle driving process, determining a target path of vehicle driving according to the perception information, determining the tracking deviation of a vehicle based on the target path, and determining the compensation turning angle of the wheel steering of the vehicle according to the tracking deviation and the vehicle speed of the vehicle; on the other hand, according to the axle path tracking point and the axle center point, a tracking deviation vector is determined, according to the preview point and the axle center point, a preview vector is determined, and according to the tracking deviation vector and the preview vector, the preview turning angle of wheel steering of the vehicle is determined. Therefore, according to the compensation rotation angle and the preview rotation angle, a total control rotation angle is determined, and according to the total control rotation angle, wheel steering of the vehicle is controlled. A combined adjustment mode of preview control and fuzzy PID control is adopted, the tracking control precision and steering stability are improved, and the transverse stability and tire abrasion of the vehicle are improved.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving, and in particular to a vehicle tracking control method and device. Background Art

[0002] With the continuous development of artificial intelligence technology, it has been widely used in many fields such as automobile driving. Among them, intelligent driving vehicles use machines to help drivers drive, and completely replace drivers in special circumstances. Therefore, the driving safety of intelligent driving is very important. At present, there are shortcomings such as large tracking deviation and insufficient control stability for the autonomous tracking problem of intelligent driving vehicles. How to improve control accuracy and stability is an urgent problem to be solved. Summary of the invention

[0003] The embodiments of the present application provide a vehicle tracking control method and device, which can improve the accuracy and stability of vehicle control.

[0004] In a first aspect, an embodiment of the present application provides a vehicle tracking control method, which is applied to a vehicle tracking control device, or a chip or circuit configured in the vehicle tracking control device, including:

[0005] Acquire perception information during vehicle travel, and determine a target path for the vehicle based on the perception information; determine a tracking deviation of the vehicle, where the tracking deviation is the distance between an axle center point of the vehicle and a path tracking point in the target path corresponding to the axle center point; determine a compensation angle for wheel steering of the vehicle based on the tracking deviation and the vehicle speed; and control the wheel steering of the vehicle based on the compensation angle.

[0006] The compensation angle of the vehicle's wheel steering is determined by the tracking deviation and the vehicle's speed, and then the vehicle's wheel steering is controlled. Fuzzy PID is used for compensation control to improve the vehicle's tracking accuracy at different speeds and small radius curves, improve the accuracy of tracking control, and improve the vehicle's lateral stability.

[0007] In one possible design, a tracking deviation vector is determined based on an axle path tracking point and the axle center point, wherein the axle path tracking point is a point on the target path vertically mapped from the axle center point in a vehicle coordinate system; a preview vector is determined based on a preview point and the axle center point, wherein the preview point is determined based on a preview distance; a preview angle of the wheel steering of the vehicle is determined based on the tracking deviation vector and the preview vector; and the wheel steering of the vehicle is controlled based on the preview angle.

[0008] The preview angle of the vehicle's wheel steering is determined by the tracking deviation vector and the preview vector, thereby controlling the vehicle's wheel steering. The improved preview control is used as the feedforward control to predict the path ahead in advance, improve the stability of the front axle steering, and respond to the road conditions ahead in advance. During the preview control process, the preview control takes into account both the lateral deviation and the vehicle's heading deviation, thereby improving the accuracy of vehicle control and improving vehicle control performance.

[0009] In a possible design, the total control angle is determined according to the compensation angle and the preview angle; the wheel steering of the vehicle is controlled according to the total control angle. The total control angle is determined by the compensation angle and the preview angle, and then the wheel steering of the vehicle is controlled. The combined adjustment method of preview control and fuzzy PID control not only improves the accuracy of tracking control and steering stability, but also improves the lateral stability of the vehicle and tire wear.

[0010] In a possible design, a weighted sum of the compensation angle and the preview angle is calculated as the total control angle.

[0011] In one possible design, the axles of the vehicle include a front axle and a rear axle, and the total control angle of the front axle steering of the vehicle is determined based on the compensation angle of the front axle steering of the vehicle and the preview angle of the front axle steering of the vehicle, and the wheel steering of the front axle of the vehicle is controlled based on the total control angle of the front axle steering of the vehicle; and the total control angle of the rear axle steering of the vehicle is determined based on the compensation angle of the rear axle steering of the vehicle and the preview angle of the rear axle steering of the vehicle, and the wheel steering of the rear axle of the vehicle is controlled based on the total control angle of the rear axle steering of the vehicle.

[0012] The front axle steering and rear axle steering of the vehicle are controlled respectively through the total control angle of the front axle and the control angle of the rear axle, thereby improving the accuracy of vehicle control and improving the performance of vehicle control.

[0013] In a possible design, the tracking deviation and the vehicle speed are input into a fuzzy controller to determine a fuzzy coefficient; based on the fuzzy coefficient, the parameters of a proportional integral derivative (PID) controller are determined; based on the parameters of the PID controller, the compensation angle of the wheel steering of the vehicle is determined. Through the fuzzy PID control method, the accuracy of the calculated compensation angle of the wheel steering is guaranteed, and the accuracy of vehicle control is improved.

[0014] In one possible design, a vector sum of the tracking deviation vector and the preview vector is calculated; and based on a transformation matrix from a global coordinate system to a vehicle coordinate system, the preview angle is determined according to the vector sum.

[0015] In one possible design, the tracking deviation vector satisfies the following formula:

[0016]

[0017] in, is the tracking deviation vector, (X(t), Y f (t)) is the coordinate of the vehicle path tracking point at time t, (X o (t), Y O (t)) is the coordinate of the center point of the axle at the time t.

[0018] In a possible design, the preview vector satisfies the following formula:

[0019]

[0020] in, is the preview vector, (X tary (t), Y tary (t)) is the coordinate of the preview point at time t, (X O (t), Y O (t)) is the coordinate of the center point of the axle at the time t.

[0021] In a possible design, the target path is a point cloud coordinate sequence in a global coordinate system.

[0022] In a second aspect, an embodiment of the present application provides a vehicle tracking control device, including a perception module, a planning control module and a power steering module, wherein:

[0023] A perception module, used to obtain perception information during the vehicle's travel, and determine a target path for the vehicle's travel based on the perception information;

[0024] a planning control module, configured to determine a tracking deviation of the vehicle, wherein the tracking deviation is a distance between a center point of an axle of the vehicle and a path tracking point corresponding to the center point of the axle in the target path; and determine a compensation angle of the wheel steering of the vehicle according to the tracking deviation and a speed of the vehicle;

[0025] The power steering module is used to control the steering of the wheels of the vehicle based on the compensation angle.

[0026] In a possible design, the planning control module is further used to determine a tracking deviation vector according to an axle path tracking point and the axle center point, wherein the axle path tracking point is a point on the target path vertically mapped from the axle center point in a vehicle coordinate system; determine a preview vector according to a preview point and the axle center point, wherein the preview point is determined according to a preview distance; and determine a preview angle of the wheel steering of the vehicle according to the tracking deviation vector and the preview vector;

[0027] The power steering module is further used to control the wheel steering of the vehicle based on the preview turning angle.

[0028] In a possible design, the planning control module is further used to determine a total control angle according to the compensation angle and the preview angle;

[0029] The control module is also used to control the steering of the wheels of the vehicle according to the total control angle.

[0030] In a possible design, the planning control module is further used to calculate a weighted sum of the compensation angle and the preview angle as the total control angle.

[0031] In one possible design, the planning control module is further used to determine the total control angle of the front axle steering of the vehicle according to the compensation angle of the front axle steering of the vehicle and the preview angle of the front axle steering of the vehicle, and the control module is further used to control the wheel steering of the front axle of the vehicle according to the total control angle of the front axle steering of the vehicle; and

[0032] The planning control module is also used to determine the total control angle of the rear axle steering of the vehicle based on the compensation angle of the rear axle steering of the vehicle and the preview angle of the rear axle steering of the vehicle; the power steering module is also used to control the wheel steering of the rear axle of the vehicle based on the total control angle of the rear axle steering of the vehicle.

[0033] In a possible design, the planning control module is also used to input the tracking deviation and the vehicle speed into a fuzzy controller to determine a fuzzy coefficient; determine parameters of a proportional integral derivative PID controller based on the fuzzy coefficient; and determine a compensation angle for wheel steering of the vehicle based on the parameters of the PID controller.

[0034] In one possible design, the planning control module is further used to calculate the vector sum of the tracking deviation vector and the preview vector; based on the transformation matrix from the global coordinate system to the vehicle coordinate system, determine the preview angle according to the vector sum.

[0035] In one possible design, the tracking deviation vector satisfies the following formula:

[0036]

[0037] in, is the tracking deviation vector, (X(t), Y f (t)) is the coordinate of the vehicle path tracking point at time t, (X O (t), Y O (t)) is the coordinate of the center point of the axle at the time t.

[0038] In a possible design, the preview vector satisfies the following formula:

[0039]

[0040] in, is the preview vector, (X tary (t), Y tary (t)) is the coordinate of the preview point at time t, (X O (t), Y o (t)) is the coordinate of the center point of the axle at the time t.

[0041] In a possible design, the target path is a point cloud coordinate sequence in a global coordinate system.

[0042] The operations and beneficial effects performed by the vehicle tracking control device can refer to the method and beneficial effects described in the first aspect above, and the repeated parts will not be repeated.

[0043] In a third aspect, the present application provides a vehicle-mounted device, which includes a processor and a memory, wherein the memory is used to store a computer program, the processor is used to call the computer program stored in the memory, and the processor executes a method as described in any one of the first aspects.

[0044] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program. When the computer program is executed, the method described in any one of the first aspects is implemented.

[0045] In a fifth aspect, the present application provides a computer program product comprising a computer program, which, when executed, enables the method described in any one of the first aspects to be implemented.

[0046] In a sixth aspect, the present application provides a vehicle, comprising a vehicle tracking control device, the vehicle tracking control device executing a method as described in any one of the first aspects.

[0047] In a seventh aspect, the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is used to communicate with an external device or an internal device, and the processor is used to implement the methods of the above-mentioned various aspects.

[0048] In one possible design, the chip may further include a memory, in which a computer program or instruction is stored, and the processor is used to execute the computer program or instruction stored in the memory, or other programs or instructions. When the computer program or instruction is executed, the processor is used to implement the above-mentioned various aspects of the method.

[0049] In one possible design, the chip can be integrated into a vehicle tracking control device. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the architecture of a vehicle control system provided in an embodiment of the present application;

[0051] Figure 2 It is a flow chart of a vehicle tracking control method provided in an embodiment of the present application;

[0052] Figure 3A It is a vehicle tracking diagram;

[0053] Figure 3B It is a schematic diagram of the front axle preview control;

[0054] Figure 3C It is a schematic diagram of rear axle preview control;

[0055] Figure 4 It is a flow chart of fuzzy control;

[0056] Figure 5A It is a schematic diagram of a function of tracking deviation membership;

[0057] Figure 5B It is a schematic diagram of a function of vehicle speed membership;

[0058] Figure 5C is a schematic diagram of a joint control surface;

[0059] Figure 6 is a flow chart of another vehicle tracking control method provided in an embodiment of the present application;

[0060] Figure 7 is a flow chart of another vehicle tracking control method provided in an embodiment of the present application;

[0061] Figure 8 It is a schematic diagram of a vehicle tracking simulation road condition;

[0062] Fig. 9 is a structural schematic diagram of a vehicle tracking control device provided in an embodiment of the present application;

[0063] Fig.10 It is a structural schematic diagram of a vehicle-mounted device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] like Figure 1 As shown, Figure 1It is a schematic diagram of the architecture of a vehicle control system provided by an embodiment of the present application. The vehicle control system may include a vehicle dynamics model building module, a driver driving and intelligent driving mode tracking control module, and a different control method comparison and parameter influence law analysis module. Among them, the driver driving and intelligent driving mode vehicle tracking control module is mainly used to respectively realize the rear axle tracking control and the front axle tracking control in the driver driving mode, and respectively realize the rear axle tracking control and the front axle tracking control in the driver driving mode. Among them, the rear axle tracking control may include preview tracking control, fuzzy proportional integral differential (proportion integration differentiation, PID) tracking control, and preview + fuzzy PID tracking control, and the front axle tracking control may include preview tracking control, fuzzy PID tracking control, and preview + fuzzy PID tracking control. The specific implementation process of the present application is introduced below.

[0065] like Figure 2 As shown, Figure 2 : is a flow chart of a vehicle tracking control method provided by an embodiment of the present application. The method can be executed by a vehicle tracking control device in a vehicle, and the method mainly includes the following steps:

[0066] S201, acquiring perception information during vehicle driving, and determining a target path for the vehicle according to the perception information.

[0067] The vehicle may be a four-wheel steering (4WS) vehicle.

[0068] Specifically, the perception information of the surrounding environment can be obtained through the on-board sensors, where the perception information may include traffic information such as surrounding vehicles, pedestrians, lane lines, traffic lights and traffic signs. Based on the traffic information such as surrounding vehicles, pedestrians, lane lines, traffic lights and traffic signs, the movement trajectories of other traffic participants can be predicted in advance, and a target path for the vehicle can be planned based on the movement trajectories of other traffic participants.

[0069] The target path is represented as a point cloud coordinate sequence in the global coordinate system, and the vehicle's driving trajectory can also be represented as a point cloud coordinate sequence in the global coordinate system. The tracking deviation and preview vector of the front and rear axles of the vehicle are calculated using the path point cloud coordinates.

[0070] S202, determining a tracking deviation of the vehicle, where the tracking deviation is a distance between an axle center point of the vehicle and a path tracking point corresponding to the axle center point in the target path.

[0071] Specifically, the axle center point may include the front axle center point and the rear axle center point, the tracking deviation of the vehicle may include the tracking deviation of the front axle and the tracking deviation of the front axle, and the front axle center point and the rear axle center point may be used as tracking control points to respectively determine the tracking deviation of the front axle of the vehicle and the tracking deviation of the front axle of the vehicle. The tracking deviation of the front axle of the vehicle is the distance between the front axle center point of the vehicle and the path tracking point corresponding to the front axle center point in the target path, and the tracking deviation of the rear axle of the vehicle is the distance between the rear axle center point of the vehicle and the path tracking point corresponding to the rear axle center point in the target path.

[0072] For example, Figure 3A As shown, Figure 3A is a vehicle tracking diagram. The coordinates of the center point of the front axle at time t are (x 0f (t), y 0f (t)), the coordinates of the path tracking point corresponding to the center point of the front axle in the target path at time t are (x f (t), y f (t)). The tracking deviation of the front axle is e f (t) satisfies the following formula:

[0073]

[0074] Another example Figure 3A As shown, the coordinates of the rear axle center point at time t are (x 0r (t), y 0r (t)), the coordinates of the path tracking point corresponding to the center point of the front axle in the target path at time t are (x r (t), y r (t)). The tracking deviation of the front axle is e r (t) satisfies the following formula:

[0075]

[0076] S203: Determine a compensation angle of the wheel steering of the vehicle according to the tracking deviation and the vehicle speed.

[0077] Specifically, during the driving process of the vehicle, when the center point of the vehicle axle deviates from the center line of the planned path, the tracking deviation and the vehicle speed can be input into a fuzzy controller to determine a fuzzy coefficient; according to the fuzzy coefficient, the parameters of a proportional integral derivative PID controller are determined; according to the parameters of the PID controller, the compensation angle of the wheel steering of the vehicle is determined.

[0078] Furthermore, the tracking deviation of the front axle and the speed of the vehicle can be input into the fuzzy controller to determine the fuzzy coefficient u1; according to the fuzzy coefficient u1, the parameters of the proportional integral derivative PID controller are determined; according to the parameters of the PID controller, the compensation angle δ of the front axle steering of the vehicle is determined 12 In addition, the tracking deviation of the rear axle and the speed of the vehicle can be input into the fuzzy controller to determine the fuzzy coefficient u2; according to the fuzzy coefficient u2, the parameters of the proportional integral derivative PID controller are determined; according to the parameters of the PID controller, the compensation angle δ of the rear axle steering of the vehicle is determined 22 .

[0079] PID control is widely used in industrial control. It has the characteristics of low structure, low cost and stable control effect. Its control rules are as follows:

[0080]

[0081] Among them, K p is the proportionality coefficient, T i is the integration time constant, T d is the differential time constant, and e(t) is the tracking deviation of the front axle.

[0082] However, the traditional PID control parameters cannot be adjusted in real time according to the road conditions. In order to improve the adaptive performance of PID control, a fuzzy control with an improved structure is designed to adjust the control parameters of PID control in real time and improve the robustness of the controller.

[0083] Among them, fuzzy control is suitable for both linear objects with relatively simple structures and nonlinear systems with relatively complex structures and difficult to establish accurate mathematical models. Fuzzy control mainly consists of fuzzification of input quantities, logical rules, databases, fuzzy reasoning and defuzzification, such as Figure 4 As shown, Figure 4 It is a flow chart of fuzzy control. First, the fuzzy controller converts the input variables into fuzzy subsets of corresponding fuzzy language values ​​through fuzzification; secondly, according to the current input tracking deviation and speed, fuzzy reasoning is performed through the rule base and database; finally, defuzzification is to convert the fuzzy quantity obtained in fuzzy reasoning into a certain output quantity.

[0084] The present application embodiment may adopt the membership function and joint control surface of the dual-input single-output fuzzy controller. Figure 5A As shown, Figure 5A is a schematic diagram of the membership function of the tracking deviation. The corresponding membership can be determined according to the tracking deviation. Figure 5B As shown, Figure 5B It is a schematic diagram of the membership function of speed. The corresponding membership can be determined according to the vehicle speed. Figure 5C As shown, Figure 5C It is a schematic diagram of a joint control surface. The compensation angle can be determined according to the tracking deviation e, the vehicle speed v and the fuzzy coefficient u.

[0085] The front axle fuzzy control takes the tracking deviation and vehicle speed of the front axle as input, and the output is set as the fuzzy coefficient u1. The more fuzzy subsets are divided, the more favorable the control accuracy is, but it will also lead to a larger amount of calculation. As shown in Table 1, Table 1 is a fuzzy control rule table of the front axle fuzzy controller. Taking into account the real-time performance and control accuracy of the calculation, the tracking deviation fuzzy set of the front axle of the vehicle is set to {NB, NM, NS, Zero, PS, PM, PB}, and the corresponding quantization factor is set, and the tracking deviation domain is set to [-50, 50]; the vehicle speed fuzzy set is set to {PS, PMS, PM, PMB, PB}, and the vehicle speed domain is set to [-40, 40]; the fuzzy set of the fuzzy coefficient u1 is set to {NB, NM, NS, Zero, PS, PM, PB}, and its domain is quantized to [-48, 48].

[0086] Table 1

[0087]

[0088] The rear axle fuzzy PID tracking controller takes the rear axle tracking deviation and vehicle speed as input, and the output is set as the fuzzy coefficient u2. The design process is the same as that of the front axle fuzzy PID controller. As shown in Table 2, Table 2 is a fuzzy control rule table of the rear axle fuzzy controller. The fuzzy set of the rear axle tracking deviation of the vehicle is set to {NB, NM, NS, Zero, PS, PM, PB}, and its domain is quantized to [-50, 50]; the fuzzy set of the vehicle speed is set to {PS, PMS, PM, PMB, PB}, and its domain is [-40, 40]; the fuzzy set of the fuzzy coefficient u2 of the fuzzy controller is {NB, NM, NS, Zero, PS, PM, PB}, and its domain is [-48, 48].

[0089] Table 2

[0090]

[0091] S204: Control the wheel steering of the vehicle based on the compensation angle.

[0092] Specifically, the wheel steering of the front axle of the vehicle can be controlled based on the compensation angle of the front axle steering, and the wheel steering of the rear axle of the vehicle can be controlled based on the compensation angle of the rear axle steering.

[0093] In the embodiment of the present application, the tracking deviation of the vehicle is determined, and the compensation angle of the vehicle's wheel steering is determined according to the tracking deviation and the vehicle's speed, and then the vehicle's wheel steering is controlled based on the compensation angle. Fuzzy PID is used for compensation control to improve the tracking accuracy of the vehicle at different speeds and small radius curves, improve the accuracy of tracking control, and improve the lateral stability of the vehicle.

[0094] like Figure 6 As shown, Figure 6 : is a flow chart of another vehicle tracking control method provided by an embodiment of the present application. The method can be executed by a vehicle tracking control device in a vehicle, and the method mainly includes the following steps:

[0095] S601, acquiring perception information during vehicle driving, and determining a target path for the vehicle according to the perception information.

[0096] Among them, the specific implementation method of S601 is the same as the specific implementation method of S201. The specific implementation method of S601 can refer to S201 and will not be repeated here.

[0097] S602, determining a tracking deviation vector according to an axle path tracking point and the axle center point, wherein the axle path tracking point is a point on the target path vertically mapped from the axle center point in a vehicle coordinate system.

[0098] Specifically, the tracking deviation vector can be calculated in the global coordinate system according to the coordinates of the axle path tracking point and the coordinates of the axle center point. The tracking deviation vector satisfies the following formula:

[0099]

[0100] in, is the tracking deviation vector, (X(t), Y f (t)) is the coordinate of the vehicle path tracking point at time t, (X O (t), Y o (t)) is the coordinate of the center point of the axle at the time t.

[0101] Furthermore, the tracking deviation vector of the front axle can be calculated based on the coordinates of the front axle path tracking point and the coordinates of the front axle center point. The front axle path tracking point is the point where the front axle center point is vertically mapped to the target path. Figure 3B As shown, Figure 3B This is a schematic diagram of the front axle preview control. Front axle path tracking point Q f The coordinates of (X f (t), Y f (t)), front axle center point O f The coordinates of (XOf (t), Y Of (t)), calculate the tracking deviation vector of the front axle satisfy:

[0102]

[0103] Furthermore, the tracking deviation vector of the rear axle can be calculated based on the coordinates of the rear axle path tracking point and the coordinates of the rear axle center point. The rear axle path tracking point is the point on the target path vertically mapped from the rear axle center point. Figure 3C As shown, Figure 3C This is a schematic diagram of the rear axle preview control. The rear axle path tracking point Q r The coordinates of (X r (t), Y r (t)), rear axle center point O r The coordinates of (X Or (t), Y Or (t)), calculate the tracking deviation vector of the rear axle satisfy:

[0104]

[0105] S603, determining a preview vector according to a preview point and the center point of the axle, wherein the preview point is determined according to a preview distance.

[0106] Specifically, the preview vector can be calculated in the global coordinate system according to the coordinates of the preview point and the coordinates of the center point of the axle. The preview point is empirical data, and the position of the preview point on the target path can be determined according to the preview distance, which can be determined according to the wheelbase of the front and rear axles. The preview vector satisfies the following formula:

[0107]

[0108] in, is the preview vector, (X tary (t), Y tary (t)) is the coordinate of the preview point at time t, (X O (t), Y O (t)) is the coordinate of the center point of the axle at time t.

[0109] Furthermore, the preview vector of the front axle can be calculated based on the coordinates of the preview point of the front axle and the coordinates of the center point of the front axle. The preview point of the front axle on the target path is determined based on the preview distance of the front axle. Figure 3A As shown, the front axle preview point P f The coordinates of (X f_tary (t), Y f_tary (t)) and the front axle center point Of The coordinates of (X Of (t), Y Of (t)), calculate the preview vector of the front axis

[0110]

[0111] Furthermore, the preview vector of the rear axle can be calculated based on the coordinates of the preview point of the rear axle and the coordinates of the center point of the rear axle. The preview point of the rear axle on the target path is determined based on the preview distance of the rear axle. Figure 3B As shown, the rear axle preview point P r The coordinates of (X r_tary (t), Y r_tary (t)) and the center point of the vehicle's rear axle O f The coordinates of (X Of (t), Y Of (t)) Calculate the preview vector of the rear axis

[0112]

[0113] S604: Determine a preview steering angle of the vehicle's wheels according to the tracking deviation vector and the preview vector.

[0114] Specifically, a vector sum of the tracking deviation vector and the preview vector is calculated; and based on a transformation matrix from a global coordinate system to a vehicle coordinate system, the preview angle is determined according to the vector sum.

[0115] like Figure 3B As shown, in the global coordinate system, the tracking deviation vector of the front axle is used and the preview vector of the front axis Calculate the vector sum of the two

[0116]

[0117] Since the vector is the tracking deviation vector of the front axle and the preview vector of the front axis The vector sum of the current axis tracking deviation vector When it is large, the vector The direction is more inclined towards the target path; the tracking deviation vector of the current axis When it is small, the vector The direction of is more inclined to the preview direction. Therefore, select vector The direction of the preview driving direction is the vector The angle with the vehicle body is used as the preview angle of the front axle.

[0118] Among them, the transformation matrix from the global coordinate system to the vehicle coordinate system is:

[0119]

[0120] Where γ is the yaw angle of the vehicle.

[0121] Use the above transformation matrix to calculate the vector sum in the vehicle coordinate system

[0122]

[0123] Front axle preview angle:

[0124]

[0125] like Figure 3C As shown, in the global coordinate system, the tracking deviation vector of the rear axle is used and the preview vector of the rear axis Calculate the vector sum of the two

[0126]

[0127] Similarly, due to the preview vector of the rear axis is the tracking deviation vector of the rear axle and the preview vector of the rear axis The vector sum of the rear axle’s tracking deviation vector When it is large, the preview vector The direction is more biased towards the rear axle target trajectory; when the rear axle tracking deviation vector When it is small, the vector The direction of is more inclined to the preview direction. Therefore, select vector The direction of the preview driving direction is the vector The angle with the vehicle body is used as the preview angle of the rear axle.

[0128] Use the above coordinate transformation matrix to calculate the vector sum in the vehicle coordinate system

[0129]

[0130] Preview angle of rear axle:

[0131]

[0132] S605: Control the wheel steering of the vehicle based on the preview turning angle.

[0133] Specifically, the wheel steering of the front axle of the vehicle can be controlled based on the preview steering angle of the front axle steering, and the wheel steering of the rear axle of the vehicle can be controlled based on the preview steering angle of the rear axle steering.

[0134] In the embodiment of the present application, the preview angle of the vehicle's wheel steering is determined by the tracking deviation vector and the preview vector, thereby controlling the vehicle's wheel steering. The improved preview control is used as the feedforward control to predict the path ahead in advance, improve the stability of the front axle steering, and respond to the road conditions ahead in advance. In the preview control process, the preview control takes into account both the lateral deviation and the vehicle's heading deviation, thereby improving the accuracy of vehicle control and improving the vehicle control performance.

[0135] like Figure 7 As shown, Figure 7 : is a flow chart of another vehicle tracking control method provided by an embodiment of the present application. The method can be executed by a vehicle tracking control device in a vehicle, and the method mainly includes the following steps:

[0136] S701, acquiring perception information during vehicle driving, and determining a target path for the vehicle based on the perception information.

[0137] S702, determining a tracking deviation of the vehicle, where the tracking deviation is a distance between an axle center point of the vehicle and a path tracking point corresponding to the axle center point in the target path.

[0138] S703: Determine a compensation angle of the wheel steering of the vehicle according to the tracking deviation and the speed of the vehicle.

[0139] The specific implementation method of S701-S703 is the same as that of S201-S203. The specific implementation method of S701-S703 can refer to S201-S203 and will not be repeated here.

[0140] S704, determining a tracking deviation vector according to the axle path tracking point and the axle center point.

[0141] The axle path tracking point is a point on the target path vertically mapped from the axle center point in vehicle coordinates.

[0142] S705, determining a preview vector according to a preview point and the center point of the axle, wherein the preview point is determined according to a preview distance.

[0143] S706: Determine a preview steering angle of the vehicle's wheels according to the tracking deviation vector and the preview vector.

[0144] The specific implementation method of S704-S706 is the same as the specific implementation method of S602-S604. The specific implementation method of S704-S706 can refer to S602-S604 and will not be repeated here.

[0145] S707: Determine a total control angle according to the compensation angle and the preview angle.

[0146] The total control angle is a weighted sum of the compensation angle and the preview angle.

[0147] Specifically, the total control angle of the front axle steering of the vehicle can be determined according to the compensation angle of the front axle steering of the vehicle and the preview angle of the front axle steering of the vehicle. Further, the weighted sum of the compensation angle of the front axle steering and the preview angle of the front axle steering of the vehicle can be used as the total control angle of the front axle steering.

[0148] The total control angle of the front axle steering is obtained by weighting the combined control adjustment of the preview control of the front axle and the fuzzy PID compensation control of the front axle. The calculation formula of the total control angle of the front axle steering is as follows:

[0149] δ1(t)=w1δ 11 (t)+w2δ 12 (t)

[0150] Among them, w1 and w2 are δ 11 (t) and δ 12 The weighted value of (t).

[0151] According to the compensation angle of the rear axle steering of the vehicle and the preview angle of the rear axle steering of the vehicle, the total control angle of the rear axle steering of the vehicle is determined. Further, the weighted sum of the compensation angle of the rear axle steering and the preview angle of the rear axle steering of the vehicle can be used as the total control angle of the rear axle steering.

[0152] The total control angle of the rear axle steering is the combined control adjustment result of the above-mentioned rear axle preview control and the rear axle fuzzy PID compensation control, and is obtained after weighting. The calculation formula of the total control angle of the rear axle steering is as follows:

[0153] δ2(t)=w 21 δ 21 (t)+w 22 δ 22 (t)

[0154] Among them, w 21 and w 22 is δ 21 (t) and δ 22 The weighted value of (t).

[0155] S708: Control the wheel steering of the vehicle according to the total control angle.

[0156] Specifically, the wheel steering of the front axle of the vehicle can be controlled according to the total control angle of the front axle steering of the vehicle, and the wheel steering of the rear axle of the vehicle can be controlled according to the total control angle of the rear axle steering of the vehicle.

[0157] like Figure 3A As shown, through the joint control adjustment of the preview control of the front axle and the fuzzy PID compensation control of the front axle, the total control angle of the front axle steering of the vehicle is determined to be δ1(t), and through the joint control adjustment of the preview control of the rear axle and the fuzzy PID compensation control of the front axle, the total control angle of the rear axle steering of the vehicle is determined to be δ2(t). The wheel steering of the front axle of the vehicle is controlled by the total control angle of δ1(t), and the wheel steering of the rear axle of the vehicle is controlled by the total control angle of δ2(t). Thus, the accuracy and stability of vehicle control are achieved.

[0158] In the embodiment of the present application, the total control angle is determined by the compensation angle and the preview angle, thereby controlling the wheel steering of the vehicle. The combined adjustment method of preview control and fuzzy PID control not only improves the tracking control accuracy and steering stability, but also improves the lateral stability of the vehicle and tire wear.

[0159] The present application can use the following method to simulate the above tracking control method and verify the control performance.

[0160] As shown in Table 3, Table 3 is a vehicle parameter table. Matlab / Simulink is used to build preview control, fuzzy PID control and preview control + fuzzy PID double-layer tracking controller. Figure 8 As shown, Figure 8 This is a schematic diagram of a vehicle tracking simulation road condition. The simulated road condition consists of straight segments, arc segments with different turning radii, and lane changes. The road adhesion coefficient μ is set to 0.85, and the set road condition can basically reflect the turning conditions of urban roads. Under the condition of vehicle speed V = 25km / h, the control performance of the tracking control method is verified through the joint simulation of the four-wheel steering vehicle dynamics model and the tracking controller.

[0161] Table 3

[0162] Serial number Main parameters Quantity 1 <![CDATA[Mass \m1]]> 1270(kg) 2 <![CDATA[Wheelbase \l1]]> 2910(mm) 3 <![CDATA[Front axle tire radius \R1]]> 334(mm) 4 <![CDATA[Front axle tire radius \R2]]> 334(mm) 5 <![CDATA[Moment of inertia about the x-axis \I x > <![CDATA[536.6(kg·m 2 )]]> 6 <![CDATA[Moment of inertia about the y-axis \I y > <![CDATA[1536.7(kg·m 2 )]]> 7 <![CDATA[Moment of inertia about the z-axis \I z > <![CDATA[1536.7(kg·m 2 )]]>

[0163] The embodiment of the present application can divide the functional modules of the vehicle tracking control device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into a planning control module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation. The following is an example of dividing each functional module according to each function.

[0164] Above, combined Figure 2 , Figure 6 and Figure 7 The method provided by the embodiment of the present application is described in detail. Fig. 9 The vehicle tracking control device provided by the embodiment of the present application is described in detail. It should be understood that the description of the device embodiment corresponds to the description of the method embodiment, so the contents not described in detail can be referred to the method embodiment above, and for the sake of brevity, they will not be repeated here.

[0165] See also Fig. 9 , Fig. 9 9 is a schematic diagram of the structure of a vehicle tracking control device provided in an embodiment of the present application. The vehicle tracking control device may include a perception module 901, a planning control module 902 and a power steering module 903.

[0166] In one possible design, the vehicle tracking control device can implement steps or processes corresponding to those performed by the vehicle tracking control device in the above method embodiment. For example, it can be a vehicle-mounted device, or a chip or circuit configured in the vehicle-mounted device.

[0167] The perception module 901 is used to obtain the perception information of the vehicle during driving;

[0168] The planning control module 902 is used to determine the target path of the vehicle according to the perception information, determine the tracking deviation of the vehicle, and the tracking deviation is the distance between the axle center point of the vehicle and the path tracking point corresponding to the axle center point in the target path; determine the compensation angle of the wheel steering of the vehicle according to the tracking deviation and the speed of the vehicle;

[0169] The power steering module 903 is used to control the wheel steering of the vehicle based on the compensation angle.

[0170] Optionally, the planning control module 902 is further used to determine a tracking deviation vector according to an axle path tracking point and the axle center point, wherein the axle path tracking point is a point on the target path vertically mapped from the axle center point in vehicle coordinates; determine a preview vector according to a preview point and the axle center point, wherein the preview point is determined according to a preview distance; and determine a preview angle of the wheel steering of the vehicle according to the tracking deviation vector and the preview vector;

[0171] The power steering module 903 is further used to control the wheel steering of the vehicle based on the preview turning angle.

[0172] Optionally, the planning control module 902 is further configured to determine a total control angle according to the compensation angle and the preview angle;

[0173] The power steering module 903 is further used to control the wheel steering of the vehicle according to the total control angle.

[0174] Optionally, the planning control module 902 is further configured to calculate a weighted sum of the compensation angle and the preview angle as the total control angle.

[0175] Optionally, the planning control module 902 is further used to determine the total control angle of the front axle steering of the vehicle according to the compensation angle of the front axle steering of the vehicle and the preview angle of the front axle steering of the vehicle, and the power steering module 903 is further used to control the wheel steering of the front axle of the vehicle according to the total control angle of the front axle steering of the vehicle; and

[0176] The planning control module 902 is also used to determine the total control angle of the rear axle steering of the vehicle based on the compensation angle of the rear axle steering of the vehicle and the preview angle of the rear axle steering of the vehicle. The power steering module 903 is also used to control the wheel steering of the rear axle of the vehicle based on the total control angle of the rear axle steering of the vehicle.

[0177] Optionally, the planning control module 902 is also used to input the tracking deviation and the vehicle speed into a fuzzy controller to determine a fuzzy coefficient; determine parameters of a proportional integral derivative PID controller based on the fuzzy coefficient; and determine a compensation angle of the vehicle's wheel steering based on the parameters of the PID controller.

[0178] Optionally, the planning control module 902 is further used to calculate the vector sum of the tracking deviation vector and the preview vector; and determine the preview angle according to the vector sum based on a transformation matrix from a global coordinate system to a vehicle coordinate system.

[0179] Optionally, the tracking deviation vector satisfies the following formula:

[0180]

[0181] in, is the tracking deviation vector, (X(t), Y f (t)) is the coordinate of the vehicle path tracking point at time t, (X o (t), Y O (t)) is the coordinate of the center point of the axle at the time t.

[0182] Optionally, the preview vector satisfies the following formula:

[0183]

[0184] in, is the preview vector, (X tary (t), Y tary (t)) is the coordinate of the preview point at time t, (X O (t), Y O (t)) is the coordinate of the center point of the axle at the time t.

[0185] Optionally, the target path is a point cloud coordinate sequence in a global coordinate system.

[0186] It should be noted that the implementation of each module can also refer to Figure 2 , Figure 6 and Figure 7 The corresponding description of the method embodiment shown executes the method and functions performed by the vehicle tracking control device in the above embodiment.

[0187] Fig.10 is a schematic diagram of the structure of a vehicle-mounted device provided in an embodiment of the present application. The vehicle-mounted device can be applied to Figure 1 In the system shown, the functions of the vehicle tracking control device in the above method embodiment are executed, or the steps or processes executed by the vehicle tracking control device in the above method embodiment are realized. The vehicle-mounted device can be a vehicle, or a vehicle-mounted system configured in a vehicle.

[0188] like Fig.10 As shown, the vehicle-mounted device includes a processor 1001 (such as a central processing unit CPU) and a transceiver 1002. Optionally, the vehicle-mounted device also includes a memory 1003. Optionally, the vehicle-mounted device may also include a controller to control the steering of the wheels of the axle of the vehicle during movement.

[0189] The processor 1001, the transceiver 1002 and the memory 1003 can communicate with each other through an internal connection path to transmit control and / or data signals. The memory 1003 is used to store a computer program, and the processor 1001 is used to call and run the computer program from the memory 1003 to control the transceiver 1002 to send and receive signals. Optionally, the vehicle-mounted device may also include an antenna for sending the uplink data or uplink control signaling output by the transceiver 1002 through a wireless signal.

[0190] The processor 1001 and the memory 1003 may be combined into a processing device, and the processor 1001 is used to execute the program code stored in the memory 1003 to implement the above functions. In specific implementation, the memory 1003 may also be integrated into the processor 1001, or independent of the processor 1001. Figure 8 Corresponding to the planning control module in.

[0191] The transceiver 1002 may also be referred to as a transceiver unit or a transceiver module. The transceiver 1002 may include a receiver (or receiver, receiving circuit) and a transmitter (or transmitter, transmitting circuit). The receiver is used to receive signals, and the transmitter is used to transmit signals.

[0192] It should be understood that Fig.10 The vehicle-mounted device shown can achieve Figure 2 , Figure 6 and Figure 7 The method embodiment shown involves various processes of the vehicle tracking control device. The operations and / or functions of each module in the vehicle-mounted device are respectively to implement the corresponding processes in the above method embodiment. For details, please refer to the description in the above method embodiment. To avoid repetition, the detailed description is appropriately omitted here.

[0193] The processor 1001 can be used to execute the actions implemented by the vehicle tracking control device in the previous method embodiment, and the transceiver 1002 can be used to execute the actions of the vehicle tracking control device sending to or receiving from other devices described in the previous method embodiment. Please refer to the description in the previous method embodiment for details, which will not be repeated here.

[0194] Among them, the processor 1001 can be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It can implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the contents disclosed in this application. The processor 1001 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processor and a microprocessor, and so on. The communication bus 1004 can be a peripheral component interconnect standard PCI bus or an extended industrial standard structure EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.10 Only one thick line is used to represent it, but it does not mean that there is only one bus or one type of bus. The communication bus 1004 is used to realize the connection and communication between these components. Among them, the transceiver 1002 in the embodiment of the present application is used to communicate signaling or data with other node devices. The memory 1003 may include volatile memory, such as nonvolatile dynamic random access memory (NVRAM), phase change random access memory (PRAM), magnetoresistive random access memory (MRAM), etc., and may also include non-volatile memory, such as at least one disk storage device, electrically erasable programmable read-only memory (EEPROM), flash memory devices, such as NOR flash memory or NAND flash memory, semiconductor devices, such as solid state disk (SSD), etc. The memory 1003 may also be at least one storage device located away from the aforementioned processor 1001. The memory 1003 may optionally store a set of computer program codes or configuration information. Optionally, the processor 1001 may also execute a program stored in the memory 1003. The processor may cooperate with the memory and the transceiver to execute any method and function of the vehicle tracking control device in the above-mentioned application embodiment.

[0195] An embodiment of the present application also provides a chip system, which includes a processor for supporting a vehicle tracking control device to implement the functions involved in any of the above embodiments, such as generating or processing the control angle involved in the above method.

[0196] In a possible design, the chip system may also include a memory, and the memory is used for the vehicle tracking control device to store necessary program instructions and data. The chip system may be composed of a chip, or may include a chip and other discrete devices. The input and output of the chip system correspond to the receiving and sending operations of the vehicle tracking control device in the method embodiment.

[0197] An embodiment of the present application also provides a vehicle, which includes a vehicle tracking control device, which is used to support the vehicle tracking control device to implement the functions involved in any of the above embodiments, such as generating or processing the control angle involved in the above method.

[0198] According to the method provided in the embodiment of the present application, the present application also provides a computer program product, the computer program product comprising: a computer program, when the computer program is run on a computer, causes the computer to execute Figure 2 , Figure 6 and Figure 7 A method according to any one of the embodiments shown.

[0199] According to the method provided in the embodiment of the present application, the present application also provides a computer readable medium, which stores a computer program, and when the program code is run on a computer, the computer executes Figure 2 , Figure 6 and Figure 7 A method according to any one of the embodiments shown.

[0200] The "multiple" mentioned in the embodiments of this application refers to two or more; "and / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural; the character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship. Also, unless otherwise specified, the "first" mentioned in the embodiments of this application is only used as a name identifier and is not used to limit the order, timing, priority or importance of multiple objects. The same rule applies to "second", "third" and "fourth" and so on.

[0201] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disc (SSD)).

[0202] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A vehicle tracking control method, characterized in that: The method comprises: Acquiring sensory information during vehicle travel, and determining a target path for the vehicle according to the sensory information; Determining a tracking deviation of the vehicle, the tracking deviation being a distance between a center point of an axle of the vehicle and a path tracking point in the target path corresponding to the center point of the axle; Determining a compensation angle of the wheel steering of the vehicle according to the tracking deviation and the speed of the vehicle; Based on the compensation angle, the wheel steering of the vehicle is controlled.

2. The method according to claim 1, characterized in that The method further comprises: Determining a tracking deviation vector according to an axle path tracking point and the axle center point, wherein the axle path tracking point is a point on the target path vertically mapped from the axle center point in vehicle coordinates; Determine a preview vector according to a preview point and the center point of the axle, wherein the preview point is determined according to a preview distance; Determine a preview angle of the wheel steering of the vehicle according to the tracking deviation vector and the preview vector; Based on the preview angle, the wheel steering of the vehicle is controlled.

3. The method according to claim 2, characterized in that The method further comprises: Determining a total control angle according to the compensation angle and the preview angle; The wheel steering of the vehicle is controlled according to the total control steering angle.

4. The method according to claim 3, characterized in that Determining the total control angle according to the compensation angle and the preview angle comprises: A weighted sum of the compensation angle and the preview angle is calculated as the total control angle.

5. The method according to claim 3, characterized in that The axle of the vehicle includes a front axle and a rear axle, and the method further includes: Determine a total control angle of the front axle steering of the vehicle according to a compensation angle of the front axle steering of the vehicle and a preview angle of the front axle steering of the vehicle, and control the wheel steering of the front axle of the vehicle according to the total control angle of the front axle steering of the vehicle; and The total control angle of the rear axle steering of the vehicle is determined based on the compensation angle of the rear axle steering of the vehicle and the preview angle of the rear axle steering of the vehicle, and the wheel steering of the rear axle of the vehicle is controlled based on the total control angle of the rear axle steering of the vehicle.

6. The method according to claim 1, characterized in that Determining the compensation angle of the wheel steering of the vehicle according to the tracking deviation and the speed of the vehicle comprises: Inputting the tracking deviation and the vehicle speed into a fuzzy controller to determine a fuzzy coefficient; Determining parameters of a proportional-integral-derivative (PID) controller according to the fuzzy coefficient; The compensation angle of the wheel steering of the vehicle is determined according to the parameters of the PID controller.

7. The method according to claim 2, characterized in that Determining the preview angle according to the tracking deviation vector and the preview vector comprises: Calculating a vector sum of the tracking deviation vector and the preview vector; The preview angle is determined according to the vector sum based on a transformation matrix from a global coordinate system to a vehicle coordinate system.

8. The method according to any one of claims 1 to 7, characterized in that: The target path is a point cloud coordinate sequence in the global coordinate system.

9. A vehicle tracking control device, characterized in that: The device comprises a perception module, a planning control module and a power steering module, wherein: The perception module is used to obtain perception information during the vehicle's driving process; The planning control module is used to determine the target path of the vehicle according to the perception information; determine the tracking deviation of the vehicle, the tracking deviation being the distance between the axle center point of the vehicle and the path tracking point corresponding to the axle center point in the target path; and determine the compensation angle of the wheel steering of the vehicle according to the tracking deviation and the vehicle speed; The power steering module is used to control the wheel steering of the vehicle based on the compensation angle.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed on a computer, the computer is enabled to execute the method according to any one of claims 1 to 8.

11. A vehicle, characterized in that: The vehicle comprises a vehicle tracking control device, and the vehicle tracking control device is used to execute the method as described in any one of claims 1-8.

Images