Path tracking control method and device and storage medium
By generating a globally planned driving path and calculating the heading angle error and yaw rate error, the front wheel steering angle is adjusted, which solves the problem of insufficient path tracking accuracy and stability in the existing technology and achieves high-precision and stable path tracking control.
Patent Information
- Application Number
- CN202511397401.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-28
- Publication Date
- 2025-12-23
AI Technical Summary
In existing technologies, pure tracking algorithms and traditional Stanley algorithms suffer from insufficient tracking accuracy and stability during path tracking, making it difficult to balance the accuracy and stability of the vehicle during path tracking.
By receiving the user-defined starting point and destination, a globally planned driving path is generated. Data such as vehicle speed, heading angle, yaw rate, and front wheel steering angle are obtained. The heading angle error, yaw rate error, and lateral error are calculated, and the front wheel steering angle is adjusted to achieve precise tracking.
It achieves effective control of vehicle path tracking while ensuring tracking accuracy and stability, thereby improving the accuracy and stability of path tracking.
Smart Images
Figure CN121187285A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vehicle control technology, and in particular to a path tracking control method, device, and storage medium. Background Technology
[0002] Path tracking control is one of the key technologies for autonomous driving, aiming to enable the vehicle to accurately track a predetermined path by adjusting its direction and speed in real time. Related technologies employ pure tracking algorithms and the traditional Stanley control algorithm for path tracking. The pure tracking algorithm is based on geometry and kinematics control, while the traditional Stanley algorithm is a lateral control algorithm based on a geometric model.
[0003] In related technologies, pure tracking algorithms suffer from the problem that path tracking performance is directly affected by the forward-looking distance, making it difficult to achieve both tracking accuracy and stability during path tracking. Furthermore, the traditional Stanley algorithm does not consider the error between the instantaneous path and the vehicle's yaw rate, resulting in low control accuracy in path tracking. Therefore, how to control vehicle path tracking to ensure both tracking accuracy and stability is a problem that needs to be solved. Summary of the Invention
[0004] This application provides a path tracking control method, apparatus, and storage medium, which can be used to ensure tracking accuracy and stability. The technical solution is as follows:
[0005] On one hand, embodiments of this application provide a path tracking control method, the method comprising:
[0006] Receive the starting point and destination of the planned trip set by the user;
[0007] A globally planned driving path is generated based on the driving start point and the target end point, and the globally planned driving path includes multiple sampling points;
[0008] Obtain the coordinate data of each sampling point in a preset coordinate system, wherein the preset coordinate system is a planar coordinate system;
[0009] Acquire the vehicle's speed, heading angle, yaw rate, front wheel steering angle, and the vehicle's coordinates in the preset coordinate system;
[0010] Based on the driving speed, the heading angle, the yaw rate, and the vehicle's coordinate data in the preset coordinate system, combined with the coordinate data of the nearest sampling point in front of the vehicle in the preset coordinate system, the heading angle error, yaw rate error, and lateral error are calculated.
[0011] The target steering angle of the front wheels is calculated based on the heading angle error, the yaw rate error, and the lateral error.
[0012] In response to the fact that the steering angle of the front wheel is not equal to the target steering angle of the front wheel, the steering angle of the front wheel is adjusted based on the target steering angle of the front wheel.
[0013] On the other hand, a path tracking control device is provided, the device comprising:
[0014] The receiving module is used to receive the starting point and destination of the planned trip set by the user.
[0015] The generation module is used to generate a globally planned driving path based on the driving start point and the target end point, wherein the globally planned driving path includes multiple sampling points;
[0016] The first acquisition module is used to acquire the coordinate data of each sampling point in a preset coordinate system, wherein the preset coordinate system is a planar coordinate system.
[0017] The second acquisition module is used to acquire the vehicle's driving speed, heading angle, yaw rate, steering angle of the front wheels, and coordinate data of the vehicle in the preset coordinate system.
[0018] The first calculation module is used to calculate the heading angle error, yaw rate error and lateral error based on the driving speed, the heading angle, the yaw rate and the vehicle's coordinate data in the preset coordinate system, combined with the coordinate data of the nearest sampling point in front of the vehicle in the preset coordinate system.
[0019] The second calculation module is used to calculate the target steering angle of the front wheel based on the heading angle error, the yaw rate error, and the lateral error;
[0020] An adjustment module is used to adjust the steering angle of the front wheel based on the target steering angle of the front wheel in response to the front wheel's steering angle not being equal to the target steering angle of the front wheel.
[0021] On the other hand, a non-transitory computer-readable storage medium is also provided, characterized in that the computer-readable storage medium stores a computer program, which is loaded and executed by a processor to implement any of the path tracking control methods described above.
[0022] On the other hand, a computer program product is also provided, the computer program product including computer instructions, which, when executed by a processor, implement the steps of any of the path tracking control methods described above.
[0023] The technical solution provided in this application brings at least the following beneficial effects:
[0024] This application performs global planning of the planned journey based on the user-defined starting point and destination, obtaining a globally planned driving path including multiple sampling points. It then acquires the coordinate data of each sampling point in a planar coordinate system for subsequent calculations. Combining the vehicle's speed, heading angle, yaw rate, front wheel steering angle, and the vehicle's coordinate data in a preset coordinate system, it calculates the heading angle error, yaw rate error, and lateral error. Furthermore, based on these errors, it calculates the target steering angle of the front wheels. If the front wheel steering angle is not equal to the target steering angle, it adjusts the front wheel steering angle accordingly. This technical solution enables control of vehicle path tracking while ensuring tracking accuracy and stability. Attached Figure Description
[0025] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0026] Figure 1 This is a schematic diagram of an implementation environment provided in an embodiment of this application;
[0027] Figure 2 This is a flowchart of a path tracking control method provided in an embodiment of this application;
[0028] Figure 3 This is a schematic diagram of a road where a vehicle is located, provided in an embodiment of this application;
[0029] Figure 4 This is a schematic diagram of the structure of a path tracking control device provided in an embodiment of this application. Detailed Implementation
[0030] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.
[0031] This application provides a path tracking control method. Please refer to... Figure 1 The diagram illustrates the implementation environment of the method provided in this application embodiment. This implementation environment may include: a domain controller 11, a central control console display screen 12, an inertial measurement unit 13, a steering angle sensor 14, and a steer-by-wire unit 15.
[0032] Optionally, the display screen 12 on the center console displays the map interface of the navigation system and multiple driving routes, receives the user's selected starting point, destination, and selected driving route, and sends them to the domain controller 11; the inertial measurement unit 13 acquires the vehicle's speed, heading angle, and yaw rate and sends them to the domain controller 11; the steering angle sensor 14 is located at the front wheel of the vehicle and is used to acquire the steering angle of the front wheel; the steer-by-wire unit 15 adjusts the steering angle of the front wheel to the target steering angle according to the instructions of the domain controller 11. The domain controller 11, the display screen 12 on the center console, the inertial measurement unit 13, the steering angle sensor 14, and the steer-by-wire unit 15 establish a communication connection via a wired or wireless network.
[0033] Based on the above Figure 1 The implementation environment shown in this application provides a path tracking control method, such as... Figure 2 As shown, taking the application of this method to a domain controller as an example, the method includes steps 201-207.
[0034] In step 201, the domain controller receives the starting point and destination of the planned trip set by the user.
[0035] In one possible implementation, the user can set the starting point and destination of a planned trip through the vehicle's central control panel. For example, the user can open the navigation system's map interface on the central control panel's display screen and select the starting point and destination; alternatively, the user can speak the starting point and destination to the central control panel's voice recognition device. Exemplarily, after receiving the user's set starting point and destination, the central control panel sends these information to the domain controller.
[0036] In step 202, the domain controller generates a globally planned driving path based on the starting point and the destination. The globally planned driving path includes multiple sampling points.
[0037] Optionally, after obtaining the starting point and destination of the planned trip set by the user, the domain controller generates a globally planned driving path based on the starting point and destination, wherein the globally planned driving path includes multiple sampling points.
[0038] In one possible implementation, the domain controller generates a globally planned driving route based on the starting point and the destination, including: the domain controller can obtain multiple driving routes from the starting point to the destination through the navigation system, and then display the multiple driving routes through the display screen of the central control panel; after receiving the driving route selected by the user, the domain controller uses the driving route selected by the user as the globally planned driving route.
[0039] For example, the domain controller can determine multiple sampling points in the globally planned driving path through the navigation system. Optionally, the number of sampling points can be determined based on the length and type of the globally planned path. For instance, the globally planned driving path can be divided into multiple segments of different types, with a sampling point set at intervals between each segment. The intervals for different path types can be set empirically, and path types include straight lines, U-shaped curves, acute-angle curves, and obtuse-angle curves.
[0040] In step 203, the domain controller acquires the coordinate data of each sampling point in a preset coordinate system, which is a planar coordinate system.
[0041] In one possible implementation, after setting the sampling points in the global planning driving path, the domain controller obtains the coordinate data of each sampling point in the preset coordinate system, including: obtaining the longitude and latitude information of the sampling points; and converting the longitude and latitude information into the coordinate data of the sampling points in the preset coordinate system by projection.
[0042] Optionally, the domain controller can obtain the longitude and latitude information of each sampling point through the navigation system, and then use the Gauss-Kruger projection method to convert the longitude and latitude information of each sampling point into planar coordinate data in a preset coordinate system. In one possible implementation, the Gauss-Kruger projection method is used to convert angle-based longitude and latitude coordinates into length-based Cartesian coordinates. The preset coordinate system can be set empirically, for example, the horizontal axis is set as the x-axis and the vertical axis is set as the y-axis.
[0043] In step 204, the domain controller acquires the vehicle's speed, heading angle, yaw rate, front wheel steering angle, and the vehicle's coordinates in a preset coordinate system.
[0044] For example, after performing coordinate transformation on the sampling points, the domain controller acquires the vehicle's speed, heading angle, yaw rate, front wheel steering angle, and vehicle coordinate data in a preset coordinate system. This includes: the domain controller acquires the vehicle's speed, heading angle, and yaw rate through an inertial measurement unit; acquires the front wheel steering angle through a front wheel steering angle sensor; acquires the vehicle's longitude and latitude information through a navigation system; and then converts the vehicle's longitude and latitude information into planar coordinate data in a preset coordinate system using a Gauss-Kruger projection method.
[0045] In step 205, the domain controller calculates the heading angle error, yaw rate error, and lateral error based on the driving speed, heading angle, yaw rate, and vehicle coordinate data in the preset coordinate system, combined with the coordinate data of the nearest sampling point in front of the vehicle in the preset coordinate system.
[0046] In one possible implementation, after obtaining the vehicle's speed, heading angle, yaw rate, front wheel steering angle, and the planar coordinate data of the sampling points and the vehicle, the heading angle error, yaw rate error, and lateral error are calculated based on the speed, heading angle, yaw rate, and the vehicle's coordinate data in a preset coordinate system, combined with the coordinate data of the nearest sampling point in front of the vehicle in the preset coordinate system. This includes: selecting the sampling point in front of the vehicle that is closest to the vehicle's current position; obtaining the angle between the tangent direction of the path at the nearest sampling point and the coordinate axis, as the target heading angle; obtaining the curvature of the path at the nearest sampling point; calculating the target yaw rate of the path at the sampling point based on the curvature and the speed; calculating the distance from the vehicle to the nearest sampling point, as the lateral error; calculating the difference between the heading angle and the target heading angle, as the heading angle error; and calculating the difference between the yaw rate and the target yaw rate, as the yaw rate error.
[0047] Optionally, the domain controller selects the sampling point closest to the vehicle's current location from the sampling points in front of the vehicle. It then uses the navigation system to obtain the angle between the tangent direction of the path at that closest sampling point and the coordinate axis, as well as the curvature of the path at that closest sampling point. The angle between the tangent direction and the coordinate axis is used as the target heading angle. After obtaining the curvature, the target yaw rate of the path at the sampling point is calculated based on the curvature and the driving speed. This includes calculating the product of the curvature and the driving speed, and using the result as the target yaw rate of the path at the sampling point.
[0048] For example, the domain controller calculates the distance from the vehicle to the nearest sampling point, using the result as the lateral error; calculates the difference between the heading angle and the target heading angle, using the result as the heading angle error; and calculates the difference between the yaw rate and the target yaw rate, using the result as the yaw rate error. In one possible implementation, a schematic diagram of the vehicle on the road is shown below. Figure 3 As shown, φ is the heading angle error, and e is the lateral error. The target steering angle for the front wheels.
[0049] In step 206, the domain controller calculates the target steering angle of the front wheels based on the heading angle error, the yaw rate error, and the lateral error.
[0050] In one possible implementation, after calculating the heading angle error, yaw rate error, and lateral error, the target steering angle of the front wheels is calculated based on these errors, including: calculating the product of the heading angle error and a first adjustable gain parameter to obtain a first calculation result; calculating the product of the lateral error and a second adjustable gain parameter, dividing by the sum of the driving speed plus 1 to obtain a second calculation result; calculating the product of a third adjustable gain parameter and the arctangent function of the second calculation result to obtain a third calculation result; calculating the integral of the heading angle error with respect to time and multiplying it by the product of a fourth adjustable gain parameter to obtain a fourth calculation result; calculating the yaw rate error and multiplying it by the product of a fifth adjustable gain parameter to obtain a fifth calculation result; and calculating the sum of the first, third, fourth, and fifth calculation results as the target steering angle of the front wheels.
[0051] Optionally, the formula for calculating the target steering angle of the front wheels is as follows:
[0052]
[0053] Where k0 is the first adjustable gain parameter, k1 is the second adjustable gain parameter, k2 is the third adjustable gain parameter, k3 is the fourth adjustable gain parameter, and k4 is the fifth adjustable gain parameter. Let φ(t) be the target steering angle of the front wheels, φ(t) be the heading angle error, e(t) be the lateral error, v(t) be the driving speed, and ψ'(t) - ψ route '(t) represents the error in yaw rate.
[0054] For example, the values of the first, second, third, fourth, and fifth adjustable gain parameters can be determined through experiments on a simulated vehicle. For instance, before calculating the target steering angle of the front wheels based on the heading angle error, yaw rate error, and lateral error, the domain controller generates multiple sets of adjustable gain parameters to be selected based on the value ranges of each adjustable gain parameter; the steering angle of the front wheels of the simulated vehicle corresponding to the vehicle is controlled based on the selected adjustable gain parameter sets; the lateral error of the simulated vehicle is collected under the control of the selected adjustable gain parameter sets; the integral of the product of the lateral error and time of the simulated vehicle with respect to time is calculated to obtain a sixth calculation result; the adjustable gain parameter set corresponding to the minimum value in the sixth calculation result is selected as the adjustable gain parameter set for controlling the steering angle of the front wheels of the vehicle.
[0055] In one possible implementation, the value range of each adjustable gain parameter can be set empirically. The domain controller adaptively optimizes the values of each adjustable gain parameter using a multi-population genetic algorithm based on the set value range. For example, multiple sets of adjustable gain parameters to be screened are generated based on the value range of each adjustable gain parameter. Each set of adjustable gain parameters to be screened is then substituted into the calculation formula for the target steering angle of the front wheels. The steering angle of the simulated vehicle's front wheels is controlled according to the calculated expected front wheel steering angle. After a period of time, the lateral error of the simulated vehicle under the control of each set of adjustable gain parameters to be screened is collected, and the integral of the product of the lateral error and time with respect to time is calculated to obtain the sixth calculation result.
[0056] Optionally, the formula for calculating the sixth result is as follows:
[0057]
[0058] Where F is the sixth calculation result.
[0059] In one possible implementation, after calculating the sixth calculation result corresponding to each set of adjustable gain parameters to be screened, the set of adjustable gain parameters to be screened corresponding to the minimum value among multiple sixth calculation results is selected as the set of adjustable gain parameters for controlling the steering angle of the front wheels of the vehicle.
[0060] For example, the lateral error of the simulated vehicle under the control of the adjustable gain parameter set to be screened includes: obtaining the path types contained in the simulation path, including straight lines, U-shaped curves, acute-angle curves, and obtuse-angle curves; and collecting the lateral error of the simulated vehicle under the control of the adjustable gain parameter set to be screened in each type of simulation path, for calculating the adjustable gain parameter set applicable to each path type.
[0061] Optionally, the simulation path is divided into multiple different types of paths. The lateral error of the simulated vehicle in each type of simulation path is collected under the control of the adjustable gain parameter group to be screened. Then, the sixth calculation result is calculated based on the lateral error corresponding to each type of simulation path. The adjustable gain parameter group suitable for each path type is selected in the same way.
[0062] In step 207, in response to the front wheel steering angle not being equal to the front wheel target steering angle, the domain controller adjusts the front wheel steering angle based on the front wheel target steering angle.
[0063] After calculating the target steering angle of the front wheels, the domain controller compares the steering angle of the front wheels with the target steering angle of the front wheels. If the steering angle of the front wheels is not equal to the target steering angle of the front wheels, the domain controller adjusts the steering angle of the front wheels based on the target steering angle of the front wheels. This includes the domain controller controlling the vehicle's steer-by-wire unit to adjust the steering angle of the front wheels to the target steering angle of the front wheels.
[0064] This application embodiment performs global planning on the planned journey based on the user-defined starting point and target endpoint, obtaining a globally planned driving path including multiple sampling points. It then acquires the coordinate data of each sampling point in a planar coordinate system for subsequent calculations. Combining the vehicle's speed, heading angle, yaw rate, front wheel steering angle, and the vehicle's coordinate data in a preset coordinate system, it calculates the heading angle error, yaw rate error, and lateral error. Furthermore, based on these errors, it calculates the target steering angle of the front wheels. If the front wheel steering angle is not equal to the target steering angle, it adjusts the front wheel steering angle accordingly. This technical solution enables control of vehicle path tracking while ensuring tracking accuracy and stability.
[0065] See Figure 4 This application provides a path tracking control device, which includes:
[0066] The receiving module 401 is used to receive the starting point and destination of the planned trip set by the user;
[0067] The generation module 402 is used to generate a globally planned driving path based on the starting point and the destination. The globally planned driving path includes multiple sampling points.
[0068] The first acquisition module 403 is used to acquire the coordinate data of each sampling point in a preset coordinate system, wherein the preset coordinate system is a planar coordinate system.
[0069] The second acquisition module 404 is used to acquire the vehicle's driving speed, heading angle, yaw rate, steering angle of the front wheels, and coordinate data of the vehicle in a preset coordinate system.
[0070] The first calculation module 405 is used to calculate the heading angle error, yaw rate error and lateral error based on the driving speed, heading angle, yaw rate and vehicle coordinate data in the preset coordinate system, combined with the coordinate data of the nearest sampling point in front of the vehicle in the preset coordinate system.
[0071] The second calculation module 406 is used to calculate the target steering angle of the front wheel based on the heading angle error, the yaw rate error and the lateral error;
[0072] The adjustment module 407 is used to adjust the steering angle of the front wheels based on the target steering angle of the front wheels in response to the front wheel steering angle not being equal to the target steering angle of the front wheels.
[0073] In one possible implementation, the second calculation module 406 is used to calculate the product of the heading angle error and the first adjustable gain parameter to obtain a first calculation result; calculate the product of the lateral error and the second adjustable gain parameter, divide it by the sum of the driving speed plus 1, to obtain a second calculation result; calculate the product of the third adjustable gain parameter and the arctangent function of the second calculation result to obtain a third calculation result; calculate the integral of the heading angle error with respect to time and multiply it by the product of the fourth adjustable gain parameter to obtain a fourth calculation result; calculate the error of the yaw rate and multiply it by the product of the fifth adjustable gain parameter to obtain a fifth calculation result; and calculate the sum of the first, third, fourth, and fifth calculation results as the target steering angle of the front wheels.
[0074] In one possible implementation, the second calculation module 406 is further configured to generate multiple sets of adjustable gain parameter sets to be screened based on the value range of each adjustable gain parameter; control the steering angle of the front wheels of the simulated vehicle corresponding to the vehicle based on the set of adjustable gain parameters to be screened; collect the lateral error of the simulated vehicle under the control of the set of adjustable gain parameters to be screened; calculate the integral of the product of the lateral error of the simulated vehicle and time with respect to time to obtain a sixth calculation result; and select the set of adjustable gain parameters to be screened corresponding to the minimum value in the sixth calculation result as the set of adjustable gain parameters for controlling the steering angle of the front wheels of the vehicle.
[0075] In one possible implementation, the second calculation module 406 is used to obtain the path types contained in the simulation path, including straight lines, U-shaped curves, acute-angle curves, and obtuse-angle curves; and to collect the lateral error of the simulated vehicle in each type of simulation path under the control of an adjustable gain parameter set to be screened, in order to calculate the adjustable gain parameter set applicable to each path type.
[0076] In one possible implementation, the first calculation module 405 is used to select the sampling point in front of the vehicle that is closest to the vehicle's current position; obtain the angle between the tangent direction of the path at the nearest sampling point and the coordinate axis, as the target heading angle; obtain the curvature of the path at the nearest sampling point; calculate the target yaw rate of the path at the sampling point based on the curvature and the driving speed; calculate the distance from the vehicle to the nearest sampling point, as the lateral error; calculate the difference between the heading angle and the target heading angle, as the heading angle error; and calculate the difference between the yaw rate and the target yaw rate, as the yaw rate error.
[0077] In one possible implementation, the first acquisition module 403 is used to acquire the longitude and latitude information of the sampling point; and to convert the longitude and latitude information into coordinate data of the sampling point in a preset coordinate system by projection.
[0078] This device performs global planning of the planned journey based on the user-defined starting point and target endpoint, obtaining a globally planned driving path including multiple sampling points. It then acquires the coordinate data of each sampling point in a planar coordinate system for subsequent calculations. Combining the vehicle's speed, heading angle, yaw rate, front wheel steering angle, and the vehicle's coordinate data in a preset coordinate system, it calculates the heading angle error, yaw rate error, and lateral error. Based on these errors, it calculates the target steering angle of the front wheels. If the front wheel steering angle is not equal to the target steering angle, it adjusts the front wheel steering angle accordingly. This technical solution enables control of vehicle path tracking while ensuring tracking accuracy and stability.
[0079] It should be noted that the apparatus provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.
[0080] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one computer program that is loaded and executed by a processor of a computer device to enable the computer to implement any of the path tracking control methods described above.
[0081] In one possible implementation, the aforementioned computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.
[0082] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform any of the path tracing control methods described above.
[0083] It should be noted that all information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this application are authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the starting point and target endpoint of the planned trip, the globally planned driving path, the vehicle's speed, heading angle, yaw rate, front wheel steering angle, the vehicle's coordinate data in the preset coordinate system, heading angle error, yaw rate error, lateral error, and the target steering angle of the front wheels involved in this application were all obtained with full authorization.
[0084] It should be understood that "multiple" as used in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0085] It should be noted that the terms "first," "second," etc. (if applicable) in the specification and claims of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0086] The above description is merely an exemplary embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.
Claims
1. A path tracking control method, characterized in that, The method includes: Receive the starting point and destination of the planned trip set by the user; A globally planned driving path is generated based on the driving start point and the target end point, and the globally planned driving path includes multiple sampling points; Obtain the coordinate data of each sampling point in a preset coordinate system, wherein the preset coordinate system is a planar coordinate system; Acquire the vehicle's speed, heading angle, yaw rate, front wheel steering angle, and the vehicle's coordinates in the preset coordinate system; Based on the driving speed, the heading angle, the yaw rate, and the vehicle's coordinate data in the preset coordinate system, combined with the coordinate data of the nearest sampling point in front of the vehicle in the preset coordinate system, the heading angle error, yaw rate error, and lateral error are calculated. The target steering angle of the front wheels is calculated based on the heading angle error, the yaw rate error, and the lateral error. In response to the fact that the steering angle of the front wheel is not equal to the target steering angle of the front wheel, the steering angle of the front wheel is adjusted based on the target steering angle of the front wheel.
2. The method according to claim 1, characterized in that, The calculation of the target steering angle of the front wheels based on the heading angle error, the yaw rate error, and the lateral error includes: Calculate the product of the heading angle error and the first adjustable gain parameter to obtain the first calculation result; Calculate the product of the lateral error and the second adjustable gain parameter, divide it by the sum of the driving speed plus 1, and obtain the second calculation result; The third calculation result is obtained by multiplying the third adjustable gain parameter by the arctangent function of the second calculation result. The integral of the heading angle error with respect to time is calculated and then multiplied by the product of the fourth adjustable gain parameter to obtain the fourth calculation result; The error of the yaw rate is calculated and multiplied by the product of the fifth adjustable gain parameter to obtain the fifth calculation result; The sum of the first, third, fourth, and fifth calculation results is used as the target steering angle of the front wheels.
3. The method according to claim 2, characterized in that, Before calculating the target steering angle of the front wheels based on the heading angle error, the yaw rate error, and the lateral error, the method further includes: Multiple sets of adjustable gain parameters to be filtered are generated based on the value range of each adjustable gain parameter. The steering angle of the front wheels of the simulated vehicle corresponding to the vehicle is controlled based on the set of adjustable gain parameters to be screened. The lateral error of the simulated vehicle is collected under the control of the adjustable gain parameter set to be screened. The sixth calculation result is obtained by integrating the product of the lateral error of the simulated vehicle and time with respect to time. The adjustable gain parameter set corresponding to the minimum value in the sixth calculation result is selected as the adjustable gain parameter set for controlling the steering angle of the front wheels of the vehicle.
4. The method according to claim 3, characterized in that, The acquisition of the lateral error of the simulated vehicle under the control of the adjustable gain parameter set to be screened includes: Obtain the path types included in the simulation path, where the path types include straight lines, U-shaped paths, acute-angle curves, and obtuse-angle curves; The lateral error of the simulated vehicle under the control of the adjustable gain parameter set to be screened is collected in each type of simulation path, and used to calculate the adjustable gain parameter set applicable to each path type.
5. The method according to claim 1, characterized in that, The calculation of heading angle error, yaw rate error, and lateral error based on the driving speed, heading angle, yaw rate, and vehicle coordinates in the preset coordinate system, combined with the coordinates of the nearest sampling point in front of the vehicle in the preset coordinate system, includes: Select the sampling point in front of the vehicle that is closest to the vehicle's current location; Obtain the angle between the tangent direction of the path at the nearest sampling point and the coordinate axis, and use it as the target heading angle; Obtain the curvature of the path at the nearest sampling point; Calculate the target yaw rate of the path at the sampling point based on the curvature and the driving speed; Calculate the distance from the vehicle to the nearest sampling point as the lateral error; Calculate the difference between the heading angle and the target heading angle, and use it as the heading angle error; The difference between the yaw rate and the target yaw rate is calculated as the error of the yaw rate.
6. The method according to claim 1, characterized in that, The step of obtaining the coordinate data of each sampling point in the preset coordinate system includes: Obtain the longitude and latitude information of the sampling points; The longitude and latitude information are converted into coordinate data of the sampling point in the preset coordinate system by projection.
7. A path tracking control device, characterized in that, The device includes: The receiving module is used to receive the starting point and destination of the planned trip set by the user. The generation module is used to generate a globally planned driving path based on the driving start point and the target end point, wherein the globally planned driving path includes multiple sampling points; The first acquisition module is used to acquire the coordinate data of each sampling point in a preset coordinate system, wherein the preset coordinate system is a planar coordinate system. The second acquisition module is used to acquire the vehicle's driving speed, heading angle, yaw rate, steering angle of the front wheels, and coordinate data of the vehicle in the preset coordinate system. The first calculation module is used to calculate the heading angle error, yaw rate error and lateral error based on the driving speed, the heading angle, the yaw rate and the vehicle's coordinate data in the preset coordinate system, combined with the coordinate data of the nearest sampling point in front of the vehicle in the preset coordinate system. The second calculation module is used to calculate the target steering angle of the front wheel based on the heading angle error, the yaw rate error, and the lateral error; An adjustment module is used to adjust the steering angle of the front wheel based on the target steering angle of the front wheel in response to the front wheel's steering angle not being equal to the target steering angle of the front wheel.
8. The apparatus according to claim 7, characterized in that, The second calculation module is used to calculate the product of the heading angle error and the first adjustable gain parameter to obtain a first calculation result; calculate the product of the lateral error and the second adjustable gain parameter, divide it by the sum of the travel speed plus 1, and obtain a second calculation result; The product of the third adjustable gain parameter and the arctangent function of the second calculation result is calculated to obtain the third calculation result; the integral of the heading angle error with respect to time is calculated and then multiplied by the product of the fourth adjustable gain parameter to obtain the fourth calculation result. The error of the yaw rate is calculated and multiplied by the product of the fifth adjustable gain parameter to obtain the fifth calculation result; The sum of the first, third, fourth, and fifth calculation results is used as the target steering angle of the front wheels.
9. A computer program product comprising computer instructions that, when executed by a processor, implement the steps of the path tracing control method as described in any one of claims 1 to 6.
10. A non-transitory computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which is loaded and executed by a processor to implement the path tracking control method as described in any one of claims 1 to 6.