Vehicle control system and method, electronic equipment and medium

Abstract

The invention provides a vehicle control system and method, electronic equipment and a medium, and relates to the technical field of vehicles. The vehicle control system comprises a vehicle transverse control module and a vehicle longitudinal control module. Wherein the vehicle transverse control module comprises a first wheel steering angle control module, and the vehicle longitudinal control module comprises a speed tracking control module and an acceleration compensation module. The first wheel steering angle control module obtains a first wheel steering angle control amount of the first vehicle based on the path tracking control problem, wherein the first wheel is a front wheel or a rear wheel; the speed tracking control module obtains the expected acceleration of the first vehicle based on the speed tracking control problem; the acceleration compensation module obtains the acceleration control quantity of the first vehicle according to the actual acceleration and / or the vehicle running resistance of the first vehicle and the expected acceleration of the first vehicle. The control performance and robustness of vehicle control can be considered.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle control system, method, electronic equipment and medium. Background Art

[0002] The control performance and robustness of vehicle control are both important factors that affect the vehicle control effect. For example, the unknown longitudinal force induced by the vehicle's wheel steering angle affects the vehicle's longitudinal control performance. Therefore, it is necessary to take into account both control performance and robustness in the process of designing vehicle control. Summary of the invention

[0003] The embodiments of the present application provide a vehicle control system, method, electronic device and medium, which can take into account both the control performance and robustness of vehicle control.

[0004] In a first aspect, an embodiment of the present application provides a vehicle control system, comprising: a vehicle lateral control module and a vehicle longitudinal control module; wherein the vehicle lateral control module comprises a first wheel steering angle control module, and the vehicle longitudinal control module comprises a speed tracking control module and an acceleration compensation module; the first wheel steering angle control module is used to solve a nonlinear unconstrained optimization problem based on a minimum principle in a loop iteration to obtain a first wheel steering angle control amount of a first vehicle, wherein the first wheel is one of a front wheel and a rear wheel; wherein the nonlinear unconstrained optimization problem is obtained by transforming a path tracking control problem for tracking a planned path using an obstacle function method and a Lagrange multiplier method, wherein the planned path includes a reference posture at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle; a speed tracking control module is used to solve a speed tracking control problem for tracking a planned speed to obtain an expected acceleration of the first vehicle; wherein the planned speed includes a reference speed at a series of future time points; an acceleration compensation module is used to obtain an acceleration control amount of the first vehicle according to at least one of an actual acceleration of the first vehicle and a vehicle driving resistance of the first vehicle, and according to the expected acceleration of the first vehicle.

[0005] In the embodiment of the present application, the first wheel steering angle control module and the speed tracking control module are independent of the vehicle chassis interface, and the control performance requirements are met by the designed high-performance control law to achieve precise control of path tracking and speed tracking, while the acceleration compensation module depends on the vehicle chassis interface, and the requirements for resisting unknown interference are met by the designed strong robustness control law to ensure the robustness of vehicle control, so that the vehicle control system can take into account both control performance and robustness.

[0006] The embodiments of the present application decouple lateral control and longitudinal control through a layered architecture, decouple the two control quantities of front wheel steering angle and rear wheel steering angle in vehicle lateral control, and decouple control performance and robustness indicators in vehicle longitudinal control, thereby making the vehicle control present high performance of "fast convergence, high precision and strong robustness".

[0007] Optionally, the vehicle lateral control module also includes a second wheel steering angle control module; the second wheel steering angle control module is used to obtain the second wheel steering angle control amount of the first vehicle based on the correlation relationship between the front wheel steering angle and the rear wheel steering angle of the first vehicle, and the first wheel steering angle control amount of the first vehicle, the second wheel being the other of the front wheel and the rear wheel; wherein the correlation relationship is obtained based on the maximum value of the front wheel steering angle of the first vehicle and the maximum value of the rear wheel steering angle of the first vehicle.

[0008] The second wheel steering angle control module relies on the vehicle chassis interface and meets the requirements of resisting unknown interference through the designed strong robust control law to ensure the robustness of the vehicle's lateral control.

[0009] Optionally, a path tracking control problem is established based on the posture error of the first vehicle relative to a Frenet coordinate system, and the origin of the Frenet coordinate system is on the planned path; the path tracking control problem is used to solve the first wheel steering angle control quantity that satisfies the lateral control constraint and makes the first function take a minimum value; wherein the first function includes a path tracking error optimization term and a smoothing control quantity optimization term, the path tracking error optimization term is obtained based on the posture error between the vehicle trajectory and the planned path, and the smoothing control quantity optimization term is obtained based on the error of the first wheel steering angle of the vehicle at adjacent moments.

[0010] In this way, the vehicle can accurately track the planned path and ensure the stability of the vehicle's lateral control.

[0011] Optionally, any solution result includes a state quantity reflecting the posture error and a control quantity reflecting the steering angle of the first wheel at a series of future time points; the nonlinear unconstrained optimization problem is solved iteratively based on the minimum principle to obtain the control quantity of the first wheel steering angle of the first vehicle, including: if there is a solution result of the previous cycle, then based on the solution result of the previous cycle, the nonlinear unconstrained optimization problem is iteratively solved to obtain the solution result of the current cycle; if both the inner loop condition and the outer loop condition are met, then according to the control quantity obtained in the current cycle, the control quantity of the first wheel steering angle of the first vehicle is obtained; wherein, the inner loop condition includes that the error between the state quantities obtained in the previous and current cycles is not greater than a set error threshold, and the outer loop condition includes that the value of the first parameter in the nonlinear unconstrained optimization problem reaches a set number threshold; if the inner loop condition is not met, the step of solving the nonlinear unconstrained optimization problem is executed again; if the inner loop condition is met and the outer loop condition is not met, the value of the first parameter is increased, and the step of solving the nonlinear unconstrained optimization problem is executed again.

[0012] This helps ensure the accuracy of the vehicle's lateral control and supports the vehicle's tracking of planned paths.

[0013] Optionally, the speed tracking control problem is obtained according to the longitudinal control model, which includes the relationship between the desired acceleration of the vehicle, the actual acceleration of the vehicle and the parameters of the first-order inertia link; the speed tracking control problem is used to solve the desired acceleration that satisfies the longitudinal control constraints and makes the second function take a minimum value; wherein the second function includes a speed tracking error, and the speed tracking error is used to describe the error between the reference speed and the vehicle speed predicted according to the desired acceleration.

[0014] By establishing the speed tracking control problem based on the longitudinal response delay characteristics of the vehicle and reducing the error between the reference speed and the predicted actual vehicle speed, accurate tracking of the vehicle in the longitudinal direction can be ensured.

[0015] Optionally, solving a speed tracking control problem for tracking the planned speed includes: iteratively constructing a third function at a series of future time points from back to front in chronological order according to the speed tracking control problem; obtaining the expected acceleration at each time point by minimizing the third function at each time point, and the expected acceleration of the first vehicle is the expected acceleration at the next time point obtained; wherein the third function at any time point is obtained based on the speed tracking error and the expected acceleration at that time point, and the speed tracking error at the next time point; the speed tracking error at any time point is used to describe the error between the reference speed at that time point and the vehicle speed predicted based on the expected acceleration at the previous time point.

[0016] By using the reinforcement learning framework to iteratively solve the velocity tracking control problem to obtain the desired acceleration, the desired acceleration can be accurately obtained.

[0017] Optionally, the vehicle driving resistance includes at least one of wheel steering angle resistance, ramp resistance and tire rolling resistance; the wheel steering angle resistance is obtained based on the first wheel steering angle control value of the first vehicle, the equivalent longitudinal force of the first axle and the equivalent lateral force of the first axle, wherein the equivalent longitudinal force of the first axle and the equivalent lateral force of the first axle are both obtained based on the first wheel steering angle control value of the first vehicle and the speed of the first vehicle; the ramp resistance is obtained based on the gravity of the first vehicle and the slope of the ground where the first vehicle is located; the tire rolling resistance is obtained based on the gravity, the slope and a set tire rolling resistance coefficient.

[0018] This can achieve an accurate estimation of the vehicle's driving resistance, thereby helping to improve the accuracy of the vehicle's longitudinal tracking.

[0019] In a second aspect, an embodiment of the present application provides a vehicle control method, comprising: iteratively solving a nonlinear unconstrained optimization problem based on the minimum principle to obtain a first wheel steering angle control value of a first vehicle, wherein the first wheel is one of a front wheel and a rear wheel; wherein the nonlinear unconstrained optimization problem is obtained by transforming a path tracking control problem for tracking a planned path using an obstacle function method and a Lagrange multiplier method, and the planned path includes a reference posture at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle; solving a speed tracking control problem for tracking a planned speed to obtain an expected acceleration of the first vehicle; wherein the planned speed includes a reference speed at a series of future time points; obtaining an acceleration control value of the first vehicle based on at least one of an actual acceleration of the first vehicle and a vehicle driving resistance of the first vehicle, and based on the expected acceleration of the first vehicle.

[0020] In a third aspect, an embodiment of the present application provides an electronic chip, comprising: a processor, which is used to execute computer program instructions stored in a memory, wherein when the computer program instructions are executed by the processor, the electronic chip is triggered to execute any method as in the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides an electronic device, comprising at least one processor, wherein the processor and a memory are coupled, the memory is used to store computer program instructions, and the processor is used to execute the computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to execute a method as described in any one of the first aspects.

[0022] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program runs on a computer, the computer executes any method in the first aspect.

[0023] In a sixth aspect, an embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is run on a computer, the computer executes any method in the first aspect.

[0024] The technical effects of the aforementioned aspects can be referenced to each other and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments are briefly introduced below.

[0026] Figure 1 A block diagram of a vehicle control system provided in an embodiment of the present application;

[0027] Figure 2 A block diagram of another vehicle control system provided in an embodiment of the present application;

[0028] Figure 3 A schematic diagram reflecting a vehicle kinematic model provided in an embodiment of the present application;

[0029] Figure 4 A schematic diagram reflecting a path tracking error model provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram reflecting the path tracking control problem provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram reflecting the wheel steering angle resistance provided in an embodiment of the present application;

[0032] Figure 7 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to better understand the technical solution of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0034] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0035] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0036] It should be understood that the term "at least one" used in this article refers to one or more, and "plurality" refers to two or more. The term "and / or" used in this article is merely a description of 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. Among them, A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b and c can be represented by: a, b, c, ab, ac, bc, or abc, wherein a, b, c can be single or multiple.

[0037] It should be understood that, although the terms first, second, etc. may be used to describe the set thresholds in the embodiments of the present application, these set thresholds should not be limited to these terms. These terms are only used to distinguish the set thresholds from each other. For example, without departing from the scope of the embodiments of the present application, the first set threshold may also be referred to as the second set threshold, and similarly, the second set threshold may also be referred to as the first set threshold.

[0038] refer to Figure 1 An embodiment of the present application provides a vehicle control system for controlling a vehicle 100, in which a lateral control and a longitudinal control are decoupled, and a longitudinal control module includes an outer-loop longitudinal control module 101 and an inner-loop longitudinal control module 102, and a lateral control module includes a top-level lateral control module 103 and a bottom-level lateral distribution module 104. The inner-loop longitudinal control module 102 includes a feedforward control module 1021 and a feedback control module 1022.

[0039] Exemplarily, the vehicle 100 may be a four-wheel steering vehicle, a front-wheel steering vehicle, a rear-wheel steering vehicle, a steer-by-wire vehicle, or a non-steer-by-wire vehicle. Taking a front-wheel steering vehicle as an example, compared to a front-wheel steering vehicle (with the front wheels as driving wheels), a four-wheel steering vehicle can synchronously control the front and rear wheels to achieve steering action by adding rear wheel steering angle control, thereby improving the maneuverability of the vehicle during parking and driving. For example, a four-wheel steering vehicle can more easily complete parking operations in a narrow environment.

[0040] Figure 1The vehicle control system shown is designed based on a layered architecture, so that the lateral and longitudinal controls are decoupled, the front and rear wheel controls in the lateral control are decoupled, and the control performance and robustness indicators in the longitudinal control are decoupled.

[0041] Figure 1 In the vehicle control system shown, the top-level lateral control module 103 solves the front wheel steering angle control quantity that can realize path tracking control based on the planned path; the bottom-level lateral allocation module 104 solves the rear wheel steering angle control quantity based on the front wheel steering angle control quantity output by the top-level lateral control module 103 and the correlation between the front and rear wheel steering angles.

[0042] The planned path can include the reference lateral position y of the vehicle at a series of future time points ref and the reference heading angle By controlling the steering angles of the front and rear wheels of the vehicle, lateral control of the vehicle can be achieved.

[0043] In one implementation, the top-level lateral control module 103 may calculate and output a desired front wheel steering angle based on a planned path tracking error (such as a lateral position error and a heading angle error).

[0044] The top-level lateral control module 103 is independent of the vehicle chassis interface and meets the control performance requirements by designing high-performance control laws to ensure the lateral control performance of the vehicle. The bottom-level lateral distribution module 104 depends on the vehicle chassis interface and meets the requirements of resisting unknown interference by designing strong robustness control laws to ensure the robustness of the vehicle lateral control.

[0045] Figure 1 In the vehicle control system shown in FIG. 1 , the outer loop longitudinal control module 101 solves the expected acceleration a that can achieve speed tracking control based on the planned speed. c The inner longitudinal control module 102 performs acceleration compensation based on the expected acceleration output by the outer longitudinal control module 101, the actual acceleration of the vehicle (which can be obtained based on the vehicle speed collected by the vehicle sensor) and the vehicle driving resistance, and obtains the acceleration control amount through acceleration error and driving resistance interference.

[0046] Among them, the feedback control module 1022 can obtain the acceleration error according to the expected acceleration and the actual acceleration, and use the acceleration error as the disturbance feedback amount; the feedforward control module 1021 can estimate the vehicle driving resistance in real time, and use the estimated vehicle driving resistance as the disturbance feedforward amount. Based on the disturbance feedback amount and the disturbance feedforward amount, the expected acceleration can be subjected to disturbance compensation processing to obtain the acceleration control amount that can cope with the disturbance.

[0047] The planned speed can include the reference speed v of the vehicle at a series of future time points refBy controlling the acceleration of the vehicle, longitudinal control of the vehicle can be achieved.

[0048] The outer-loop longitudinal control module 101 is independent of the vehicle chassis interface and meets the control performance requirements by designing a high-performance control law to ensure the longitudinal control performance of the vehicle, while the inner-loop longitudinal control module 102 depends on the vehicle chassis interface and meets the anti-unknown interference requirements by designing a strong robustness control law to ensure the robustness of the vehicle longitudinal control.

[0049] The vehicle control system can achieve driving control of the vehicle by decoupling the vehicle's lateral and longitudinal directions.

[0050] in this way, Figure 1 The vehicle control system shown may have at least the following features:

[0051] (1) The outer-loop longitudinal control module and the top-level lateral control module are independent of the vehicle chassis interface. The high-performance control law is designed to meet the control performance requirements to achieve precise control of path tracking and speed tracking. The inner-loop longitudinal control module and the bottom-level lateral distribution module rely on the vehicle chassis interface. The strong robustness control law is designed to meet the requirements of anti-unknown interference to ensure the robustness of vehicle control. In this way, the vehicle control system can take into account both control performance and robustness.

[0052] (2) By decoupling lateral control and longitudinal control through a hierarchical architecture, and decoupling the two control variables of the front wheel steering angle and the rear wheel steering angle in the vehicle lateral control, and decoupling the control performance and robustness indicators in the vehicle longitudinal control, the vehicle control presents a high performance of "fast convergence, high accuracy and strong robustness".

[0053] (3) Through the lateral and longitudinal decoupling design, the influence of the unknown longitudinal force induced by the two control variables of the front wheel steering angle and the rear wheel steering angle on the longitudinal control performance of the vehicle can be effectively suppressed, so that the longitudinal control of the vehicle can take into account both the control performance and the robustness requirements.

[0054] (4) Through layered architecture design, the vehicle control requirements of “easy to implement, easy to maintain, easy to expand and easy to upgrade” are met.

[0055] (5) The vehicle control system has the characteristic of backward compatibility, that is, it can be applied not only to the vehicle control of four-wheel steering vehicles, but also to the vehicle control of front-wheel steering vehicles. Therefore, it can serve as the basis for creating a "high-performance, platform-based, and vehicle-type decoupled" general vehicle control architecture.

[0056] (6) Figure 1When the vehicle control system shown is applied to the parking scenario of a four-wheel steering vehicle, the four-wheel steering vehicle can synchronously control the front and rear wheels to achieve steering action based on the vehicle control system, and can achieve precise tracking and control of the parking planning path, so that the four-wheel steering vehicle has better maneuverability and flexibility during parking, and it is easier to complete parking operations in narrow spaces.

[0057] refer to Figure 2 An embodiment of the present application provides a vehicle control system 200, which includes: a vehicle lateral control module 210 and a vehicle longitudinal control module 220; wherein the vehicle lateral control module 210 includes a first wheel steering angle control module 211, and the vehicle longitudinal control module 220 includes a speed tracking control module 221 and an acceleration compensation module 222.

[0058] The vehicle control system 200 is applicable to vehicle control scenarios such as parking scenarios and driving scenarios. During the parking process, the vehicle is in a low-speed and large-angle motion state, and the vehicle control system 200 supports the vehicle to achieve accurate and stable parking in the parking scenario.

[0059] The vehicle control system 200 is applicable to vehicles such as front-wheel steering vehicles, rear-wheel steering vehicles, and four-wheel steering vehicles. When the vehicle control system 200 is used to control a front-wheel steering vehicle, the first wheel is the front wheel, and when the vehicle control system 200 is used to control a rear-wheel steering vehicle, the first wheel is the rear wheel. When the vehicle control system 200 is used to control a four-wheel steering vehicle, the first wheel may be the front wheel.

[0060] In the vehicle control system 200, the first wheel steering angle control module 211 solves the nonlinear unconstrained optimization problem iteratively based on the minimum principle to obtain the first wheel steering angle control value of the first vehicle (the controlled vehicle), where the first wheel is one of the front wheel and the rear wheel.

[0061] Among them, the nonlinear unconstrained optimization problem is obtained by transforming the path tracking control problem for tracking the planned path using the obstacle function method and the Lagrange multiplier method. The planned path includes a reference posture at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle.

[0062] The parking path tracking control problem solver constructed by integrating the obstacle function method, Lagrange multiplier method and minimum principle can have high computational efficiency, which can improve the accuracy of vehicle lateral control by reducing the top-level lateral control calculation cycle.

[0063] In one embodiment, the first wheel steering angle control module 211 may be the top-level lateral control module 103 .

[0064] The path tracking control problem is preferably used to track the planned path by controlling the first wheel steering angle of the first vehicle. The first wheel steering angle of the first vehicle may be controlled according to the first wheel steering angle control amount obtained by solving the path tracking control problem.

[0065] In one embodiment, the constraint conditions of the path tracking control problem can be obtained based on the vehicle control dynamics model, the maximum / minimum value of the wheel steering angle, etc.

[0066] Taking the first wheel as the front wheel as an example, in one embodiment, based on the nonlinear unconstrained optimization problem obtained by converting the path tracking control problem, the nonlinear unconstrained optimization problem can be solved repeatedly to obtain the front wheel steering angle control amount that meets the path tracking requirement. The path tracking requirement can be that the gap between the predicted trajectory and the planned path meets the requirement (i.e., the vehicle is controlled to travel along the planned path in the lateral direction), and the predicted trajectory is the vehicle's driving trajectory predicted in the future when the vehicle is controlled by the solved front wheel steering angle control amount.

[0067] If the front wheel steering angle obtained in the current cycle does not meet the path tracking requirement, the next loop solution of the nonlinear unconstrained optimization problem can be performed based on the front wheel steering angle obtained in the current cycle, so that as the number of loop solutions increases, the front wheel steering angle control amount obtained by the solution can be more likely to meet the path tracking requirement. In this way, the nonlinear unconstrained optimization problem can be solved repeatedly until the front wheel steering angle that meets the path tracking requirement is solved, and this is used as the front wheel steering angle control amount to control the front wheel steering angle of the vehicle to perform lateral control on the vehicle.

[0068] The reference posture in the planned path may include a reference lateral position and / or a reference heading angle. By solving the front wheel steering angle based on the reference lateral position and / or the reference heading angle, and using the solved front wheel steering angle to control the vehicle, the lateral control effect of the vehicle tracking the planned path can be achieved.

[0069] The planned path may include reference postures at a series of future time points, such as reference postures at steps 0 to N. The state of the vehicle at the next moment can be predicted based on the state of the vehicle at the current moment (such as posture) and control quantity (such as front wheel steering angle). In this way, the state and control quantity at steps 0 to N can be predicted in sequence through iterative solution in any loop solution process, and the predicted series of state quantities can reflect the above-mentioned predicted trajectory.

[0070] In the vehicle control system 200, the speed tracking control module 221 solves a speed tracking control problem for tracking a planned speed to obtain a desired acceleration of the first vehicle; wherein the planned speed includes reference speeds at a series of future time points.

[0071] In one embodiment, the speed tracking control module 221 may be the outer loop longitudinal control module 101 described above.

[0072] The speed tracking control problem is preferably used to track the planned speed by controlling the acceleration of the first vehicle. The acceleration of the first vehicle can be controlled according to the desired acceleration obtained by solving the speed tracking control problem after acceleration disturbance compensation.

[0073] In one embodiment, the constraint conditions of the speed tracking control problem can be obtained according to a vehicle longitudinal control model, etc.

[0074] In the vehicle control system 200, the acceleration compensation module 222 obtains the acceleration control amount of the first vehicle according to at least one of the actual acceleration of the first vehicle and the vehicle driving resistance of the first vehicle, and according to the expected acceleration of the first vehicle.

[0075] The vehicle longitudinal control module may control the acceleration of the first vehicle according to the acquired acceleration control amount.

[0076] In one embodiment, the acceleration compensation module 222 may be the inner loop longitudinal control module 102 described above.

[0077] The acceleration compensation module 222 can estimate the vehicle driving resistance, which is an interference factor, in real time through the feedforward control module 1021. By combining the vehicle driving resistance to obtain the acceleration control amount, the influence of the vehicle driving resistance on the robustness of the vehicle longitudinal control can be optimized.

[0078] The acceleration compensation module 222 can obtain the acceleration error interference factor according to the reference acceleration and the actual acceleration of the vehicle through the feedback control module 1022. By combining the acceleration error to obtain the acceleration control amount, the influence of the acceleration error on the robustness of the longitudinal control of the vehicle can be optimized.

[0079] By performing acceleration compensation according to interference factors such as acceleration error and vehicle driving resistance, an acceleration control amount that meets the speed tracking requirement can be obtained. The speed tracking requirement can be that the difference between the predicted speed and the planned speed meets the requirement (i.e., the vehicle is controlled to travel at the planned speed in the longitudinal direction), and the predicted speed is the vehicle's driving speed predicted in the future when the vehicle is controlled by the obtained acceleration control amount.

[0080] Since the acceleration control amount obtained after compensation eliminates the influence of interference factors on the longitudinal control of the vehicle, compared with the reference acceleration, the acceleration control amount can better meet the speed tracking requirements and ensure the longitudinal control effect of the vehicle.

[0081] In order to make the vehicle control system 200 not only applicable to four-wheel steering vehicles, but also backward compatible to be applicable to front-wheel or rear-wheel steering vehicles, in one embodiment of the present application, reference Figure 2 The vehicle lateral control module 210 also includes a second wheel steering angle control module 212; the second wheel steering angle control module 212 obtains the second wheel steering angle control amount of the first vehicle according to the correlation between the front wheel steering angle and the rear wheel steering angle of the first vehicle, and the first wheel steering angle control amount of the first vehicle, and the second wheel is the other of the front wheel and the rear wheel; wherein the correlation is obtained according to the maximum value of the front wheel steering angle of the first vehicle and the maximum value of the rear wheel steering angle of the first vehicle.

[0082] The second wheel steering angle of the first vehicle may be controlled according to the obtained second wheel steering angle control amount.

[0083] In one embodiment, the second wheel steering angle control module 212 may be the bottom-level lateral distribution module 104 .

[0084] After the top-level lateral control module obtains the front wheel steering angle control value, the bottom-level lateral distribution module can calculate and output the rear wheel steering angle control value based on it, thereby realizing the perfect decoupling control of the front wheel steering angle and the rear wheel steering angle of the four-wheel steering vehicle.

[0085] The second wheel steering angle control module relies on the vehicle chassis interface and meets the requirements of resisting unknown interference through the designed strong robust control law to ensure the robustness of the vehicle's lateral control.

[0086] Taking a front-wheel steering vehicle as an example, compared with a front-wheel steering vehicle, the additional rear-wheel steering angle control of a four-wheel steering vehicle causes the instantaneous steering center of the vehicle to change in real time, making it difficult to select a vehicle reference point for vehicle lateral control. However, the embodiment of the present application achieves perfect decoupling of the two control quantities of the front-wheel steering angle and the rear-wheel steering angle of a four-wheel steering vehicle by decoupling the parking lateral control into a top-level lateral control and a bottom-level lateral distribution module, and fixes the vehicle reference point.

[0087] The allocation strategy of the two control quantities of the front wheel steering angle and the rear wheel steering angle of a four-wheel steering vehicle is an important factor affecting the vehicle's lateral control performance index, and the complex nonlinear relationship between the two control quantities of the front wheel steering angle and the rear wheel steering angle and the lateral movement of the four-wheel steering vehicle poses a great challenge to the formulation of the allocation strategy of the two control quantities. However, this application can achieve a reasonable allocation of the front and rear wheel steering angle control quantities and improve the lateral control accuracy by decoupling the front and rear wheel steering angles and combining the correlation between the front and rear wheel steering angles.

[0088] refer to Figure 3The schematic diagram of the vehicle kinematic model reflecting the four-wheel steering vehicle 301 is shown. In order to make the closed-loop control effect of the front and rear wheel steering angles of the four-wheel steering vehicle more human-like, safe and comfortable, in one embodiment, the rear wheel steering angle δ r With the front wheel steering angle δ f The following formula (1) is satisfied.

[0089] L f tanδ r =L r tanδ f (1)

[0090] In formula (1), L f and L r They are the distances from point P on a four-wheel steering vehicle to the front and rear axles of the vehicle, respectively.

[0091] In formula (1),

[0092] Among them, the maximum values ​​of the front and rear wheel steering angles of the four-wheel steering vehicle are δ fmax and δ rmax , L is the wheelbase of the four-wheel steering vehicle.

[0093] It can be seen from formula (1) that the bottom-level lateral distribution module can calculate and output the rear wheel steering angle control amount based on the front wheel steering angle control amount output by the top-level lateral control module by comprehensively considering the maximum value constraints of the front and rear wheel steering angles of the four-wheel steering vehicle.

[0094] Exemplarily, the correlation between the front and rear wheel steering angles of the first vehicle can be expressed as formula (1). By substituting the first wheel steering angle control value output by the first wheel steering angle control module 211 into formula (1), the second wheel steering angle control value of the first vehicle can be obtained.

[0095] In one embodiment of the present application, a path tracking control problem is established based on the posture error of the first vehicle relative to the Frenet coordinate system, and the origin of the Frenet coordinate system is on the planned path; the path tracking control problem is used to solve the first wheel steering angle control amount that satisfies the lateral control constraint and makes the first function take the minimum value; wherein the first function includes a path tracking error optimization term and a smoothing control amount optimization term, the path tracking error optimization term is obtained based on the posture error between the vehicle trajectory and the planned path, and the smoothing control amount optimization term is obtained based on the error of the first wheel steering angle of the vehicle at adjacent moments.

[0096] The path tracking control problem is used to solve the first wheel steering angle control value, and the path tracking control problem including the first wheel steering angle control value can be established based on the Frenet coordinate system. The lateral and longitudinal directions described in this embodiment can be lateral and longitudinal directions based on the Frenet coordinate system.

[0097] The posture error may include the error between the actual lateral position of the vehicle and the reference lateral position, and the error between the actual heading angle of the vehicle and the reference heading angle. In the process of iteratively solving the nonlinear unconstrained optimization problem, the actual lateral position of the vehicle at a future time may be the predicted result of the lateral position of the vehicle, and the actual heading angle of the vehicle at a future time may be the predicted result of the heading angle of the vehicle.

[0098] In one embodiment, the lateral control constraint condition may be obtained based on a vehicle control dynamics model, a maximum / minimum value of a wheel steering angle, and the like.

[0099] By making the first function include a path tracking error optimization term and solving the wheel steering angle control amount when the first function takes the minimum value, the error between the vehicle trajectory and the planned path can be reduced. By making the first function include a smoothing control amount optimization term and solving the wheel steering angle control amount when the first function takes the minimum value, the stability of the vehicle's lateral control can be ensured.

[0100] In one embodiment of the present application, any solution result includes a state quantity reflecting the posture error and a control quantity reflecting the first wheel steering angle at a series of future time points. Based on this, the step of obtaining the first wheel steering angle control quantity of the first vehicle by iteratively solving the nonlinear unconstrained optimization problem based on the minimum principle may include:

[0101] If there is a solution result of the previous cycle, the nonlinear unconstrained optimization problem is iteratively solved based on the solution result of the previous cycle to obtain the solution result of the current cycle; if both the inner loop condition and the outer loop condition are met, the first wheel steering angle control quantity of the first vehicle is obtained according to the control quantity obtained in the current cycle; wherein, the inner loop condition includes that the error between the state quantities obtained in the previous and current cycles is not greater than a set error threshold, and the outer loop condition includes that the value of the first parameter in the nonlinear unconstrained optimization problem reaches a set number threshold.

[0102] Since there is no solution result of the previous cycle in the first loop solution process, the first loop solution process can be performed based on the preset initial information, and then another loop solution is performed based on the solution result of the previous cycle (that is, the k+1th loop solution is performed based on the solution result of the kth cycle).

[0103] The cyclic solution of nonlinear unconstrained optimization problems can be achieved by combining the inner loop with the outer loop.

[0104] In any outer loop solution process, the inner loop solution process can be executed multiple times in a loop until the inner loop solution result satisfies the inner loop condition, the current outer loop solution process is terminated, and it is determined whether to execute the next outer loop solution process. After executing the outer loop solution process for a set number of times, the first wheel steering angle control amount of the first vehicle is obtained with the final solution result (i.e., the solution result of the last inner loop process in the last outer loop solution process).

[0105] In one embodiment, the error threshold may be set to a set minimum value, such as 10 -3 , so that the inner loop is stopped when the difference between the solution results of two adjacent inner loops is extremely small. At this time, the solution result reaches the optimal inner loop in the current outer loop solution process.

[0106] In one embodiment of the present application, if the inner loop condition is not met, the step of solving the nonlinear unconstrained optimization problem is performed again, that is, the inner loop solution process is performed again. Each inner loop solution process is performed based on the solution result of the previous loop, so that as the number of inner loops increases, the solution result of the inner loop gradually tends to the optimal solution result in the current outer loop solution process.

[0107] In one embodiment of the present application, if the inner loop condition is met and the outer loop condition is not met, the value of the first parameter is increased, and the step of solving the nonlinear unconstrained optimization problem is executed again, that is, the outer loop solution process is executed again.

[0108] Since the solution result of each outer loop solution process will reach the optimal solution result of the current outer loop solution process after the inner loop solution process is executed multiple times, the local optimal limit can be jumped out by changing the value of the first parameter to support the effectiveness of the next outer loop solution process, so that the global optimal solution result can be obtained after multiple outer loop solution processes. This helps to ensure the accuracy of the vehicle's lateral control and supports the vehicle to follow the planned path.

[0109] The following takes the case where the first wheel is the front wheel, the vehicle is a four-wheel steering vehicle, and the planned path is a planned parking path as an example to illustrate a feasible implementation process of the first wheel steering angle control module 211 solving the front wheel steering angle control value. The relevant technical implementation is also applicable to embodiments where the first wheel is a rear wheel, a front-wheel or rear-wheel steering vehicle, and the planned path is a planned driving path.

[0110] refer to Figure 3 , point P on the four-wheel steering vehicle can be used as a reference point to model the path tracking error. Figure 4 As shown, the lateral error E of a point P on the four-wheel steering vehicle 401 relative to the projection point on the parking path 402 can be defined as y and heading angle error E ψ They are equation (2) and equation (3) respectively.

[0111]

[0112] E ψ =ψ-ψ σ (3)

[0113] In equations (2) and (3), (X, Y, ψ) is the position of point P on the four-wheel steering vehicle in the fixed coordinate system OXY, (X σ , Y σ , ψ σ ) is the position and posture of the projection point on the parking path in the fixed coordinate system OXY.

[0114] The lateral velocity of the vehicle can be considered as v y If is zero, then the lateral error E of point P on the four-wheel steering vehicle relative to the projection point on the parking path is y (or lateral position error) and heading angle error E ψ Taking the derivative, we can get the following equations (4) and (5).

[0115]

[0116]

[0117] In formula (4), v x is the longitudinal speed of a four-wheel steering vehicle.

[0118] According to the instantaneous center of velocity theorem, the following equation (6) can be obtained.

[0119]

[0120] In the formula, ρ σ is the curvature radius of the parking path at the projection point, is the velocity of the projection point on the parking path generated by the four-wheel steering vehicle moving along the parking path, v σ is the longitudinal speed v of the four-wheel steering vehicle x Projected speed in the tangent direction of the parking path, radius of curvature ρ σ Characterizing the inherent geometric properties of the parking path, the longitudinal velocity v of the four-wheel steering vehicle x It represents the actual motion state of the four-wheel steering vehicle along the parking path. From formula (6), we can know that the two can deduce the instantaneous change rate of the heading angle of the parking path at the projection point based on the instantaneous center of velocity theorem:

[0121] By rearranging equation (6), we can obtain that the velocity of the projection point on the parking path generated by the four-wheel steering vehicle moving along the parking path is The expression of is formula (7).

[0122]

[0123] In formula (7), k s is the curvature of the parking path at the projection point, which can be expressed as k s =1 / ρ σ .

[0124] Define the state vector as ζ = [E y E ψ ] T , by the chain rule, we can get equation (8).

[0125]

[0126] Based on the chain derivation result of formula (8), combined with formula (4), (5), and (7), we can get formula (9) and formula (10).

[0127]

[0128]

[0129] In formula (10), k v is the curvature of the actual driving path of the four-wheel steering vehicle, which can be expressed as:

[0130] According to the inherent properties of the steering mechanism of a four-wheel steering vehicle, the curvature k of the actual driving path of the four-wheel steering vehicle is v satisfy:

[0131] Define the parameterized state vector as ζ(s) = [E y (s) E ψ (s)] T , the control quantity is k v Based on the above derivation, the parameterized state equation can be obtained as follows (11).

[0132]

[0133] From formula (11), we can know that the lateral error E of point P on the four-wheel steering vehicle relative to the projection point on the parking path is y and heading angle error E ψ After parameterization, the dynamic characteristics of the two are independent of the longitudinal speed v of the four-wheel steering vehicle xdynamic characteristics and allows control of the system when the vehicle is parked.

[0134] like Figure 5 As shown, the Euclidean distance Δs between adjacent projection points on the parking path 502 and the curvature k at the projection point are used. s Characterizing the geometric characteristics of the parking path, and establishing a series of Frenet coordinate systems with the projection point on the parking path as the origin, it can be seen that the parameterized state equation of formula (11) describes the dynamic posture information of the four-wheel steering vehicle relative to the Frenet coordinate system. Therefore, the parking path tracking control problem can be established as formula (12).

[0135] J error +J smooth +ηα T a

[0136]

[0137] In formula (12), J error and J smooth are the parking path tracking error optimization term and the smoothing control quantity optimization term, respectively. A and B are the discretization coefficient matrices of the parameterized state equation, and are the relaxation vector and weight coefficient. α and η are the upper boundaries of the relaxation vector elements, respectively. and are the lower and upper boundaries of the lateral error of point P on the four-wheel steering vehicle relative to the projection point on the parking path, E ymin and E ψmin are the lower and upper bounds of the heading angle error of point P on the four-wheel steering vehicle relative to the projection point on the parking path, s k is the path length at the kth step.

[0138] Among them, J error and J smooth , A, B and α can be expressed as:

[0139]

[0140]

[0141]

[0142]

[0143]

[0144] Among them, γ1, γ2 and γ3 are weight coefficients.

[0145] In one embodiment, the path tracking control problem may be the parking path tracking control problem of equation (12), and the first function may be J in equation (12): error +J smooth +ηα T a, the first function includes the path tracking error optimization term J error And the smoothing control quantity optimization term J smooth , path tracking error optimization term J error According to the position error between the vehicle trajectory and the planned path (lateral error E y and heading angle error E ψ ) to obtain the smoothing control optimization term J smooth According to the first wheel steering angle of the vehicle at adjacent moments The error is obtained.

[0146] In this way, by solving the first wheel steering angle control amount that satisfies the lateral control constraint condition (i.e., the equality constraint and inequality constraint in the above equation (12)) and makes the first function take the minimum value, the path tracking error optimization term J can be obtained. error Small, smooth control quantity optimization term J smooth Smaller. Based on the smaller smoothing control amount, the optimization term J smooth , which can reduce the error between the vehicle trajectory and the planned path, and support the vehicle to accurately track the planned path. smooth , which can ensure the stability of the vehicle's lateral control.

[0147] After obtaining the parking path tracking control problem of the above formula (12), the lateral error and heading angle error of the point P on the four-wheel steering vehicle relative to the projection point on the parking path can be obtained by solving formula (12). Furthermore, the position and posture of the point P on the four-wheel steering vehicle in the fixed coordinate system OXY can be obtained through coordinate transformation (see the following formula (13)).

[0148]

[0149] Let x k =[E y (s k )E ψ (s k )] T 、u k =k v (s k ), then the parking path tracking control problem described by equation (12) can be abstracted into the following nonlinear constrained optimization problem (see equation (14) below).

[0150]

[0151] See the following equations (15) and (16), the inequality constraint in equation (14) is expressed using the following obstacle function.

[0152] b k (x k )=-log(-g k (x k ))k=0,1,...,N (15)

[0153] d k (u k )=-log(-h k (u k ))k=0,1,...,N-1 (16)

[0154] When the inequality in equation (14) satisfies the constraint, the function values ​​of equations (15) and (16) are 0; when the inequality in equation (14) does not satisfy the constraint, the function values ​​of equations (15) and (16) are positive infinity. Therefore, using equations (15) and (16), the nonlinear constrained optimization problem described in equation (14) can be transformed into the nonlinear constrained optimization problem described in equation (17).

[0155]

[0156] In formula (17), t is a parameter whose value increases gradually with the number of cycles of the outer loop.

[0157] Furthermore, the nonlinear constrained optimization problem described by equation (17) is abbreviated as equation (18).

[0158]

[0159] In formula (18), φ N (x N )=tc N (x N )+b N (x N ),

[0160] The Lagrange multiplier method can be used to transform the nonlinear constrained optimization problem described by equation (18) into the nonlinear unconstrained optimization problem described by equation (19).

[0161]

[0162] In formula (19), λ k+1 is the Lagrange multiplier.

[0163] based on and For φ in formula (19), N (xN )、L k (x k ) and M k (u k )exist Performing a second-order Taylor expansion in the domain, we can obtain the following equations (20) to (22).

[0164]

[0165]

[0166]

[0167] in, Indicates that the x obtained in the previous loop N , Indicates that the x obtained in the previous loop k , Indicates that u is obtained in the previous cycle k .

[0168] based on and For f in formula (19), k (x k ,u k )exist Performing a first-order Taylor expansion in the domain, we can obtain the following formula (23).

[0169]

[0170] Substituting equations (20) to (23) into equation (19), we can obtain the unconstrained quadratic optimization problem described by equation (24).

[0171]

[0172] Formula (24) is an unconstrained quadratic optimization problem, and its local optimal solution is also the global optimal solution. Taking the partial derivative of formula (24), we can get the following formula (25).

[0173]

[0174] Furthermore, based on formula (25), formula (26) can be obtained.

[0175]

[0176] Assume λ k With δx k The following equation (27) is satisfied.

[0177] λ k =P kδx k +υ k (27)

[0178] In formula (27), P k is the gain coefficient, υ k is the coefficient of variation.

[0179] From the fourth sub-formula in formula (26), we can see that P N and N They can be expressed as formula (28) and formula (29) respectively.

[0180]

[0181]

[0182] Furthermore, according to formula (27), we can get formula (30).

[0183] λ k+1 =P k+1 δx k+1 +υ k+1 (30)

[0184] Substituting equation (27) and equation (30) into the first sub-equation in equation (26), we can obtain equation (31).

[0185]

[0186] Further rearrangement of formula (31) yields formula (32).

[0187]

[0188] Substituting equation (30) into the second sub-equation in equation (26), we can obtain equation (33).

[0189]

[0190] Substituting equation (33) into the third sub-equation in equation (26), we can obtain equation (34).

[0191]

[0192] Substituting equation (32) into equation (34), we can obtain equation (35).

[0193]

[0194] From formula (35), we can get formula (36).

[0195]

[0196] Further rearrangement of equation (36) yields equations (37) and (38).

[0197]

[0198]

[0199] Based on the above content, the solution steps of the parking path tracking control problem may include the following steps 1.1 to 1.7:

[0200] Step 1.1, initialize the solver parameters.

[0201] Step 1.2, based on the solution result of the previous cycle Construct the nonlinear constrained optimization problem of equation (18).

[0202] Step 1.3, using equations (28) and (29) as initial conditions, use equations (36) and (37) to iteratively calculate the gain coefficient P from back to front (i.e., from the k+1th step to the kth step): k and coefficient of deviation υ k That is, P1, P2, ..., P N andυ1,υ2,...,υ N .

[0203] Step 1.4, use formula (33) to iteratively calculate δu from the front to the back (i.e. from the kth step to the k+1th step) k , and according to Calculate u for the current loop k .

[0204] See formula (33), the gain coefficient P k and coefficient of deviation υ k To calculate δu k The intermediate variables to be used.

[0205] Step 1.5, calculate δx using the third subformula in equation (26): k , and according to Calculate x for the current loop k .

[0206] After calculating uk and xk of the current loop, the solution result of the current loop (x k , x N ,u k ) can be used according to the solution result (x k , x N ,u k )right Update so that when step 1.2 is executed again, according to the solution result (xk , x N ,u k ) constructs the nonlinear constrained optimization problem of formula (18) and then proceeds to the next cycle solution.

[0207] Step 1.6, if δx k Satisfy the inner loop stopping criteria (such as |δx k |≤10 -3 ), then jump to step 1.7; if δx k If the inner loop stopping criteria are not met, jump to step 1.2 to perform another inner loop solution.

[0208] Step 1.7, if t (see formula (17)) satisfies the outer loop stopping criterion (for example, t ≥ 100), the solution ends; if t does not satisfy the outer loop stopping criterion, t increases by 1 and jumps to step 1.2 to perform another outer loop solution.

[0209] After the solution is completed, the front wheel steering angle control value can be obtained based on the latest solution result.

[0210] In one embodiment, any solution result obtained by the first wheel steering angle control module 211 through cyclically solving the nonlinear unconstrained optimization problem includes a state quantity x used to reflect the posture error. k =[E y (s k ) E ψ (s k )] T and the control amount u used to reflect the first wheel steering angle k =k v (s k ), the first parameter may be t in formula (17), the inner loop condition may be an inner loop stop criterion, and the outer loop condition may be an outer loop stop criterion.

[0211] In one embodiment of the present application, a speed tracking control problem is obtained based on a longitudinal control model, which includes a desired acceleration of the vehicle, an actual acceleration of the vehicle, and a correlation relationship between first-order inertia link parameters; the speed tracking control problem is used to solve the desired acceleration that satisfies the longitudinal control constraints and makes the second function take a minimum value; wherein the second function includes a speed tracking error, which is used to describe the error between a reference speed and a vehicle speed predicted based on the desired acceleration.

[0212] The first-order inertia link can be used to approximate the longitudinal response characteristics of the four-wheel steering vehicle, and the longitudinal control model of the four-wheel steering vehicle can be constructed accordingly. By establishing the speed tracking control problem based on the longitudinal response delay characteristics of the vehicle, the expected acceleration can be accurately obtained.

[0213] In one embodiment, the longitudinal control constraint condition may be obtained based on a vehicle longitudinal control model or the like.

[0214] By making the second function include the speed tracking error and solving the expected acceleration when the second function takes the minimum value, the error between the reference speed and the predicted actual speed of the vehicle can be reduced to ensure accurate tracking of the vehicle in the longitudinal direction. In the process of iteratively solving the speed tracking control problem, the actual speed of the vehicle at the future moment can be the predicted result of the vehicle speed.

[0215] In one embodiment of the present application, solving a speed tracking control problem for tracking a planned speed includes: iteratively constructing a third function at a series of future time points from the time sequence, from the back to the front (i.e., from the k+1th step to the kth step), according to the speed tracking control problem; obtaining an expected acceleration at each time point by minimizing the third function at each time point, and the expected acceleration of the first vehicle is the expected acceleration at the next time point obtained.

[0216] Among them, the third function at any time point is obtained according to the speed tracking error and the expected acceleration at that time point, and the speed tracking error at the next time point; the speed tracking error at any time point is used to describe the error between the reference speed at that time point and the vehicle speed predicted according to the expected acceleration at the previous time point.

[0217] By making the third function include the speed tracking error at the current moment and the next moment, and solving the expected acceleration when the third function takes the minimum value, the error between the reference speed and the predicted actual speed of the vehicle can be reduced, and the third function can be iteratively constructed from back to front, thereby iteratively calculating the expected acceleration at each time point.

[0218] The speed tracking control module 221 establishes a speed tracking control problem based on the longitudinal response delay characteristics of the vehicle, and uses a reinforcement learning framework to iteratively solve the speed tracking control problem to obtain the desired acceleration, thereby accurately obtaining the desired acceleration.

[0219] The following takes the case where the vehicle is a four-wheel steering vehicle and the planned path is a planned parking path as an example to illustrate a feasible implementation process of the speed tracking control module 221 solving the expected acceleration. The relevant technical implementation is also applicable to embodiments where the vehicle is a front-wheel or rear-wheel steering vehicle and the planned path is a planned driving path.

[0220] The first-order inertia link is used to approximate the longitudinal response characteristics of the four-wheel steering vehicle, and the nominal model of the outer loop longitudinal control of the four-wheel steering vehicle parking can be expressed as formula (38).

[0221]

[0222] In formula (38), v and a are the actual speed and actual acceleration of the four-wheel steering vehicle respectively; a c is the expected acceleration of the four-wheel steering vehicle; τ is the first-order inertia link parameter.

[0223] Define the system state vector and control vector as x k =[v k ,a k ] T and u k =[a c ] T , assuming the sampling period is T, then equation (38) can be discretized into equation (39).

[0224] x k+1 =A k x k +B k u k (39)

[0225] In formula (39), the coefficient matrix A k Expressed as B k Expressed as

[0226] The goal of the outer-loop longitudinal control of a four-wheel steering vehicle parking is to make the vehicle speed quickly, accurately and stably track the parking reference speed while satisfying the control constraints. Therefore, a constrained optimization problem such as equation (40) can be defined to describe the outer-loop longitudinal control of a four-wheel steering vehicle parking.

[0227]

[0228] For the constrained optimization problem described by equation (40), the value function of the Nth step is equation (41).

[0229]

[0230] The action-value function of step N-1 is formula (42).

[0231]

[0232] Using x N =A N-1 x N-1 +B N-1 u N-1 The action-value function of step N-1 can be transformed into equation (43).

[0233]

[0234] By minimizing the action-value function described by equation (43), the control law for the N-1th step can be obtained as equation (44).

[0235]

[0236] Substituting equation (44) into equation (43), we can get the value function of the N-1th step as V(x N-1 ), and use the patterns described by equations (41) and (42) to construct the action-value function Q(x) of step N-2 N-2 ,u N-2 ), minimize Q(x N-2 ,u N-2 ) Get the control law u of step N-2 N-2 . Continuing in this way, we can iterate from back to front to obtain the control law, value function and action-value function of each step.

[0237] Based on the above content, the steps for solving the parking outer ring longitudinal control problem of a four-wheel steering vehicle may include the following steps 2.1 to 2.3:

[0238] Step 2.1, initialize the solver parameters.

[0239] Step 2.2, iteratively calculate the control law u for each step from back to front k .

[0240] Step 2.3, the control law at the next moment calculated iteratively is used as the calculation output of the parking outer loop longitudinal control.

[0241] Among them, u k =[a c ] T , then the desired acceleration can be obtained according to the control quantity.

[0242] In one embodiment, the speed tracking control problem solved by the speed tracking control module 221 may be equation (40), and the third function may be equation (42).

[0243] In one embodiment of the present application, the vehicle driving resistance includes at least one of wheel steering angle resistance, ramp resistance and tire rolling resistance. In this way, accurate estimation of the vehicle driving resistance can be achieved, thereby helping to improve the accuracy of vehicle longitudinal tracking.

[0244] In one embodiment, the acceleration compensation module 222 may be the inner longitudinal control module 102 mentioned above. The inner longitudinal control module 102 may estimate the wheel steering angle resistance, ramp resistance and tire rolling resistance in real time online, and calculate the vehicle driving resistance in combination with formula (45).

[0245] F x =F δ+F θ +F r (45)

[0246] Among them, F x 、F δ 、F θ and F r They are vehicle driving resistance, wheel steering angle resistance, ramp resistance and tire rolling resistance.

[0247] Feasibly, the wheel steering angle resistance is obtained based on the first wheel steering angle control amount of the first vehicle, the first wheel axle equivalent longitudinal force and the first wheel axle equivalent lateral force, wherein the first wheel axle equivalent longitudinal force and the first wheel axle equivalent lateral force are both obtained based on the first wheel steering angle control amount of the first vehicle and the speed of the first vehicle.

[0248] In one embodiment, reference Figure 6 The wheel steering angle resistance F can be calculated according to formula (46) δ .

[0249] F δ =F x1 cosδ f -F y1 sinδ f +F x2 cosδ r +F y2 sinδ r (46)

[0250] In formula (46), F x1 and F y1 is the front axle equivalent longitudinal force and front axle equivalent lateral force of the vehicle; F x2 and F y2 is the equivalent longitudinal force and lateral force on the rear axle of the vehicle.

[0251] In a feasible implementation, the vehicle speed and the wheel steering angle are used as inputs, and the equivalent longitudinal force and the equivalent lateral force of the front / rear axle are obtained by looking up a table.

[0252] Optionally, the hill resistance is obtained according to the gravity of the first vehicle and the slope of the ground on which the first vehicle is located.

[0253] In one embodiment, the ramp resistance F can be calculated according to formula (47): θ .

[0254] F θ =mgsinθ (47)

[0255] In formula (47), m is the mass of the vehicle, g is the acceleration due to gravity, and θ is the slope of the ground where the vehicle is located.

[0256] Preferably, the tire rolling resistance is obtained according to gravity, slope and a set tire rolling resistance coefficient.

[0257] In one embodiment, the tire rolling resistance F can be calculated according to formula (48): r .

[0258] F r =ξmgcosθ (48)

[0259] In formula (48), ξ is the tire rolling resistance coefficient.

[0260] An embodiment of the present application provides a vehicle control method, which may include the following steps: iteratively solving a nonlinear unconstrained optimization problem based on the minimum principle to obtain a first wheel steering angle control value of a first vehicle, where the first wheel is one of a front wheel and a rear wheel; wherein the nonlinear unconstrained optimization problem is obtained by transforming a path tracking control problem for tracking a planned path using an obstacle function method and a Lagrange multiplier method, and the planned path includes a reference posture at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle; solving a speed tracking control problem for tracking a planned speed to obtain an expected acceleration of the first vehicle; wherein the planned speed includes a reference speed at a series of future time points; obtaining an acceleration control value of the first vehicle based on at least one of an actual acceleration of the first vehicle and a vehicle driving resistance of the first vehicle, and based on the expected acceleration of the first vehicle.

[0261] An embodiment of the present application provides an electronic chip, including: a processor, which is used to execute computer program instructions stored in a memory, wherein when the computer program instructions are executed by the processor, the electronic chip is triggered to execute the method described in any embodiment of the present application.

[0262] An embodiment of the present application provides an electronic device, which includes at least one processor, the processor and a memory are coupled, the memory is used to store computer program instructions, and the processor is used to execute the computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to execute the method described in any embodiment of the present application.

[0263] An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer executes the method described in any embodiment of the present application.

[0264] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program runs on a computer, the computer executes the method described in any embodiment of the present application.

[0265] Figure 7 A schematic diagram of a computer device provided in one embodiment of the present application. Figure 7 As shown, the computer device 20 of this embodiment includes: a processor 21 and a memory 22, the memory 22 is used to store a computer program 23 that can be run on the processor 21, and the computer program 23 is executed by the processor 21 to implement the steps in the method embodiment of the present application. To avoid repetition, they are not described one by one here. Alternatively, when the computer program 23 is executed by the processor 21, the functions of each model / unit in the device embodiment of the present application are implemented. To avoid repetition, they are not described one by one here.

[0266] The computer device 20 includes but is not limited to a processor 21 and a memory 22. Those skilled in the art will appreciate that Figure 7 It is only an example of the computer device 20 and does not constitute a limitation of the computer device 20. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0267] The processor 21 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may be any conventional processor, etc.

[0268] The memory 22 may be an internal storage unit of the computer device 20, such as a hard disk or memory of the computer device 20. The memory 22 may also be an external storage device of the computer device 20, such as a plug-in hard disk, a Smart Media (SM) card, a Secure Digital (SD) card, a Flash Card, etc. equipped on the computer device 20. Further, the memory 22 may also include both an internal storage unit of the computer device 20 and an external storage device. The memory 22 is used to store the computer program 23 and other programs and data required by the computer device. The memory 22 may also be used to temporarily store data that has been output or is to be output.

[0269] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0270] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0271] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0272] The integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (Processor) to perform some steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program code.

[0273] In the embodiments of the present application, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, method, commodity or device including the element.

[0274] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0275] Those skilled in the art will appreciate that the various units and algorithm steps described in the embodiments of the present application can be implemented by a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0276] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the same or similar parts between the various embodiments in this application can be referred to each other. For example, the specific working process of the system, device and unit described in the embodiments of this application can refer to the corresponding process in the method embodiment of this application, and will not be repeated here.

[0277] The above description is only a specific embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A vehicle control system, characterized in that: include: A vehicle lateral control module and a vehicle longitudinal control module; Wherein, the vehicle lateral control module includes a first wheel steering angle control module, and the vehicle longitudinal control module includes a speed tracking control module and an acceleration compensation module; The first wheel steering angle control module is used to solve the nonlinear unconstrained optimization problem based on the minimum principle in a loop iteration to obtain the first wheel steering angle control value of the first vehicle, wherein the first wheel is one of the front wheel and the rear wheel; wherein the nonlinear unconstrained optimization problem is obtained by transforming the path tracking control problem for tracking the planned path using the barrier function method and the Lagrange multiplier method, wherein the planned path includes reference postures at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle; The speed tracking control module is used to solve the speed tracking control problem for tracking the planned speed to obtain the expected acceleration of the first vehicle; wherein the planned speed includes reference speeds at a series of future time points; The acceleration compensation module is used to obtain the acceleration control amount of the first vehicle according to at least one of the actual acceleration of the first vehicle and the vehicle driving resistance of the first vehicle, and according to the expected acceleration of the first vehicle.

2. The vehicle control system according to claim 1, characterized in that: The vehicle lateral control module also includes a second wheel steering angle control module; The second wheel steering angle control module is used to obtain a second wheel steering angle control amount of the first vehicle according to the correlation between the front wheel steering angle and the rear wheel steering angle of the first vehicle and the first wheel steering angle control amount of the first vehicle, wherein the second wheel is the other of the front wheel and the rear wheel; The association relationship is obtained according to a maximum value of a front wheel steering angle of the first vehicle and a maximum value of a rear wheel steering angle of the first vehicle.

3. The vehicle control system according to claim 1 or 2, characterized in that: The path tracking control problem is established based on the posture error of the first vehicle relative to the Frenet coordinate system, and the origin of the Frenet coordinate system is on the planned path; The path tracking control problem is used to solve the first wheel steering angle control amount when the lateral control constraint condition is satisfied and the first function takes the minimum value; Among them, the first function includes a path tracking error optimization term and a smoothing control amount optimization term, the path tracking error optimization term is obtained according to the posture error between the vehicle trajectory and the planned path, and the smoothing control amount optimization term is obtained according to the error of the first wheel steering angle of the vehicle at adjacent moments.

4. The vehicle control system according to claim 1 or 2, characterized in that: Any solution result includes a state quantity reflecting the posture error and a control quantity reflecting the steering angle of the first wheel at a series of future time points; The method of solving the nonlinear unconstrained optimization problem by cyclic iteration based on the minimum principle to obtain the first wheel steering angle control value of the first vehicle includes: If there is a solution result of the previous cycle, then based on the solution result of the previous cycle, the nonlinear unconstrained optimization problem is iteratively solved to obtain a solution result of the current cycle; If both the inner loop condition and the outer loop condition are satisfied, the first wheel steering angle control amount of the first vehicle is obtained according to the control amount obtained in the current loop; wherein the inner loop condition includes that the error between the state amounts obtained in the previous loop and the current loop is not greater than a set error threshold, and the outer loop condition includes that the value of the first parameter in the nonlinear unconstrained optimization problem reaches a set number of times threshold; If the inner loop condition is not met, the step of solving the nonlinear unconstrained optimization problem is performed again; If the inner loop condition is met and the outer loop condition is not met, the value of the first parameter is increased, and the step of solving the nonlinear unconstrained optimization problem is performed again.

5. The vehicle control system according to claim 1 or 2, characterized in that: The speed tracking control problem is obtained according to a longitudinal control model, wherein the longitudinal control model includes a correlation relationship between a desired acceleration of the vehicle, an actual acceleration of the vehicle and a first-order inertia link parameter; The speed tracking control problem is used to solve the desired acceleration that satisfies the longitudinal control constraint and makes the second function take the minimum value; The second function includes a speed tracking error, and the speed tracking error is used to describe the error between the reference speed and the vehicle speed predicted according to the expected acceleration.

6. The vehicle control system according to claim 1 or 2, characterized in that: The solution to the speed tracking control problem for tracking the planned speed includes: According to the speed tracking control problem, iteratively construct the third function at a series of future time points from the latter to the former in chronological order; Obtaining the expected acceleration at each time point by minimizing the third function at each time point, wherein the expected acceleration of the first vehicle is the expected acceleration at the next time point obtained; Among them, the third function at any time point is obtained according to the speed tracking error and the expected acceleration at that time point, and the speed tracking error at the next time point; the speed tracking error at any time point is used to describe the error between the reference speed at that time point and the vehicle speed predicted according to the expected acceleration at the previous time point.

7. The vehicle control system according to claim 1 or 2, characterized in that: The vehicle running resistance includes at least one of wheel steering angle resistance, slope resistance and tire rolling resistance; The wheel steering angle resistance is obtained according to a first wheel steering angle control amount, a first wheel axle equivalent longitudinal force and a first wheel axle equivalent lateral force of the first vehicle, wherein the first wheel axle equivalent longitudinal force and the first wheel axle equivalent lateral force are both obtained according to the first wheel steering angle control amount of the first vehicle and the speed of the first vehicle; The slope resistance is obtained according to the gravity of the first vehicle and the slope of the ground where the first vehicle is located; The tire rolling resistance is obtained according to the gravity, the slope and a set tire rolling resistance coefficient.

8. A vehicle control method, characterized in that: include: A nonlinear unconstrained optimization problem is solved iteratively based on the minimum principle to obtain a first wheel steering angle control value of the first vehicle, where the first wheel is one of the front wheel and the rear wheel; wherein the nonlinear unconstrained optimization problem is obtained by transforming a path tracking control problem for tracking a planned path using an obstacle function method and a Lagrange multiplier method, where the planned path includes reference postures at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle; Solving a speed tracking control problem for tracking a planned speed to obtain a desired acceleration of the first vehicle; wherein the planned speed includes reference speeds at a series of future time points; An acceleration control amount of the first vehicle is obtained based on at least one of an actual acceleration of the first vehicle and a vehicle travel resistance of the first vehicle, and based on a desired acceleration of the first vehicle.

9. An electronic device, characterized in that: The electronic device comprises at least one processor, the processor is coupled to a memory, the memory is used to store computer program instructions, and the processor is used to execute the computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to execute the method as claimed in claim 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is run on a computer, the computer is caused to execute the method according to claim 8.

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