Vehicle control method, vehicle, device and program product

Abstract

The invention relates to the technical field of vehicles, in particular to a vehicle control method, a vehicle, equipment and a program product. The method comprises the following steps: acquiring a first steering angle predicted based on preview foresight duration in a trajectory tracking process of a vehicle; acquiring an actual transverse position error when the vehicle runs for the preview foresight duration; adjusting the first steering angle based on the actual transverse position error to obtain a second steering angle; and executing a trajectory tracking strategy configured by the vehicle based on the second steering angle to control the vehicle to run. According to the invention, the real-time performance of path tracking can be ensured, the path tracking control precision is improved, and the path tracking effect is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle control method, a vehicle, a device and a program product. Background Art

[0002] With the development of autonomous driving technology, the requirements for vehicle path tracking are increasing. At present, some path tracking control methods need to rely on many driving parameters of the vehicle to achieve high-precision tracking, and the control response becomes a limiting factor. For example, based on the vehicle prediction model, lateral displacement deviation and other errors, a fuzzy controller is used to track the vehicle trajectory path. However, the processing logic of multiple driving parameters and complex models is more complicated, which leads to lag in the vehicle path tracking process and poor path tracking effect. There are also some path tracking control methods that use solutions with better real-time performance. For example, based on the preview compensator, the track winding acceleration of the tracked vehicle is calculated according to parameters such as lateral error and heading error to adjust the tracked vehicle. However, the existing control methods with high real-time performance cannot guarantee the accuracy of path tracking, and the path tracking effect is also poor. Summary of the invention

[0003] Based on the above-mentioned defects and shortcomings of the prior art, the present application proposes a vehicle control method, vehicle, equipment and program product, which can improve the path tracking control accuracy while ensuring the real-time performance of path tracking, thereby improving the path tracking effect.

[0004] According to a first aspect of the present application, a vehicle control method is provided, including: obtaining a first steering angle predicted based on a preview forward vision duration during a trajectory tracking process of the vehicle; obtaining an actual lateral position error of the vehicle when traveling for the preview forward vision duration; adjusting the first steering angle based on the actual lateral position error to obtain a second steering angle; and executing a trajectory tracking strategy configured for the vehicle based on the second steering angle to control the driving of the vehicle.

[0005] According to the vehicle control method provided in the first aspect of the present application, the method of obtaining the first steering angle obtained by the vehicle during trajectory tracking based on the preview forward vision time prediction includes: obtaining the predicted lateral position error obtained by the vehicle during trajectory tracking based on the preview forward vision time prediction, and obtaining the curvature of the centerline of the trajectory of the vehicle based on the preview forward vision time; based on the predicted lateral position error and the curvature, obtaining the first steering angle.

[0006] According to the vehicle control method provided in the first aspect of the present application, the method of obtaining the predicted lateral position error of the vehicle obtained based on the preview forward vision duration during trajectory tracking includes: obtaining the center line of the trajectory of the vehicle; obtaining the predicted vehicle position of the vehicle based on the preview forward vision duration based on the trajectory tracking preview forward vision duration and the motion information of the vehicle; and obtaining the predicted lateral position error corresponding to the predicted vehicle position based on the predicted vehicle position and the center line of the trajectory.

[0007] According to the vehicle control method provided in the first aspect of the present application, the method of obtaining the curvature of the center line of the trajectory of the vehicle based on the preview-aim-forward viewing time includes: calculating the curvature of the trajectory center line corresponding to the preview-aim-forward viewing time based on the preview-aim-forward viewing time, the trajectory center line and the motion information of the vehicle.

[0008] According to the vehicle control method provided in the first aspect of the present application, obtaining the center line of the trajectory of the vehicle includes: identifying the lane lines in the road where the vehicle is located, and obtaining the center line of the trajectory based on the lane lines; or, obtaining the traveled path information of the vehicle, obtaining a planned path based on the traveled path information, and obtaining the center line of the trajectory based on the planned path.

[0009] According to the vehicle control method provided in the first aspect of the present application, the step of obtaining the actual lateral position error of the vehicle when it travels the preview-aim forward viewing time includes: obtaining the center line of the trajectory of the vehicle; obtaining the actual vehicle position of the vehicle when it travels the preview-aim forward viewing time; and obtaining the actual lateral position error based on the center line of the trajectory and the actual vehicle position.

[0010] According to the vehicle control method provided in the first aspect of the present application, the actual lateral position error is obtained based on the trajectory centerline and the actual vehicle position, including: calculating the initial lateral position error between the vehicle and the trajectory centerline based on the trajectory centerline and the actual vehicle position; if the initial lateral position error is greater than or equal to an error threshold, determining the initial lateral position error to be the actual lateral position error.

[0011] According to a second aspect of the present application, a vehicle is provided, the vehicle comprising a trajectory tracking module, the trajectory tracking module being configured with a trajectory tracking strategy; the vehicle driving is controlled by executing the trajectory tracking strategy through the vehicle control method as described in any one of the first aspects.

[0012] According to a third aspect of the present application, an electronic device is provided, comprising: a memory and a processor; the memory is connected to the processor and is used to store programs; the processor is used to implement the vehicle control method as described in the first aspect by running the program in the memory.

[0013] According to a fourth aspect of the present application, a computer program product is provided, comprising computer program instructions; when the computer program instructions are executed by a processor, the processor is caused to execute the vehicle control method as described in the first aspect. Optionally, the computer program may be stored in a readable storage medium of a computer device or in the cloud; the processor of the computer device reads the computer program from the readable storage medium or the cloud.

[0014] In the present application, the first steering angle of the vehicle is obtained based on the prediction of the preview forward-looking time during the trajectory tracking process; the actual lateral position error of the vehicle during the preview forward-looking time is obtained; the first steering angle is adjusted based on the actual lateral position error to obtain the second steering angle; the trajectory tracking strategy configured for the vehicle is executed based on the second steering angle to control the vehicle's travel. In the above process, the first steering angle obtained by preview is adopted to avoid the lag of path tracking and ensure the real-time performance of the vehicle's path tracking control. At the same time, compared with the method of pure preview calculation of trajectory tracking, the control accuracy of the vehicle's trajectory tracking can be further improved by adjusting the first steering angle based on the first steering angle using the actual lateral position error of the vehicle. Based on the above, the technical solution provided by the present application ensures both real-time performance and control accuracy during the vehicle trajectory tracking process, thereby improving the control effect of the vehicle trajectory tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0016] Figure 1 One of the flow charts of a vehicle control method provided in an embodiment of the present application;

[0017] Figure 2 A schematic diagram of a two-degree-of-freedom vehicle model provided in an embodiment of the present application;

[0018] Figure 3 A logical schematic diagram of a vehicle trajectory tracking simulation model based on a vehicle control method provided in an embodiment of the present application;

[0019] Figure 4A single preview control error experimental curve diagram provided in an embodiment of the present application;

[0020] Figure 5 A control error experimental curve diagram based on a vehicle control method provided in an embodiment of the present application;

[0021] Figure 6 A second flow chart of a vehicle control method provided in an embodiment of the present application;

[0022] Figure 7 A block diagram of a vehicle control device provided in an embodiment of the present application;

[0023] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0025] Exemplary Methods

[0026] In order to ensure the real-time performance and control accuracy of vehicle path tracking at the same time, the present application provides a vehicle control method, which can be implemented in the form of a software algorithm on any device with data processing capabilities, such as a vehicle's configured processor, a cloud processor, etc.

[0027] In one embodiment, if Figure 1 As shown, the process steps for implementing the vehicle control method include:

[0028] Step 101, obtaining a first steering angle predicted based on a preview look ahead duration during a trajectory tracking process of the vehicle.

[0029] In this embodiment, during the driving process, the vehicle can be abstracted as a two-degree-of-freedom vehicle model, such as Figure 2 The schematic diagram of the two-degree-of-freedom vehicle model is shown in Figure 1. Figure 2 In the XY coordinate system, δ f is the steering angle of the front wheels of the vehicle, δ r is the steering angle of the rear wheels of the vehicle; β f is the tire slip angle of the front wheel of the vehicle, β f for Figure 2 Medium Delta f With ξ f The angle betweenr is the tire slip angle of the rear wheel of the vehicle, β r for Figure 2 Medium Delta r With ξ r The angle between f is the angle between the velocity direction of the midpoint of the front axle of the vehicle and the X-axis, ξ r is the angle between the velocity direction of the midpoint of the rear axle of the vehicle and the X-axis; β is the sideslip angle of the vehicle at the center of mass; ω is the yaw angular velocity of the vehicle around the Z-axis; l f is the distance from the front axle to the center of mass of the vehicle, l r is the distance from the rear axle to the center of mass of the vehicle, F yr is the lateral force of the rear wheel of the vehicle, F yf is the lateral force of the front wheel of the vehicle; v x is the vehicle speed, v y is the lateral velocity generated by the centrifugal force caused by the vehicle turning, and v is v x With v y The combined speed.

[0030] According to the differential equation of vehicle motion, there is a relationship:

[0031]

[0032] Where m is the mass of the vehicle; M z I is the moment of rotation of the vehicle around the z-axis perpendicular to the ground; Z The moment of inertia of the vehicle rotating around the z-axis perpendicular to the ground;

[0033] Since the model is a linearized two-degree-of-freedom vehicle model, the vehicle tires are in the linear region, and the tire force can be obtained from the tire slip angle and cornering stiffness. Formula (1) can be rewritten as:

[0034]

[0035] Among them, k f is the cornering stiffness of the front vehicle tire, k f is the cornering stiffness of the rear vehicle tire; β f is the side slip angle of the front vehicle tire, β r is the side slip angle of the rear vehicle tire.

[0036] The formula for calculating tire slip angle is:

[0037]

[0038]

[0039] The cornering stiffness and the slip angle determine the size of the wheel lateral force. The tire lateral force calculation formula is:

[0040]

[0041]

[0042] Substituting into formula (2), the equation can be rewritten as the state equation:

[0043]

[0044] For the traditional two-degree-of-freedom vehicle model with only front-wheel steering, there is δ r =0, so the state equation of the two-degree-of-freedom vehicle model of the traditional vehicle is:

[0045]

[0046] By inputting the front wheel steering angle, the yaw rate and the sideslip angle of the center of mass can be calculated, which can provide reasonable control constraint values ​​for the subsequent control objective function.

[0047] In this embodiment, during the vehicle trajectory tracking process, the predicted vehicle position that the vehicle will reach at each future time step is predicted with the preview forward-looking time as a period, and each predicted position corresponds to a predicted front wheel steering angle of the vehicle, which is defined as a first steering angle.

[0048] Step 102, obtaining the actual lateral position error of the vehicle during the preview forward-looking period.

[0049] In this embodiment, as the vehicle continues to travel based on the preview process, the vehicle will pass through each time step based on the preview forward vision duration. When arriving at any time step, the actual lateral position error of the vehicle when it actually travels to each time step can be obtained based on the predicted vehicle position and the actual vehicle position obtained based on the previous prediction. The actual lateral error refers to the lateral error between the actual vehicle position and the predicted vehicle position at the same time step.

[0050] Step 103: Adjust the first steering angle based on the actual lateral position error to obtain a second steering angle.

[0051] In this embodiment, if the vehicle is controlled to perform trajectory tracking based only on the preview technology, the control accuracy will be low. Therefore, the predicted first steering angle is adjusted using the actual lateral position error of the vehicle, and the real-time position information of the vehicle's actual driving is integrated into the trajectory tracking process. This can effectively improve the vehicle's trajectory tracking control accuracy and avoid problems such as vehicle yaw.

[0052] In this embodiment, the specific process of adjusting the first steering angle based on the actual lateral position error can generate a smaller adjusted steering angle based on the actual lateral position error, and then obtain the second steering angle by calculating the adjusted steering angle and the first steering angle; the first steering angle can also be adaptively adjusted based on the actual lateral position error according to the trajectory tracking strategy actually configured by the vehicle.

[0053] Step 104 , executing a trajectory tracking strategy configured for the vehicle based on the second steering angle to control the driving of the vehicle.

[0054] In this embodiment, the second steering angle is the front wheel steering angle after fine adjustment using the actual lateral position error. The vehicle trajectory tracking process is controlled based on the second steering angle. This not only has simple adjustment logic and can ensure the real-time performance of trajectory tracking, but also can improve the control accuracy of trajectory tracking.

[0055] In one embodiment, obtaining a first steering angle obtained by predicting a preview look ahead time during a trajectory tracking process of a vehicle includes: obtaining a predicted lateral position error obtained by predicting a preview look ahead time during a trajectory tracking process of a vehicle, and obtaining a curvature of a centerline of a trajectory of the vehicle based on the preview look ahead time; obtaining the first steering angle based on the predicted lateral position error and the curvature.

[0056] In this embodiment, the predicted lateral position error refers to the lateral position error predicted based on each time step of the preview look ahead duration. Based on the trajectory centerline of the road where the vehicle is traveling, the curvature of the trajectory centerline at each time step based on the preview look ahead duration can be calculated.

[0057] In one embodiment, a predicted lateral position error of a vehicle obtained based on a preview look-ahead time prediction during trajectory tracking is obtained, including: obtaining a center line of the trajectory along which the vehicle is traveling; obtaining a predicted vehicle position based on the preview look-ahead time based on the trajectory tracking preview look-ahead time and the vehicle's motion information; and obtaining a predicted lateral position error corresponding to the predicted vehicle position based on the predicted vehicle position and the trajectory center line.

[0058] In this embodiment, the vehicle's motion information includes but is not limited to the vehicle's speed, acceleration, mass, and other information. After obtaining the preview look-ahead duration of trajectory tracking and the vehicle's motion information, the predicted lateral position error of the vehicle at each time step based on the preview look-ahead duration can be calculated based on kinematic knowledge. Each time step corresponds to a predicted vehicle position.

[0059] In one embodiment, obtaining the curvature of the center line of the vehicle's trajectory based on the preview look-ahead time includes: calculating the curvature corresponding to the preview look-ahead time of the center line of the trajectory based on the preview look-ahead time, the center line of the trajectory, and motion information of the vehicle.

[0060] In this embodiment, the vehicle's motion information includes but is not limited to the vehicle's speed, acceleration, mass and other information.

[0061] In one embodiment, obtaining the center line of the vehicle's travel trajectory includes: identifying lane lines in the road where the vehicle is located, and obtaining the center line of the trajectory based on the lane lines; or obtaining information about a path that the vehicle has traveled, obtaining a planned path based on the traveled path information, and obtaining the center line of the trajectory based on the planned path.

[0062] In this embodiment, there are two main situations when a vehicle is traveling on a road. In the first case, the lane line of the road where the vehicle is traveling exists and is clear; in the second case, the road where the vehicle is traveling has no lane line or is not paved. For the first case, the road driving path can be captured in real time directly through the hardware configured by the vehicle (sensing devices such as cameras and lidars), and the centerline position of the vehicle's driving road can be identified as the centerline of the trajectory for tracking; for the second case, the vehicle needs to have path planning capabilities, and the implementation technology of this recognition capability can be but is not limited to the Dijkstra algorithm, deep reinforcement learning, etc., and the hardware can rely on vehicle-mounted equipment such as lidars and cameras; according to the algorithm, the driving path can be planned first, and then the centerline of the trajectory can be obtained. After obtaining the centerline of the trajectory, the polynomial fitting algorithm can be used to fit the centerline of the trajectory to obtain the polynomial function expression f(x) of the centerline of the trajectory.

[0063] In one embodiment, obtaining the actual lateral position error of a vehicle during a preview-look-ahead period includes: obtaining a center line of a trajectory of the vehicle; obtaining an actual vehicle position during a preview-look-ahead period of the vehicle; and obtaining an actual lateral position error based on the center line of the trajectory and the actual vehicle position.

[0064] In this embodiment, the vehicle drives according to the control parameters obtained by the preview technology, and after each preview forward-looking time, it will reach the actual vehicle position corresponding to the preview forward-looking time. In the trajectory tracking process, the ideal state is to completely follow the trajectory centerline, but due to various reasons, the actual driving position of the vehicle will deviate from the trajectory centerline. Therefore, based on the trajectory centerline and the actual vehicle position, the actual lateral position error can be calculated.

[0065] In one embodiment, based on the trajectory centerline and the actual vehicle position, the actual lateral position error is obtained, including: based on the trajectory centerline and the actual vehicle position, calculating the initial lateral position error between the vehicle and the trajectory centerline; if the initial lateral position error is greater than or equal to an error threshold, determining the initial lateral position error to be the actual lateral position error.

[0066] In this embodiment, a low-pass filter based on an error threshold is configured. After the initial lateral position error is preliminarily calculated, the initial lateral position error is compared with the error threshold. If the initial lateral position error is less than the error threshold, it indicates that the actual initial lateral position error during the vehicle's driving process is small, and the impact on the vehicle's trajectory tracking process is small. In order to avoid safety hazards caused by frequent control of the vehicle, when the initial lateral position error is small, the first steering angle of the vehicle's trajectory tracking is not adjusted. However, if the initial lateral position error is greater than or equal to the error threshold, it indicates that the vehicle has deviated far from the center line of the trajectory, then it is necessary to determine that the initial lateral position error is the actual lateral position error, and adjust the first steering angle according to the actual lateral position error to ensure the control accuracy of the trajectory tracking. Based on the setting of the error threshold, not only a higher control accuracy of the vehicle is guaranteed, but also excessive interference with the vehicle can be avoided, ensuring the safety of the vehicle during driving. It should be noted that the error threshold can be pre-set according to actual needs and actual requirements for control accuracy, and the protection scope of this application is not limited to the specific value of the error threshold.

[0067] In one embodiment, the first steering angle is calculated based on the predicted lateral position error and curvature. Specifically, the centerline function of the vehicle's driving trajectory is defined as f(x), and f(x) can be converted into a time function f(t) according to the speed and acceleration of the vehicle.

[0068] Given the vehicle speed v(t), the corresponding relationship between time t and spatial coordinate x(t) can be calculated by integration:

[0069]

[0070] Among them, x0 is the initial position.

[0071] Based on the above, the f(x) path can be converted to f(t) as follows:

[0072] f(t)=f(x(t)) (10)

[0073] The vehicle position at the preview point is calculated as follows:

[0074]

[0075] Where T is the preview look-ahead duration, y(t+T) is the predicted vehicle position corresponding to the preview look-ahead duration, and y(t) is the actual vehicle position at time t. is the actual lateral velocity of the vehicle at time t, is the actual lateral acceleration of the vehicle at time t.

[0076] The position predicted to be reached after the vehicle's preview time is set as the preview position. The actual lateral position error of the vehicle at the preview position should be as follows:

[0077] f(t+f)-y(t+T)

[0078] With the above information, we can calculate the curvature of the path:

[0079]

[0080] Where, d is the forward distance, that is, the distance from the pilot to the preview position; is the curvature, and R is the turning radius of the vehicle.

[0081] The relationship between curvature and rotation angle is as follows:

[0082]

[0083] Wherein, L is the wheelbase of the vehicle.

[0084] In one embodiment, the trajectory tracking strategy configured for the vehicle can be any control strategy, such as Model Predictive Control (MPC), Proportional-Integral-Derivative Control (PID) control, fuzzy control, sliding mode control, etc.

[0085] In this embodiment, the simulation calculation is carried out by using the model predictive control MPC as a case. The model predictive control process is mainly divided into three steps:

[0086] The first step is to estimate / measure / read the current system state;

[0087] The second step is to perform optimization based on U(k).

[0088] The third step is to perform rolling optimization control.

[0089] The relevant calculation formula of model predictive control is as follows:

[0090] By linearizing and discretizing the vehicle model, the system output formula can be obtained:

[0091]

[0092] in:

[0093]

[0094] in, is the output coefficient matrix; is a nonlinear vehicle model, that is, a two-degree-of-freedom vehicle model in the above embodiment; is the vehicle state, which includes the actual lateral position error of the vehicle; is a system output matrix, wherein the system output matrix includes the calculated second steering angle; for The matrix after Taylor expansion.

[0095] At the same time, the control objective function can also be obtained:

[0096]

[0097] Among them: the first N is the prediction time domain p The second term is the maintenance term for controlling the target state quantity. N is the system in the control time domain c The control increment size within the control period reflects the system's requirement for a smooth change in the control quantity; however, since the system changes in real time, it cannot be guaranteed that the optimization objective function that satisfies the constraints at every moment can obtain the optimal solution within the control period. Therefore, it is necessary to add a relaxation factor ρε to the optimization objective function. 2 , where ρ is the penalty factor or weight coefficient and ε is the weight coefficient, so as to ensure that when there is no optimal solution within the control period, the system replaces the optimal solution with the obtained suboptimal solution to prevent the occurrence of no feasible solution.

[0098] Through the transformation calculation of the formula, the control problem can be converted into a quadratic programming problem, and the optimal control output can be obtained according to the objective function and the set constraints.

[0099] In this embodiment, based on the above-mentioned model predictive control and the vehicle control method provided by this application, the trajectory tracking algorithm is verified on the simulation platform. The simulation model logic built on the simulation platform is as follows: Figure 3 In the process of vehicle trajectory tracking, based on the preview technology and the model predictive control, the predicted vehicle front wheel steering angle (i.e., the first steering angle) is adjusted using the actual lateral position error of the vehicle, thereby achieving high real-time performance and high control accuracy in the process of vehicle trajectory tracking.

[0100] In this embodiment, the lateral position error of the vehicle in the double lane change condition is compared and verified, such as Figure 4 As shown in Figure 1, the error of single preview control fluctuates between -0.2m and +0.2m; Figure 5As shown, using the vehicle control method provided in this embodiment, the control error fluctuates between -0.025m and +0.025m, and the lateral error is significantly reduced compared to the error of the driving path (the maximum error is reduced from the original 0.2m to 0.025m). It can be seen that the vehicle control method provided in this embodiment greatly improves the control accuracy of vehicle trajectory tracking.

[0101] In a specific embodiment, Figure 6 As shown, the specific process of implementing the vehicle control method is as follows:

[0102] Step 601, the vehicle is traveling;

[0103] Step 602, identifying whether there is a lane line on the road, if yes, executing step 603, if no, executing step 604;

[0104] Step 603, identifying the center line of the vehicle's driving trajectory;

[0105] Step 604, performing path planning to form a virtual driving trajectory, and then obtaining a trajectory centerline;

[0106] Step 605, fitting the trajectory centerline to obtain a centerline polynomial function f(x);

[0107] Step 606, calculating the actual lateral position error between the actual position of the vehicle and the center line of the track, generating an adjustment angle based on the actual lateral position error, and executing step 608;

[0108] Step 607, calculate the predicted lateral position error and trajectory curvature according to the preview forward-looking time and the vehicle motion information, calculate the first steering angle using the preview control algorithm, and execute step 608;

[0109] Step 608 , using the adjustment angle to adjust the first steering angle to obtain a second steering angle, and controlling the vehicle trajectory tracking process based on the second steering angle, and returning to step 601 .

[0110] In this embodiment, the above cycle process stops when the vehicle stops running or receives a stop command.

[0111] In an embodiment of the present application, a first steering angle predicted based on the preview forward-looking time during the trajectory tracking process of the vehicle is obtained; the actual lateral position error of the vehicle during the preview forward-looking time is obtained; the first steering angle is adjusted based on the actual lateral position error to obtain a second steering angle; the trajectory tracking strategy configured for the vehicle is executed based on the second steering angle to control the vehicle's travel. In the above process, the first steering angle obtained by preview is adopted to avoid the lag of path tracking and ensure the real-time performance of the vehicle's path tracking control. At the same time, compared with the method of pure preview calculation of trajectory tracking, the first steering angle is adjusted based on the first steering angle by the actual lateral position error of the vehicle, which can further improve the control accuracy of the vehicle's trajectory tracking. Based on the above, the technical solution provided by the present application ensures both real-time performance and control accuracy during the vehicle trajectory tracking process, thereby improving the control effect of the vehicle trajectory tracking.

[0112] Furthermore, the curvature of the preview position of the vehicle is calculated, and the steering angle of the vehicle is calculated and output in advance, thereby improving the response speed of the vehicle to the driving path; at the same time, according to the actual lateral position error between the real-time vehicle actual position and the center line of the trajectory, PID, MPC and other control algorithms are used to quickly calculate the adjustment of the front wheel steering angle, thereby reducing the calculation complexity and improving the accuracy of trajectory tracking. Optionally, when the application object of this application is an unmanned vehicle, the control output is the front wheel steering angle of the vehicle (the second steering angle). Compared with the control scheme that directly uses the real-time lateral displacement calculation of the vehicle, the preview control does not have control lag and has higher control accuracy; at the same time, compared with the pure preview calculation trajectory tracking method, the front wheel steering angle is optimized and adjusted according to the real-time actual position of the vehicle on the basis of the preview control, thereby further improving the control accuracy.

[0113] Exemplary Devices

[0114] Accordingly, the embodiment of the present application also provides a vehicle control device, such as Figure 7 As shown, the device may include:

[0115] The predicted angle acquisition module 701 is used to acquire a first steering angle predicted based on the preview forward-looking duration of the vehicle during the trajectory tracking process;

[0116] The actual error calculation module 702 is used to obtain the actual lateral position error of the vehicle during the preview forward-looking time;

[0117] An angle adjustment module 703, used to adjust the first steering angle based on the actual lateral position error to obtain a second steering angle;

[0118] The vehicle control module 704 is used to execute a trajectory tracking strategy configured for the vehicle based on the second steering angle to control the driving of the vehicle.

[0119] In one embodiment, the predicted angle acquisition module 701 is used to obtain the predicted lateral position error of the vehicle based on the preview forward vision time during the trajectory tracking process, and to obtain the curvature of the center line of the vehicle's trajectory based on the preview forward vision time; based on the predicted lateral position error and curvature, a first steering angle is obtained.

[0120] In one embodiment, the predicted angle acquisition module 701 is used to obtain the center line of the vehicle's travel trajectory; based on the preview forward viewing time of trajectory tracking and the vehicle's motion information, obtain the predicted vehicle position based on the preview forward viewing time; based on the predicted vehicle position and the trajectory center line, obtain the predicted lateral position error corresponding to the predicted vehicle position.

[0121] In one embodiment, the prediction angle acquisition module 701 is used to calculate the curvature corresponding to the preview look-ahead time of the centerline of the trajectory based on the preview look-ahead time, the centerline of the trajectory and the motion information of the vehicle.

[0122] In one embodiment, the predicted angle acquisition module 701 is used to identify the lane lines in the road where the vehicle is located, and obtain the center line of the trajectory based on the lane lines; or, obtain the traveled path information of the vehicle, obtain the planned path based on the traveled path information, and obtain the center line of the trajectory based on the planned path.

[0123] In one embodiment, the actual error calculation module 702 is used to obtain the center line of the vehicle's travel trajectory; obtain the actual vehicle position during the vehicle's travel preview forward viewing period; and obtain the actual lateral position error based on the trajectory center line and the actual vehicle position.

[0124] In one embodiment, the actual error calculation module 702 is used to calculate the initial lateral position error between the vehicle and the trajectory centerline based on the trajectory centerline and the actual vehicle position; if the initial lateral position error is greater than or equal to the error threshold, the initial lateral position error is determined to be the actual lateral position error.

[0125] The vehicle control device provided in this embodiment belongs to the same application concept as the vehicle control method provided in the above embodiments of this application, and can execute the vehicle control method provided in any of the above embodiments of this application, and has the corresponding functional modules and beneficial effects of the execution method. For the technical details not fully described in this embodiment, please refer to the specific processing content of the vehicle control method provided in the above embodiments of this application, and will not be repeated here.

[0126] Exemplary Electronic Devices

[0127] The present application also provides an electronic device, such as Figure 8 As shown, the electronic device includes: a memory 800 and a processor 801.

[0128] The memory 800 is connected to the processor 801 and is used to store programs.

[0129] The processor 801 is used to implement the vehicle control method in the above embodiment by running the program stored in the memory 800.

[0130] Specifically, the electronic device may further include: a communication interface 802 , an input device 803 , an output device 804 and a bus 805 .

[0131] The processor 801, the memory 800, the communication interface 802, the input device 803 and the output device 804 are connected to each other via a bus.

[0132] Bus 805 may include a pathway for transferring information between the various components of the computer system.

[0133] The processor 801 may be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the scheme of the present invention. It may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0134] The processor 801 may include a main processor, and may also include a baseband chip, a modem, etc.

[0135] The memory 800 stores a program for executing the technical solution of the present invention, and may also store an operating system and other key services. Specifically, the program may include a program code, and the program code includes a computer operation instruction. More specifically, the memory 800 may include a read-only memory (ROM), other types of static storage devices that can store static information and instructions, a random access memory (RAM), other types of dynamic storage devices that can store information and instructions, a disk storage, a flash, and the like.

[0136] The input device 803 may include a device for receiving data and information input by a user, such as a keyboard, a mouse, a camera, a scanner, a light pen, a voice input device, a touch screen, a pedometer, or a gravity sensor.

[0137] Output device 804 may include devices that allow information to be output to a user, such as a display screen, printer, speakers, etc.

[0138] The communication interface 802 may include any transceiver or the like to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0139] The processor 801 executes the program stored in the memory 800 and calls other devices, which can be used to implement the various steps of the vehicle control method provided in the above embodiments of the present application.

[0140] Exemplary computer program products and storage media

[0141] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps in the vehicle control method described in the embodiment of the present application.

[0142] The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK).

[0143] The computer program product may be written in any combination of one or more programming languages ​​to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages, such as Java, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0144] In addition, an embodiment of the present application may also be a storage medium on which a computer program is stored, and the computer program is executed by a processor to execute the steps of the vehicle control method described in the embodiment of the present application.

[0145] For the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0146] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0147] The steps in the methods of each embodiment of the present application can be adjusted in order, combined and deleted according to actual needs, and the technical features recorded in each embodiment can be replaced or combined.

[0148] The modules and sub-modules in the devices and terminals provided in the embodiments of the present application can be merged, divided and deleted according to actual needs.

[0149] In the several embodiments provided in the present application, it should be understood that the disclosed terminals, devices and methods can be implemented in other ways. For example, the terminal embodiments described above are only schematic, for example, the division of modules or submodules is only a logical function division, and there may be other division methods in actual implementation, for example, multiple submodules or modules can be combined or integrated into another module, 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 modules, which can be electrical, mechanical or other forms.

[0150] The modules or submodules described as separate components may or may not be physically separated, and the components of the modules or submodules may or may not be physical modules or submodules, that is, they may be located in one place, or they may be distributed on multiple network modules or submodules. Some or all of the modules or submodules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0151] In addition, each functional module or submodule in each embodiment of the present application may be integrated into one processing module, or each module or submodule may exist physically separately, or two or more modules or submodules may be integrated into one module. The above-mentioned integrated modules or submodules may be implemented in the form of hardware or in the form of software functional modules or submodules.

[0152] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may 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.

[0153] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly by hardware, software units executed by a processor, or a combination of the two. The software units may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0154] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0155] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A vehicle control method, characterized in that: include: Obtaining a first steering angle of the vehicle predicted based on the preview forward-looking duration during the trajectory tracking process; Obtaining an actual lateral position error of the vehicle when the vehicle travels the preview forward viewing time; adjusting the first steering angle based on the actual lateral position error to obtain a second steering angle; A trajectory tracking strategy configured for the vehicle is executed based on the second steering angle to control the vehicle driving.

2. The vehicle control method according to claim 1, characterized in that: The obtaining of a first steering angle predicted based on the preview forward-looking duration of the vehicle during the trajectory tracking process includes: Obtaining a predicted lateral position error of the vehicle during trajectory tracking based on the preview forward-looking duration, and obtaining a curvature of a centerline of a trajectory of the vehicle based on the preview forward-looking duration; Based on the predicted lateral position error and the curvature, the first steering angle is obtained.

3. The vehicle control method according to claim 2, characterized in that: The obtaining of a predicted lateral position error of the vehicle during the trajectory tracking process based on the preview forward-looking duration prediction includes: Obtaining a center line of a trajectory of the vehicle; Based on the preview look-ahead duration of trajectory tracking and the motion information of the vehicle, obtaining a predicted vehicle position of the vehicle based on the preview look-ahead duration; Based on the predicted vehicle position and the trajectory centerline, the predicted lateral position error corresponding to the predicted vehicle position is obtained.

4. The vehicle control method according to claim 3, characterized in that: The step of obtaining the curvature of the center line of the vehicle's trajectory based on the preview duration includes: The curvature of the trajectory centerline corresponding to the preview look-ahead time is calculated based on the preview look-ahead time, the trajectory centerline and the motion information of the vehicle.

5. The vehicle control method according to claim 3, characterized in that: The step of obtaining the center line of the vehicle's travel trajectory includes: Identifying a lane line on a road where the vehicle is located, and acquiring a center line of the trajectory based on the lane line; or, Acquire information about a route traveled by the vehicle, acquire a planned route based on the information about the route traveled, and acquire the center line of the trajectory based on the planned route.

6. The vehicle control method according to claim 1, characterized in that: The obtaining of the actual lateral position error of the vehicle when the vehicle travels the preview forward-looking time period includes: Obtaining a center line of a trajectory of the vehicle; Obtaining the actual vehicle position when the vehicle travels for the preview forward viewing time; The actual lateral position error is obtained based on the trajectory centerline and the actual vehicle position.

7. The vehicle control method according to claim 6, characterized in that: The obtaining the actual lateral position error based on the trajectory centerline and the actual vehicle position includes: calculating an initial lateral position error between the vehicle and the trajectory centerline based on the trajectory centerline and the actual vehicle position; If the initial lateral position error is greater than or equal to an error threshold, the initial lateral position error is determined to be the actual lateral position error.

8. A vehicle, characterized in that: The vehicle includes a trajectory tracking module, wherein the trajectory tracking module is configured with a trajectory tracking strategy; The trajectory tracking strategy is executed by the vehicle control method according to any one of claims 1 to 7 to control the driving of the vehicle.

9. An electronic device, characterized in that: include: Memory and processor; The memory is connected to the processor and is used to store programs; The processor is used to implement the vehicle control method as described in any one of claims 1 to 7 by running the program in the memory.

10. A computer program product, characterized in that includes computer program instructions; When the computer program instructions are executed by a processor, the processor is caused to execute the vehicle control method according to any one of claims 1 to 7.

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