Vehicle control method, device and equipment, medium and vehicle

Abstract

The invention provides a vehicle control method, device and equipment, a medium and a vehicle, relates to the technical field of vehicles, and aims to solve the problems of low precision and poor timeliness of a general technology for controlling the vehicle. The vehicle control method comprises the following steps: acquiring driving state information and planning path information of a vehicle; according to the driving state information and the planning path information, determining a target PID parameter of a fuzzy PID controller of the vehicle; determining control parameters of the vehicle according to the driving state information, the planning path information and the target PID parameters; controlling the vehicle to run according to the control parameters.

Description

Technical Field

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

[0002] The vehicle can control the vehicle's accelerator pedal, brake pedal and wheel steering according to the vehicle's status information and planned path information to make the vehicle travel along the planned path.

[0003] General technology usually controls vehicles based on vehicle mathematical models or dynamic models. However, controlling vehicle movement based on vehicle mathematical models is only based on simple kinematics and cannot accurately feedback vehicle status, which affects control accuracy. Controlling vehicle movement based on dynamic models requires large amounts of calculations, which affects the timeliness of control.

[0004] Therefore, the general technology for controlling vehicle driving has low accuracy and poor timeliness. Summary of the invention

[0005] The embodiments of the present disclosure provide a vehicle control method, device, equipment, medium and vehicle, aiming to solve the problem of low accuracy and poor timeliness of vehicle control using general technology.

[0006] In order to achieve the above objectives, this application adopts the following technical solutions:

[0007] In a first aspect, a vehicle control method is provided, including: obtaining driving state information and planned path information of the vehicle; determining target PID parameters of a fuzzy proportional-integral-derivative (PID) controller of the vehicle according to the driving state information and the planned path information; determining control parameters of the vehicle according to the driving state information, the planned path information and the target PID parameters; and controlling the driving of the vehicle according to the control parameters.

[0008] Optionally, target PID parameters of the vehicle's fuzzy PID controller are determined based on driving status information and planned path information, including: determining deviation information based on the driving status information and planned path information; the deviation information is used to indicate the deviation between the driving status information and the planned path information; determining a fuzzy coefficient based on the deviation information and a membership function corresponding to the deviation information; different deviation information corresponds to different fuzzy coefficients; the fuzzy coefficient is a coefficient for determining the target PID parameters; and determining the product of the fuzzy coefficient and the initial PID parameters of the fuzzy PID controller as the target PID parameter of the fuzzy PID controller.

[0009] Optionally, the driving status information includes: the center point of the front axle, and the planned path information includes: the front axle target tracking point; based on the driving status information and the planned path information, the deviation information is determined, including: the difference between the front axle target tracking point and the front axle center point in a first direction is determined as the deviation information of the longitudinal position, and the difference between the front axle target tracking point and the front axle center point in a second direction is determined as the deviation information of the lateral position of the front axle; the first direction is used to indicate the direction in which the rear axle center point points to the front axle center point; the first direction is perpendicular to the second direction.

[0010] Optionally, the driving status information includes: the center point of the rear axle, and the planned path information includes: the target tracking point of the rear axle; and the deviation information is determined based on the driving status information and the planned path information, including: determining the difference between the rear axle target tracking point and the rear axle center point in the second direction as the deviation information of the lateral position of the rear axle.

[0011] Optionally, the driving status information also includes: the current driving speed, and the planned path information also includes: the target driving speed; according to the driving status information and the planned path information, the deviation information is determined, including: determining the difference between the target driving speed and the current driving speed as the speed deviation information.

[0012] Optionally, when the control parameters include lateral control parameters and the lateral control parameters include the front wheel steering angle, the deviation information includes: the deviation information of the lateral position of the front axle; the driving status information includes: the current driving speed; the membership function includes the deviation information of the lateral position of the front axle, the current driving speed and the corresponding relationship between the fuzzy coefficient; when the control parameters include lateral control parameters and the lateral control parameters include the rear wheel steering angle, the deviation information includes: the deviation information of the lateral position of the rear axle; the driving status information includes: the sideslip angle of the center of mass; the membership function includes the deviation information of the lateral position of the rear axle, the corresponding relationship between the sideslip angle of the center of mass and the fuzzy coefficient.

[0013] Optionally, the control parameters of the vehicle are determined based on the driving state information, the planned path information and the target PID parameters, including: determining compensation information of the target driving state based on the deviation information and the target PID parameters; compensating the target driving state based on the compensation information, and determining the control parameters of the vehicle based on the compensated target driving state.

[0014] Optionally, the deviation information includes: deviation information of longitudinal position and deviation information of speed; the compensation information includes: compensation speed and compensation acceleration; the control parameters include: motor torque and brake pressure; the driving state information includes: motor speed; the target driving state includes: target driving speed and target acceleration; the target driving state is compensated according to the compensation information, and the control parameters of the vehicle are determined according to the compensated target driving state, including: compensating the target driving speed according to the compensation speed to obtain the compensated target driving speed, and compensating the target acceleration according to the compensation acceleration to obtain the compensated target acceleration; according to the compensated target driving speed, the compensated target acceleration, the correspondence between the motion parameters and the control parameters, the throttle depth and brake pressure of the vehicle are determined; the motion parameters include compensation speed and compensation acceleration; the control parameters include throttle depth and brake pressure; the correspondence between the motion parameters and the control parameters includes: the correspondence between the motion parameters and the throttle depth and the correspondence between the motion parameters and the brake pressure; the motor torque of the vehicle is determined according to the throttle depth and the motor speed.

[0015] Optionally, the deviation information includes: deviation information of the lateral position of the front axle; the driving state information includes: the front axle center point; the planned path information includes: the front axle target tracking point and the front axle preview point; the target driving state includes: the front wheel preview angle; the compensation information includes: the front wheel compensation angle; the control parameters include: the front wheel steering angle; the target driving state is compensated according to the compensation information, and the control parameters of the vehicle are determined according to the compensated target driving state, including: determining the direction vector pointing from the front axle center point to the front axle target tracking point as the front axle target direction vector; determining the direction vector pointing from the front axle center point to the front axle preview point as the front axle preview direction vector; determining the front wheel preview angle according to the front axle target direction vector and the front axle preview direction vector; compensating the front wheel preview angle according to the front wheel compensation angle, and determining the compensated front wheel preview angle as the front wheel steering angle.

[0016] Optionally, the deviation information includes: deviation information of the lateral position of the rear axle; the driving state information includes: the center point of the rear axle; the planned path information includes: the rear axle target tracking point and the rear axle preview point; the target driving state includes: the rear wheel preview angle; the compensation information includes: the rear wheel compensation angle; the control parameters include: the rear wheel steering angle; the target driving state is compensated according to the compensation information, and the control parameters of the vehicle are determined according to the compensated target driving state, including: determining the direction vector pointing from the center point of the rear axle to the rear axle target tracking point as the rear axle target direction vector; determining the direction vector pointing from the center point of the rear axle to the rear axle preview point as the rear axle preview direction vector; determining the rear wheel preview angle according to the rear axle target direction vector and the rear axle preview direction vector; compensating the rear wheel preview angle according to the rear wheel compensation angle, and determining the compensated rear wheel preview angle as the rear wheel steering angle.

[0017] Optionally, when the control parameters include longitudinal control parameters, the membership function includes the correspondence between deviation information and fuzzy coefficients; when the control parameters include lateral control parameters, the membership function includes the correspondence between deviation information, driving state information and fuzzy coefficients.

[0018] In a second aspect, a vehicle control device is provided, which includes: a communication unit and a processing unit; the communication unit is used to obtain the vehicle's driving state information and planned path information; the processing unit is used to determine the target PID parameters of the vehicle's fuzzy proportional integral differential PID controller based on the driving state information and the planned path information; the processing unit is also used to determine the vehicle's control parameters based on the driving state information, the planned path information and the target PID parameters; the processing unit is also used to control the vehicle's driving according to the control parameters.

[0019] Optionally, the processing unit is specifically used to: determine the deviation information according to the driving state information and the planned path information; the deviation information is used to indicate the deviation between the driving state information and the planned path information; determine the fuzzy coefficient according to the deviation information and the membership function corresponding to the deviation information; different deviation information corresponds to different fuzzy coefficients; the fuzzy coefficient is the coefficient for determining the target PID parameters; the product of the fuzzy coefficient and the initial PID parameters of the fuzzy PID controller is determined as the target PID parameters of the fuzzy PID controller.

[0020] Optionally, the driving status information includes: the center point of the front axle, and the planned path information includes: the front axle target tracking point; a processing unit is specifically used to: determine the difference between the front axle target tracking point and the front axle center point in a first direction as the deviation information of the longitudinal position, and determine the difference between the front axle target tracking point and the front axle center point in a second direction as the deviation information of the lateral position of the front axle; the first direction is used to indicate the direction in which the rear axle center point points to the front axle center point; the first direction is perpendicular to the second direction.

[0021] Optionally, the driving status information includes: the rear axle center point, and the planned path information includes: the rear axle target tracking point; the processing unit is specifically used to: determine the difference between the rear axle target tracking point and the rear axle center point in the second direction as the deviation information of the lateral position of the rear axle.

[0022] Optionally, the driving status information also includes: a current driving speed, and the planned path information also includes: a target driving speed; and the processing unit is specifically used to: determine the difference between the target driving speed and the current driving speed as speed deviation information.

[0023] Optionally, when the control parameters include lateral control parameters and the lateral control parameters include the front wheel steering angle, the deviation information includes: the deviation information of the lateral position of the front axle; the driving status information includes: the current driving speed; the membership function includes the deviation information of the lateral position of the front axle, the current driving speed and the corresponding relationship between the fuzzy coefficient; when the control parameters include lateral control parameters and the lateral control parameters include the rear wheel steering angle, the deviation information includes: the deviation information of the lateral position of the rear axle; the driving status information includes: the sideslip angle of the center of mass; the membership function includes the deviation information of the lateral position of the rear axle, the corresponding relationship between the sideslip angle of the center of mass and the fuzzy coefficient.

[0024] Optionally, the processing unit is specifically used to: determine compensation information of the target driving state based on the deviation information and the target PID parameters; compensate the target driving state based on the compensation information, and determine the control parameters of the vehicle based on the compensated target driving state.

[0025] Optionally, the deviation information includes: deviation information of longitudinal position and deviation information of speed; the compensation information includes: compensation speed and compensation acceleration; the control parameters include: motor torque and brake pressure; the driving state information includes: motor speed; the target driving state includes: target driving speed and target acceleration; the processing unit is specifically used to: compensate the target driving speed according to the compensation speed to obtain the compensated target driving speed, and compensate the target acceleration according to the compensation acceleration to obtain the compensated target acceleration; determine the throttle depth and brake pressure of the vehicle according to the compensated target driving speed, the compensated target acceleration, the correspondence between the motion parameters and the control parameters; the motion parameters include compensation speed and compensation acceleration; the control parameters include throttle depth and brake pressure; the correspondence between the motion parameters and the control parameters includes: the correspondence between the motion parameters and the throttle depth and the correspondence between the motion parameters and the brake pressure; determine the motor torque of the vehicle according to the throttle depth and the motor speed.

[0026] Optionally, the deviation information includes: deviation information of the lateral position of the front axle; the driving state information includes: the front axle center point; the planned path information includes: the front axle target tracking point and the front axle preview point; the target driving state includes: the front wheel preview angle; the compensation information includes: the front wheel compensation angle; the control parameters include: the front wheel steering angle; the processing unit is specifically used to: determine the direction vector pointing from the front axle center point to the front axle target tracking point as the front axle target direction vector; determine the direction vector pointing from the front axle center point to the front axle preview point as the front axle preview direction vector; determine the front wheel preview angle according to the front axle target direction vector and the front axle preview direction vector; compensate the front wheel preview angle according to the front wheel compensation angle, and determine the compensated front wheel preview angle as the front wheel steering angle.

[0027] Optionally, the deviation information includes: deviation information of the lateral position of the rear axle; the driving state information includes: the center point of the rear axle; the planned path information includes: the rear axle target tracking point and the rear axle preview point; the target driving state includes: the rear wheel preview angle; the compensation information includes: the rear wheel compensation angle; the control parameters include: the rear wheel steering angle; the processing unit is specifically used to: determine the direction vector pointing from the center point of the rear axle to the rear axle target tracking point as the rear axle target direction vector; determine the direction vector pointing from the center point of the rear axle to the rear axle preview point as the rear axle preview direction vector; determine the rear wheel preview angle according to the rear axle target direction vector and the rear axle preview direction vector; compensate the rear wheel preview angle according to the rear wheel compensation angle, and determine the compensated rear wheel preview angle as the rear wheel steering angle.

[0028] Optionally, when the control parameters include longitudinal control parameters, the membership function includes the correspondence between deviation information and fuzzy coefficients; when the control parameters include lateral control parameters, the membership function includes the correspondence between deviation information, driving state information and fuzzy coefficients.

[0029] In a third aspect, a vehicle control device is provided, comprising a memory and a processor; the memory is used to store computer execution instructions, and the processor is connected to the memory via a bus; when the vehicle control device is running, the processor executes the computer execution instructions stored in the memory, so that the vehicle control device executes the vehicle control method of the first aspect.

[0030] The vehicle control device may be an electronic device or a part of an electronic device, such as a chip system in an electronic device. The chip system is used to support the electronic device to implement the functions involved in the first aspect and any possible implementation thereof, for example, to obtain and determine the data and / or information involved in the above-mentioned vehicle control method. The chip system includes a chip and may also include other discrete devices or circuit structures.

[0031] In a fourth aspect, a computer-readable storage medium is provided, the computer-readable storage medium comprising computer execution instructions, and when the computer execution instructions are run on a computer, the computer executes the vehicle control method described in the first aspect.

[0032] In a fifth aspect, a computer program product is also provided, which includes a computer program or instructions. When the computer instructions are executed on a vehicle control device, the vehicle control device executes the vehicle control method as described in the first aspect above.

[0033] In a sixth aspect, a vehicle is provided, comprising a vehicle control device as in the second aspect, and the vehicle is used to implement a method as in the first aspect.

[0034] It should be noted that the above-mentioned computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer-readable storage medium may be packaged together with the processor of the vehicle control device, or may be packaged separately from the processor of the vehicle control device, which is not limited in the embodiments of the present application.

[0035] The description of the third, fourth, fifth and sixth aspects of the present application can refer to the detailed description of the first and second aspects.

[0036] In the embodiments of the present application, the name of the above-mentioned vehicle control device does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear with other names. For example, the receiving unit may also be called a receiving module, a receiver, etc. As long as the functions of each device or functional module are similar to those of the present application, they fall within the scope of the claims of the present application and their equivalent technologies.

[0037] The technical solution provided by this application brings at least the following beneficial effects:

[0038] Based on any of the above aspects, an embodiment of the present application provides a vehicle control method, first, obtaining the driving state information and the planned path information of the vehicle. Then, according to the driving state information and the planned path information, the target PID parameters of the fuzzy PID controller of the vehicle are determined. Then, according to the driving state information, the planned path information and the target PID parameters, the control parameters of the vehicle are determined. Then, the vehicle is controlled to travel according to the control parameters.

[0039] As can be seen from the above, the present application uses a fuzzy PID controller to determine the control parameters of the vehicle to control the vehicle when controlling the vehicle. The fuzzy PID controller can be used to adjust the PID parameters of the fuzzy PID controller in real time according to the vehicle's driving state information, which can improve the accuracy of controlling the vehicle. In addition, the fuzzy PID controller has less computational complexity and higher efficiency, which can improve the timeliness of controlling the vehicle.

[0040] The beneficial effects of the first, second, third, fourth, fifth and sixth aspects of the present application can all be referred to the analysis of the above beneficial effects, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1A schematic diagram of the structure of a vehicle control system provided in an embodiment of the present application;

[0043] Figure 2 A schematic diagram of a hardware structure of a communication device provided in an embodiment of the present application;

[0044] Figure 3 A schematic diagram of a vehicle control method provided in an embodiment of the present application;

[0045] Figure 4 A flow chart of another vehicle control method provided in an embodiment of the present application;

[0046] Figure 5 A schematic diagram of a vehicle driving provided in an embodiment of the present application;

[0047] Figure 6 A schematic diagram of a membership function provided in an embodiment of the present application;

[0048] Figure 7 A schematic diagram of another membership function provided in an embodiment of the present application;

[0049] Figure 8 A schematic diagram of another membership function provided in an embodiment of the present application;

[0050] Fig. 9 A schematic diagram of another membership function provided in an embodiment of the present application;

[0051] Fig.10 A flow chart of another vehicle control method provided in an embodiment of the present application;

[0052] Fig.11 A flow chart of another vehicle control method provided in an embodiment of the present application;

[0053] Fig.12 A flow chart of another vehicle control method provided in an embodiment of the present application;

[0054] Fig.13 A driving schematic diagram of another vehicle provided in an embodiment of the present application;

[0055] Fig.14 A flow chart of another vehicle control method provided in an embodiment of the present application;

[0056] Fig.15 A schematic diagram of a process for determining a longitudinal control parameter of a vehicle by a vehicle control device provided in an embodiment of the present application;

[0057] Fig.16 A schematic diagram of a process for determining a vehicle lateral control parameter by a vehicle control device provided in an embodiment of the present application;

[0058] Fig.17 A schematic diagram of a process for controlling vehicle driving provided in an embodiment of the present application;

[0059] Fig.18 A schematic diagram of a curve showing vehicle data changing over time provided in an embodiment of the present application;

[0060] Fig.19 A schematic diagram of a curve showing another type of vehicle data changing over time provided in an embodiment of the present application;

[0061] Fig. 20 A schematic diagram of the structure of a vehicle control device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0062] 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.

[0063] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0064] In order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second", etc. are used to distinguish the same items or similar items with basically the same functions and effects. Those skilled in the art can understand that the words "first", "second", etc. are not limiting the quantity and execution order.

[0065] Before introducing the vehicle control method provided by the present application in detail, a brief introduction to the application scenarios and implementation environment involved in the present application is first given.

[0066] First, a brief introduction to the application scenarios involved in this application is given.

[0067] As described in the background art, the vehicle can control the accelerator pedal, brake pedal and wheel steering of the vehicle according to the vehicle status information and the planned path information, so that the vehicle travels along the planned path.

[0068] General technology usually adopts optimal control and model predictive control to control vehicle driving.

[0069] Among them, optimal control is a control method based on vehicle state feedback. However, optimal control uses a vehicle mathematical model. It cannot accurately feedback the vehicle state based on a simple kinematic model, and the control accuracy is not high. Optimal control uses a complex dynamic model, and the amount of calculation is too large, which affects the timeliness of control. In addition, optimal control only considers the vehicle state, not the environmental factors. When entering and exiting a curve, the longitudinal control and lateral control are not accurate.

[0070] Model predictive control is a method of controlling vehicle movement by predicting changes in vehicle position, speed, and acceleration. However, model predictive control uses a complex dynamic model, which results in a large amount of calculation. In addition, the derivation of the model predictive control algorithm is relatively complex, which affects the timeliness of the control.

[0071] As can be seen from the above, controlling vehicle movement based on the vehicle mathematical model is only based on simple kinematics, which cannot accurately feedback the vehicle state and affects the control accuracy. Controlling vehicle movement based on the dynamic model requires a large amount of calculation, which affects the timeliness of control. Therefore, the general technology for controlling vehicle movement has low accuracy and poor timeliness.

[0072] In view of the above problems, an embodiment of the present application provides a vehicle control method. First, the driving state information and the planned path information of the vehicle are obtained. Then, the target PID parameters of the fuzzy PID controller of the vehicle are determined according to the driving state information and the planned path information. Then, the control parameters of the vehicle are determined according to the driving state information, the planned path information and the target PID parameters. Then, the vehicle is controlled to travel according to the control parameters.

[0073] As can be seen from the above, this application uses a fuzzy PID controller to determine the control parameters of the vehicle when controlling the vehicle to control the vehicle. The fuzzy PID controller can adjust the PID parameters of the fuzzy PID controller in real time according to the vehicle's driving state information, thereby improving the accuracy of controlling the vehicle. Moreover, compared with using a dynamic model to determine the control parameters, the fuzzy PID controller has less computational complexity and higher efficiency, which can improve the timeliness of controlling the vehicle.

[0074] The implementation environment of the above-mentioned vehicle control method can be the vehicle control system provided in the embodiment of the present application.

[0075] Figure 1 FIG. 1 shows a schematic diagram of the structure of a vehicle control system provided by an embodiment of the present application. Figure 1 As shown, the vehicle control system includes: a vehicle control device 101, a data storage device 102, and a vehicle-mounted sensor 103.

[0076] The vehicle control device 101 and the data storage device 102 are communicatively connected to each other, and the vehicle-mounted sensor 103 is communicatively connected to the vehicle control device 101 and the data storage device 102 respectively.

[0077] In practical applications, the vehicle control device 101 can be connected to any number of data storage devices 102 and vehicle sensors 103. For ease of understanding, Figure 1 An example is given for description in which a vehicle control device 101 is connected to a data storage device 102 and a vehicle-mounted sensor 103 .

[0078] In an embodiment of the present application, the data storage device 102 is used to provide the vehicle control device 101 with planned path information, including but not limited to data such as the front axle target tracking point, the rear axle target tracking point, the front axle preview point and the rear axle preview point. The data storage device 102 is also used to provide the vehicle control device 101 with data such as the vehicle target driving speed and target acceleration.

[0079] The vehicle-mounted sensor 103 is used to provide the vehicle control device 101 with vehicle driving status information, including but not limited to the front axle center point, the rear axle center point, the current driving speed, the center of mass sideslip angle and the motor speed.

[0080] Optionally, the vehicle control device 101 and the data storage device 102 may be two devices independently provided, or may be integrated into the same device. When the vehicle control device 101 and the data storage device 102 are integrated into the same device, the data storage device 102 may be a communication module of the vehicle control device.

[0081] It is easy to understand that when the vehicle control device 101 and the data storage device 102 are integrated into the same device, the communication mode between the vehicle control device 101 and the data storage device 102 is the communication between the internal modules of the device. In this case, the communication process between the two is the same as the communication process between the vehicle control device 101 and the data storage device 102 when they are independent of each other.

[0082] Optionally, the vehicle control device 101 and the vehicle sensor 103 may be two devices independently provided, or may be integrated into the same device. When the vehicle control device 101 and the vehicle sensor 103 are integrated into the same device, the vehicle sensor 103 may be a communication module of the vehicle control device.

[0083] It is easy to understand that when the vehicle control device 101 and the vehicle-mounted sensor 103 are integrated into the same device, the communication method between the vehicle control device 101 and the vehicle-mounted sensor 103 is the communication between the internal modules of the device. In this case, the communication process between the two is the same as the communication process between the two when the vehicle control device 101 and the vehicle-mounted sensor 103 are independent of each other. For ease of understanding, this application is explained by taking the vehicle control device 101, the data storage device 102 and the vehicle-mounted sensor 103 as an example of being independent of each other.

[0084] The vehicle control devices in the vehicle control system include: Figure 2 The following are the components included. Figure 2 Taking the communication device shown in the figure as an example, the hardware structure of the vehicle control device is introduced.

[0085] Figure 2 , which is a schematic diagram of a hardware structure of a communication device provided in an embodiment of the present application. The communication device includes a processor 21, a memory 22, a communication interface 23, and a bus 24. The processor 21, the memory 22, and the communication interface 23 can be connected via a bus 24.

[0086] The processor 21 is the control center of the communication device, which can be a processor or a general term for multiple processing elements. For example, the processor 21 can be a general-purpose central processing unit (CPU) or other general-purpose processors. Among them, the general-purpose processor can be a microprocessor or any conventional processor.

[0087] As an embodiment, the processor 21 may include one or more CPUs, such as Figure 2 CPU0 and CPU1 are shown in the figure.

[0088] The memory 22 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0089] In a possible implementation, the memory 22 may exist independently of the processor 21, and the memory 22 may be connected to the processor 21 via a bus 24 to store instructions or program codes. When the processor 21 calls and executes the instructions or program codes stored in the memory 22, the vehicle control method provided in the following embodiments of the present application can be implemented.

[0090] In the embodiment of the present application, for the communication device, the software programs stored in the memory 22 are different, so the functions implemented by the communication device are different. The functions performed by each device will be described in conjunction with the following flowchart.

[0091] In another possible implementation, the memory 22 may also be integrated with the processor 21 .

[0092] The communication interface 23 is used for the communication device to connect with other devices through a communication network, and the communication network may be Ethernet, wireless access network, wireless local area network (WLAN), etc. The communication interface 23 may include a receiving unit for receiving data and a sending unit for sending data.

[0093] The bus 24 may be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0094] It should be pointed out that Figure 2 The structure shown in the figure does not constitute a limitation on the communication device, except Figure 2 In addition to the components shown, the communication device may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0095] The vehicle control method provided in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0096] The vehicle control method provided in the embodiment of the present application is applied to Figure 1 The vehicle control device 101 in the vehicle control system shown in FIG. Figure 3 As shown, the vehicle control method provided by the embodiment of the present application includes:

[0097] S301. Obtain vehicle driving status information and planned path information.

[0098] In one achievable manner, the vehicle control device needs to determine the target PID parameters of the fuzzy PID controller according to the vehicle's driving state information and planned path information, and determine the vehicle's control parameters according to the driving state information, the planned path information and the target PID parameters, so as to subsequently control the vehicle to travel along the planned path according to the control parameters. Therefore, the vehicle control device needs to obtain the vehicle's driving state information and planned path information.

[0099] Driving status information includes: front axle center point, rear axle center point, current driving speed, center of mass sideslip angle and motor speed.

[0100] The front axle center point is the point halfway between the axis of the front wheels of the vehicle.

[0101] The rear axle center is the point halfway between the axis of the vehicle's rear wheels.

[0102] The side slip angle refers to the angle between the vehicle's center of mass speed and the vehicle's longitudinal axis. During the vehicle's steering process, the vehicle's center of mass speed will form an angle with the vehicle's longitudinal axis. A large side slip angle will affect the safety of the vehicle.

[0103] The longitudinal axis of the vehicle refers to the direction from the center point of the rear axle to the center of the front axle.

[0104] Motor speed refers to the speed at which the motor rotates. Motor speed directly determines motor torque and motor output power, thus affecting the acceleration performance of the vehicle.

[0105] The planned path information includes: front axle target tracking point, rear axle target tracking point, front axle preview point and rear axle preview point.

[0106] The front axle target tracking point refers to the specific position of the vehicle's front axle that needs to be tracked during driving.

[0107] The rear axle target tracking point refers to the specific position of the vehicle's rear axle that needs to be tracked during driving.

[0108] The front axle preview point refers to the preview position at a certain distance in front of the front axle during vehicle driving.

[0109] The rear axle preview point refers to the preview position at a certain distance in front of the rear axle during vehicle driving.

[0110] Combination Figure 1 The vehicle control device can obtain driving status information from the on-board sensor and can obtain planned path information from the data storage device.

[0111] S302: Determine target PID parameters of the vehicle's fuzzy PID controller according to the driving state information and the planned path information.

[0112] In one possible implementation, in order to improve the accuracy of the vehicle control device in controlling the vehicle, the vehicle control device determines the target PID parameters of the fuzzy PID controller according to the real-time driving state information and the planned path information, including: proportional coefficient, integral time constant, differential time constant, so that the result output by the fuzzy PID controller is more accurate. Then, the vehicle control device controls the vehicle to travel along the planned path according to the control parameters output by the fuzzy PID controller. Therefore, the vehicle control device can determine the target PID parameters of the fuzzy PID controller of the vehicle according to the driving state information and the planned path information.

[0113] Fuzzy PID controller is a control system that combines fuzzy control and PID control techniques.

[0114] The fuzzy PID controller includes: a fuzzy controller, a PID controller and a feedback signal.

[0115] The fuzzy controller adjusts the PID parameters of the PID controller in real time according to the input signal, and the PID controller determines the control parameters according to the adjusted PID parameters and the input signal.

[0116] In the embodiment of the present application, when the input signal is the deviation information of the longitudinal position and the deviation information of the speed, the control parameters include: motor torque and brake pressure. When the input signal is the deviation information of the lateral position of the front axle, the control parameters include: front wheel steering angle. When the input signal is the deviation information of the lateral position of the rear axle, the control parameters include: rear wheel steering angle.

[0117] Fuzzy control includes: fuzzified input, logical rules, database, fuzzy logic (also known as fuzzy reasoning) and understanding fuzziness.

[0118] The input quantity of fuzzification is referred to as fuzzy set.

[0119] The logic rules include: fuzzy control rules for longitudinal position, fuzzy control rules for speed, fuzzy control rules for lateral position of the front axle and fuzzy control rules for lateral position of the rear axle.

[0120] Fuzzy logic is a logical method for dealing with imprecise, uncertain and fuzzy information. Its input is a fuzzy set and its output is a definite result.

[0121] Among them, the fuzzy set includes: Negative Big (NB), Negative Medium (NM), Negative Small (NS), Zero (Zero), Positive Small (PS), Positive Medium (PM), Positive Big (PB), Positive Medium Small (PMS), and Positive Medium Big (PMB).

[0122] NB represents a very small negative value, NM represents a moderate negative value, NS represents a small negative value, Zero represents a value close to zero, PS represents a small positive value, PM represents a moderate positive value, PB represents a very large positive value, PMS represents a positive value between PS and PM, and PMB represents a positive value between PM and PB.

[0123] The PID controller performs proportional, integral and differential operations on the deviation and linearly combines the operation results to obtain control parameters.

[0124] The target PID parameters refer to the target proportional coefficient, target integral time constant, and target differential time constant in the PID controller.

[0125] S303: Determine the control parameters of the vehicle according to the driving state information, the planned path information and the target PID parameters.

[0126] In one achievable manner, in order to improve the accuracy of controlling the vehicle, the vehicle control device can adjust the target PID parameters of the fuzzy PID control according to the real-time driving state information and the planned path information. Therefore, after determining the target PID parameters of the fuzzy PID controller, the vehicle control device can determine the control parameters of the vehicle according to the driving state information, the planned path information and the target PID parameters, and control the vehicle to travel along the planned path according to the control parameters. Therefore, the vehicle control device can determine the control parameters of the vehicle according to the driving state information, the planned path information and the target PID parameters.

[0127] Control parameters include: motor torque, brake pressure, front wheel steering angle and rear wheel steering angle.

[0128] The vehicle control device can control the vehicle's driving speed and acceleration by adjusting the motor torque and brake pressure.

[0129] The vehicle control device can control the steering of the front wheels of the vehicle by adjusting the front wheel steering angle, and can control the steering of the rear wheels of the vehicle by adjusting the rear wheel steering angle.

[0130] S304: Control the vehicle to travel according to the control parameters.

[0131] In one achievable manner, after the control parameters are determined, the vehicle control device controls the vehicle to travel according to the control parameters so that the vehicle travels along the planned path.

[0132] In some embodiments, in combination Figure 3 ,like Figure 4 As shown, in S302, the target PID parameters of the fuzzy PID controller of the vehicle are determined according to the driving state information and the planned path information, specifically including:

[0133] S401. Determine deviation information according to driving state information and planned path information.

[0134] In one achievable manner, in order to improve the accuracy of controlling the vehicle, the vehicle control device determines the target PID parameters of the fuzzy PID controller according to the real-time driving state information and the planned path information. Since in the process of determining the target PID parameters by the vehicle control device, it is necessary to first determine the deviation information according to the driving state information and the planned path information, and determine the fuzzy coefficient corresponding to the deviation information, and then determine the target PID parameters according to the fuzzy coefficient. Therefore, the vehicle control device needs to determine the deviation information according to the driving state information and the planned path information.

[0135] The deviation information is used to indicate the deviation between the driving state information and the planned path information.

[0136] The deviation information includes: longitudinal position deviation information (also called longitudinal position deviation), front axle lateral position deviation information (also called front axle lateral deviation), rear axle lateral position deviation information (also called rear axle lateral deviation) and speed deviation information (also called longitudinal speed deviation).

[0137] For example, Figure 5 Figure 2 shows a schematic diagram of vehicle driving. Figure 5 As shown, the front axle center point is marked as F, the rear axle center point is marked as R, and the front axle target tracking point is marked as P f0 , the rear axle target tracking point is marked as P r0 , the front axis preview point is marked as P f , the rear axis preview point is marked as P r , the deviation information of the longitudinal position is marked as e y , the deviation information of the lateral position of the front axle is marked as e f , the deviation information of the lateral position of the rear axle is marked as e r .

[0138] Optionally, the vehicle control device can construct a vehicle coordinate system, in which the direction from the center point of the rear axle to the center of the front axle is the Y-axis, the front axle of the vehicle is the X-axis, and the center point of the front axle is the origin.

[0139] Optionally, the vehicle control device can construct a global coordinate system, which can take a certain intersection as the origin, the east-west direction as the X-axis, and the north-south direction as the Y-axis. Alternatively, the north-south direction can be the X-axis and the east-west direction can be the Y-axis.

[0140] Optionally, the global coordinate system may also be a coordinate system in a mapping software.

[0141] The data in the global coordinate system can be converted to and from the vehicle coordinate system.

[0142] For example, the vector in the global coordinate system Convert to a vector in the vehicle coordinate system This can be done in the following ways:

[0143] The vehicle control device can obtain the vehicle's yaw angle γ to obtain the transformation matrix A 10 , the transformation matrix A 10 Satisfies the following formula:

[0144]

[0145] Among them, cosγ is used to represent the cosine value of the yaw angle, and sinγ is used to represent the sine value of the yaw angle.

[0146] Then, the vehicle control device can With A 10 The product of is determined as Satisfies the following formula:

[0147]

[0148] Among them, A 10 is the transformation matrix, is a vector in the global coordinate system.

[0149] In some embodiments, the driving state information includes: a front axle center point, the planned path information includes: a front axle target tracking point, and the deviation information is determined according to the driving state information and the planned path information, including:

[0150] The difference between the front axle target tracking point and the front axle center point in the first direction is determined as the deviation information of the longitudinal position, and the difference between the front axle target tracking point and the front axle center point in the second direction is determined as the deviation information of the front axle lateral position, the first direction is used to indicate the direction in which the rear axle center point points to the front axle center point, and the first direction is perpendicular to the second direction.

[0151] Optionally, in the vehicle coordinate system, the first direction is the same as the Y-axis, and the second direction is the same as the X-axis.

[0152] Optional, combined Figure 5 , the deviation information of the longitudinal position satisfies the following formula:

[0153] e y (t) = y 0y (t)-y f (t);

[0154] Among them, y 0y (t) is used to represent the value of the front axle target tracking point on the Y axis in the vehicle coordinate system (it can also be a function that changes over time), f (t) is used to represent the value of the center point of the front axle on the Y-axis in the vehicle coordinate system (it can also be a function that changes over time).

[0155] Optional, combined Figure 5 , the deviation information of the lateral position of the front axle satisfies the following formula:

[0156] e f (t) = x f0 (t)-x f (t);

[0157] Among them, x f0 (t) is used to represent the value of the front axle target tracking point on the X axis in the vehicle coordinate system (it can also be a function that changes over time), x f (t) is used to represent the value of the center point of the front axle on the X-axis in the vehicle coordinate system (it can also be a function that changes over time).

[0158] In some embodiments, the driving state information includes: a rear axle center point, the planned path information includes: a rear axle target tracking point, and the deviation information is determined according to the driving state information and the planned path information, including:

[0159] The difference between the rear axle target tracking point and the rear axle center point in the second direction is determined as deviation information of the rear axle lateral position.

[0160] Optionally, in the vehicle coordinate system, the second direction is in the same direction as the X-axis.

[0161] Optional, combined Figure 5 , the deviation information of the lateral position of the rear axle satisfies the following formula:

[0162] e r (t) = x r0 (t)-x r (t);

[0163] Among them, x r0(t) is used to represent the value of the target tracking point on the rear axle on the X axis in the vehicle coordinate system (it can also be a function that changes over time), r (t) is used to represent the value of the center point of the rear axle on the X-axis in the vehicle coordinate system (it can also be a function that changes over time).

[0164] In some embodiments, the driving state information further includes: current driving speed, and the planned path information further includes: target driving speed. According to the driving state information and the planned path information, the deviation information is determined, including:

[0165] The difference between the target driving speed and the current driving speed is determined as speed deviation information.

[0166] Optionally, the longitudinal deviation information of the speed satisfies the following formula:

[0167] e vy (t) = V 0y (t)-V y (t);

[0168] Among them, V 0y (t) is used to represent the target driving speed (it can also be a function that changes over time), V y (t) is used to indicate the current speed of the vehicle (it can also be a function that changes over time).

[0169] S402: Determine a fuzzy coefficient according to the deviation information and a membership function corresponding to the deviation information.

[0170] In one possible implementation, in order to improve the accuracy of the vehicle control device in controlling the vehicle, the vehicle control device can determine the target PID parameter of the fuzzy PID controller based on the real-time driving state information and the planned path information. Since there is a definite relationship between the target PID parameter and the fuzzy coefficient, and there is a corresponding relationship between the deviation information and the fuzzy coefficient, that is, the membership function corresponding to the deviation information. Therefore, the vehicle control device can determine the fuzzy coefficient based on the deviation information and the membership function corresponding to the deviation information.

[0171] The membership function is a function used to describe the degree to which an element belongs to a fuzzy set.

[0172] In an embodiment of the present application, the precise deviation is input into the fuzzy PID controller, and the fuzzy PID controller can determine the fuzzy coefficient corresponding to the deviation according to the membership function.

[0173] The fuzzy coefficient is a parameter used to adjust the fuzzy rules or fuzzy reasoning in the fuzzy PID controller. The vehicle control device optimizes the performance of the fuzzy PID controller by adjusting the fuzzy coefficient.

[0174] In some embodiments, when the control parameter includes a longitudinal control parameter, the membership function includes a correspondence between deviation information and a fuzzy coefficient.

[0175] The membership function can be constructed by the vehicle control device.

[0176] The membership function for expressing the correspondence between the deviation information of the longitudinal position and the fuzzy coefficient is constructed in the following manner: First, the vehicle control device sets the fuzzy set of the deviation information of the longitudinal position to {NB z , N.M. z , NS z ,Zero z , P.S. z , PM z , P.B. z}, and quantize its domain to [-50, 50]. The vehicle control device converts the fuzzy coefficient u y The fuzzy set is set to {NBy, NM y , NS y ,Zero y , P.S. y , PM y , P.B. y}, and quantize its domain to [-10, 10].

[0177] Then, the vehicle control device calculates the longitudinal position deviation information e y Fuzzy sets and fuzzy coefficients u y The fuzzy control rule table corresponding to the fuzzy set is constructed to represent the deviation information e of the longitudinal position. y and the fuzzy coefficient u y The membership function of the corresponding relationship.

[0178] Among them, the fuzzy control rule table of the longitudinal position is shown in Table 1.

[0179] <![CDATA[e y ]]> <![CDATA[NB z ]]> <![CDATA[NM z ]]> <![CDATA[NS z ]]> <![CDATA[Zero z ]]> <![CDATA[PS z ]]> <![CDATA[PM z ]]> <![CDATA[PB z ]]> <![CDATA[u y ]]> <![CDATA[NB y ]]> <![CDATA[NM y ]]> <![CDATA[NS y ]]> <![CDATA[Zero y ]]> <![CDATA[PS y ]]> <![CDATA[PM y ]]> <![CDATA[PB y ]]>

[0180] Table 1

[0181] The membership function is Figure 6 As shown, Figure 6 The deviation information and fuzzy coefficient u of the longitudinal position are shown y The membership function of .

[0182] Domain quantification refers to determining the value range of a fuzzy set.

[0183] In the embodiment of the present application, the vehicle control device can determine the fuzzy coefficient u corresponding to the deviation information of the longitudinal position according to the deviation information of the longitudinal position. y .

[0184] The membership function used to express the correspondence between the deviation information of the speed and the fuzzy coefficient is constructed in the following way:

[0185] First, the vehicle control device sets the fuzzy set of the speed deviation information to {NB v , NMv ， NS v ,Zero v , P.S. v , PM v , P.B. v}, and quantize its domain to [-50, 50]. The vehicle control device converts the fuzzy coefficient u a The fuzzy set is set to {NB a , N.M. a , NS a ,Zero a , P.S. a , PM a , P.B. a}, and quantize its domain to [-10, 10].

[0186] Then, the vehicle control device calculates the speed deviation information V y Fuzzy sets and fuzzy coefficients u a The fuzzy control rule table corresponding to the fuzzy set is constructed to represent the speed deviation information V y and the fuzzy coefficient u a The membership function of the corresponding relationship.

[0187] Among them, the fuzzy control rules table of speed is shown in Table 2.

[0188] <![CDATA[V y ]]> <![CDATA[NB v ]]> <![CDATA[NM v ]]> <![CDATA[NS v ]]> <![CDATA[Zero v ]]> <![CDATA[PS v ]]> <![CDATA[PM v ]]> <![CDATA[PB v ]]> <![CDATA[u a ]]> <![CDATA[NB a ]]> <![CDATA[NM a ]]> <![CDATA[NS a ]]> <![CDATA[Zero a ]]> <![CDATA[PS a ]]> <![CDATA[PM a ]]> <![CDATA[PB a ]]>

[0189] Table 2

[0190] The membership function is Figure 7 As shown, Figure 7 The deviation information of the speed and the fuzzy coefficient u are shown a The membership function of .

[0191] In the embodiment of the present application, the vehicle control device can determine the fuzzy coefficient u corresponding to the speed deviation information according to the speed deviation information. a .

[0192] In some embodiments, when the control parameters include lateral control parameters, the membership function includes a correspondence between deviation information, driving state information and fuzzy coefficients.

[0193] When the control parameters include lateral control parameters, and the lateral control parameters include the front wheel steering angle, the deviation information includes: deviation information of the lateral position of the front axle, the driving state information includes: current driving speed, and the membership function includes the deviation information of the lateral position of the front axle, the current driving speed and the correspondence between the fuzzy coefficient.

[0194] The membership function used to represent the correspondence between the deviation information of the lateral position of the front axle, the current driving speed and the fuzzy coefficient is constructed in the following way:

[0195] First, the vehicle control device sets the fuzzy set of the deviation information of the lateral position of the front axle to {NB f , N.M. f , NS f ,Zero f , P.S. f , PM f , P.B. f}, quantize its domain to [-50, 50], and set the quantization factor of the response. The vehicle control device sets the fuzzy set of the current driving speed to {PS u , PMS u , PM u ,PMB u , P.B. u}, quantizes its domain to [-40, 40], and sets the quantization factor of the response. The vehicle control device sets the fuzzy set of the fuzzy coefficient u1 to {NB1, NM1, NS1, Zero1, PS1, PM1, PB1}, and quantizes its domain to [-48, 48].

[0196] Optionally, the quantization factor is a coefficient used to map the input variable to the domain, which can reduce or enlarge the actual value range of the input variable to the range of the domain according to a certain ratio.

[0197] For example, the actual value range of the deviation information of the front axle lateral position is [-100, 100], and the domain is set to [-48, 48]. When the time value of the deviation information of the front axle lateral position is 50, the actual deviation information of the front axle lateral position can be converted into a corresponding value of 24 in the domain through the quantization factor.

[0198] Then, the vehicle control device uses the deviation information e of the lateral position of the front axle f Fuzzy set of current driving speed V y The fuzzy control rule table corresponding to the fuzzy set of fuzzy coefficient u1 is constructed to represent the deviation information e of the lateral position of the front axle. f 、Current driving speed V y The membership function of the corresponding relationship with the fuzzy coefficient u1.

[0199] Among them, the membership function is as follows Figure 8 shown.

[0200] Figure 8 (a) shows the deviation information of the lateral position of the front axle f And the membership function of the fuzzy coefficient u1.

[0201] Figure 8 (b) shows the current driving speed V y And the membership function of the fuzzy coefficient u1.

[0202] Figure 8 (c) shows the deviation information of the lateral position of the front axle f 、Current driving speed V y and the joint control surface of the fuzzy coefficient u1.

[0203] The fuzzy control rules table of the front axle lateral position is shown in Table 3.

[0204]

[0205] Table 3

[0206] In the embodiment of the present application, the vehicle control device can determine the fuzzy coefficient u1 corresponding to the deviation information of the lateral position of the rear axle and the current driving speed based on the deviation information of the lateral position of the front axle and the current driving speed.

[0207] When the control parameters include lateral control parameters, and the lateral control parameters include the rear wheel steering angle, the deviation information includes: the deviation information of the lateral position of the rear axle, the driving state information includes: the sideslip angle of the center of mass, and the membership function includes the correspondence between the deviation information of the lateral position of the rear axle, the sideslip angle of the center of mass and the fuzzy coefficient.

[0208] The membership function used to represent the deviation information of the lateral position of the rear axle, the corresponding relationship between the center of mass sideslip angle and the fuzzy coefficient is constructed in the following way:

[0209] First, the vehicle control device sets the fuzzy set of the deviation information of the rear axle lateral position to {NB r , N.M. r , NS r ,Zero r , P.S. r , PM r , P.B. r}, and quantize its domain to [-50, 50]. The vehicle control device sets the fuzzy set of the center of mass sideslip angle to {NB z , N.M. z , NS z ,Zero z , P.S.z , PM z , P.B. z}, quantizes its domain to [-40, 40], and sets the quantization factor of the response. The vehicle control device sets the fuzzy set of the fuzzy coefficient u2 to {NB2, NM2, NS2, Zero2, PS2, PM2, PB2}, quantizes its domain to [-48, 48], and sets the quantization factor of the response.

[0210] Then, the vehicle control device uses the deviation information e of the rear axle lateral position to r The fuzzy control rule table corresponding to the fuzzy set of the fuzzy set of the center of mass side slip angle ZX and the fuzzy set of the fuzzy coefficient u2 is constructed to represent the deviation information e for the lateral position of the rear axle. r , the membership function of the corresponding relationship between the center of mass sideslip angle ZX and the fuzzy coefficient u2.

[0211] Among them, the membership function is as follows Fig. 9 shown.

[0212] Fig. 9 (a) shows the deviation information of the lateral position of the rear axle r And the membership function of the fuzzy coefficient u2.

[0213] Fig. 9 (b) in FIG. 5 shows the membership function of the sideslip angle ZX and the fuzzy coefficient u2.

[0214] Fig. 9 (c) shows the deviation information of the lateral position of the rear axle r , the joint control surface of the center of mass sideslip angle ZX and the fuzzy coefficient u2.

[0215] The fuzzy control rules table for the rear axle lateral direction is shown in Table 4.

[0216]

[0217] Table 4

[0218] In an embodiment of the present application, the vehicle control device can determine the fuzzy coefficient u2 corresponding to the deviation information of the lateral position of the rear axle and the sideslip angle of the center of mass based on the deviation information of the lateral position of the rear axle and the sideslip angle of the center of mass.

[0219] Different deviation information corresponds to different fuzzy coefficients, and the fuzzy coefficients are coefficients for determining target PID parameters.

[0220] S403: Determine the product of the fuzzy coefficient and the initial PID parameter of the fuzzy PID controller as the target PID parameter of the fuzzy PID controller.

[0221] In one possible implementation, in order to improve the accuracy of the vehicle control device in controlling the vehicle, the vehicle control device can determine the target PID parameters of the fuzzy PID controller based on the real-time driving state information and the planned path information. Since there is a definite relationship between the target PID parameters and the fuzzy coefficients, the vehicle control device can determine the product of the fuzzy coefficients and the initial PID parameters of the fuzzy PID controller as the target PID parameters of the fuzzy PID controller.

[0222] In some embodiments, in combination Figure 4 ,like Fig.10 As shown, in S303, the control parameters of the vehicle are determined according to the driving state information, the planned path information and the target PID parameters, specifically including:

[0223] S1001. Determine compensation information of a target driving state according to deviation information and target PID parameters.

[0224] In a feasible manner, in order to improve the accuracy of controlling the vehicle, the vehicle control device can adjust the target PID parameters of the fuzzy PID control according to the real-time driving state information and the planned path information. Therefore, after determining the target PID parameters of the fuzzy PID controller, the vehicle control device can determine the control parameters of the vehicle according to the driving state information, the planned path information and the target PID parameters. Since in the process of the vehicle control device determining the control parameters, the vehicle control device only determines the control parameters based on the target driving state, which is inaccurate. Therefore, the vehicle control device can first determine the compensation information of the target driving state according to the deviation information and the target PID parameters, and compensate the target driving state to determine the control parameters of the vehicle according to the compensated target driving state. Therefore, the vehicle control device can determine the compensation information of the target driving state according to the deviation information and the target PID parameters.

[0225] Optionally, the target driving state includes: a target driving speed, a target acceleration, a front wheel preview turning angle, and a rear wheel preview turning angle.

[0226] The compensation information includes: compensation speed, compensation acceleration, front wheel compensation angle and rear wheel compensation angle.

[0227] S1002: Compensate the target driving state according to the compensation information, and determine the control parameters of the vehicle according to the compensated target driving state.

[0228] In one practicable manner, after determining the compensation information, the vehicle control device can compensate for the target driving state according to the compensation information, and determine the control parameters of the vehicle according to the compensated target driving state.

[0229] In some embodiments, in combination Fig.10 ,like Fig.11 As shown, the deviation information includes: deviation information of longitudinal position and deviation information of speed, the compensation information includes: compensation speed and compensation acceleration, the control parameters include: motor torque and brake pressure, the driving state information includes: motor speed, the target driving state includes: target driving speed and target acceleration, in S1002, the target driving state is compensated according to the compensation information, and the control parameters of the vehicle are determined according to the compensated target driving state, which specifically include:

[0230] S1101. Compensate the target driving speed according to the compensation speed to obtain a compensated target driving speed, and compensate the target acceleration according to the compensation acceleration to obtain a compensated target acceleration.

[0231] In one achievable manner, in the process of the vehicle control device determining the control parameters, the vehicle control device determines the control parameters inaccurately only based on the target driving state. Therefore, after determining the compensation information, the vehicle control device can compensate the target driving state according to the compensation information, and determine the control parameters of the vehicle according to the compensated target driving state. The compensation information includes: compensation speed, compensation acceleration, the target driving state includes: target driving speed, target acceleration, the vehicle control device can compensate the target driving speed according to the compensation speed to obtain the compensated target driving speed, and compensate the target acceleration according to the compensation acceleration to obtain the compensated target acceleration.

[0232] The compensation speed satisfies the following formula:

[0233]

[0234] Among them, e y (t) is used to indicate the deviation information of the longitudinal position, K p1 Used to express the proportionality factor, T i1 Used to represent the integration time constant, T d1 Used to represent the differential time constant.

[0235] The vehicle control device determines a compensated target traveling speed based on the compensation speed and the target traveling speed.

[0236] Optionally, the vehicle control device may determine the sum of the compensation speed and the target driving speed as the compensated target driving speed.

[0237] Optionally, the vehicle control device determines the product of the compensation speed and the compensation weight coefficient, and the product of the target driving speed and the target weight coefficient, respectively, and determines the sum of the products as the compensated target driving speed.

[0238] The compensation acceleration satisfies the following formula:

[0239]

[0240] Among them, e vy (t) is used to indicate the deviation information of speed, K p2 Used to express the proportionality factor, T i2 Used to represent the integration time constant, T d2 Used to represent the differential time constant.

[0241] The vehicle control device determines a compensated target acceleration based on the compensation acceleration and the target acceleration.

[0242] Optionally, the vehicle control device may determine the sum of the compensation acceleration and the target acceleration as the compensated target driving speed.

[0243] Optionally, the vehicle control device determines the product of the compensation acceleration and the compensation weight coefficient, and the product of the target acceleration and the target weight coefficient, respectively, and determines the sum of the products as the compensated target acceleration.

[0244] S1102: Determine the throttle depth and brake pressure of the vehicle according to the compensated target driving speed, the compensated target acceleration, the corresponding relationship between the motion parameters and the control parameters.

[0245] In one achievable method, after the vehicle control device determines the compensated target driving speed and target acceleration, the vehicle control device can determine the vehicle's throttle depth and braking pressure based on the corresponding relationship between the compensated target driving speed, the compensated target acceleration, motion parameters and control parameters.

[0246] The motion parameters include compensation velocity and compensation acceleration.

[0247] Control parameters include throttle depth and brake pressure.

[0248] The correspondence between motion parameters and control parameters (also called throttle-brake combined calibration table) includes: the correspondence between motion parameters and throttle depth (also called throttle calibration table) and the correspondence between motion parameters and brake pressure (also called brake calibration table).

[0249] The correspondence between the motion parameters and the control parameters can be constructed through the vehicle control device.

[0250] The correspondence between motion parameters and throttle depth is constructed in the following way:

[0251] First, the vehicle control device sets the input quantity of the vehicle dynamics model to the motor torque and brake pressure, and sets the output quantity to the driving speed, acceleration and motor speed.

[0252] Then, the vehicle control device sets the brake pressure to 0, sets the throttle depth to a variable, with an initial throttle depth of 0 and a maximum throttle depth of 1, and sets the initial speed to 0.

[0253] Next, the vehicle control device determines the driving speed and acceleration corresponding to different throttle depths by cyclically calling the throttle calibration algorithm. The throttle depth is a variable, and the throttle depth increases by 0.05 each time the cycle is called 20 times in total.

[0254] Finally, the vehicle control device obtains the corresponding relationship between the motion parameters and the throttle depth, that is, the throttle calibration table.

[0255] The corresponding relationship between motion parameters and brake pressure is constructed in the following way:

[0256] First, the vehicle control device sets the input quantity of the vehicle dynamics model to the motor torque and brake pressure, and sets the output quantity to the driving speed, acceleration and motor speed.

[0257] Then, the vehicle control device sets the motor torque to 0, sets the brake pressure to a variable, the initial brake pressure to 0, the maximum brake pressure to 8MPa, and sets the initial speed to 180km / h.

[0258] Next, the vehicle control device determines the driving speed and acceleration corresponding to different brake pressures by cyclically calling the brake calibration algorithm. The brake pressure is a variable, and the brake pressure increases by 0.1Mpa each time, and the cycle is called 80 times in total.

[0259] The vehicle control device can fit the throttle calibration table and the brake calibration table into one calibration table, namely, the throttle brake combined calibration table, based on the throttle brake combined algorithm in the Matrix Laboratory (MATLAB).

[0260] Exemplarily, first, the vehicle control device can set the input quantity of the throttle-brake joint calibration table to the driving speed and acceleration, the intermediate output quantity is a positive signal and a negative signal, the intermediate input quantity is the motor speed, and the output quantity is set to the brake pressure and the motor torque. Then, the vehicle control device can set the throttle depth corresponding to the driving speed and acceleration to a positive signal, and set the throttle depth corresponding to the driving speed and acceleration to a negative signal. Next, the vehicle control device inputs the driving speed and acceleration into the throttle-brake joint calibration table, and when the intermediate output quantity is a positive signal, inputs the motor speed, determines the throttle depth, and calls the throttle calibration table, and finally outputs the motor torque. The vehicle control device inputs the driving speed and acceleration into the throttle-brake joint calibration table, and when the intermediate output quantity is a negative signal, calls the brake calibration table, and the final output quantity is the brake pressure.

[0261] From the above, it can be seen that the vehicle control device calls the throttle and brake joint calibration table to avoid the call logic problem and control discontinuity problem caused by the improper transition adjustment of the throttle calibration table and the brake calibration table. It can also avoid the vehicle speed oscillation problem caused by adjusting the throttle depth immediately after the brake pressure reaches the extreme.

[0262] S1103: Determine the motor torque of the vehicle according to the throttle depth and the motor speed.

[0263] In one achievable manner, the motor torque is related to the throttle depth and the motor speed. Therefore, after the vehicle control device determines the throttle depth, the motor torque of the vehicle can be determined based on the throttle depth and the motor speed.

[0264] The motor torque satisfies the following formula:

[0265]

[0266] Among them, T is used to represent the motor torque, thr is used to represent the throttle depth, n is used to represent the motor speed, and n i For presetting the speed.

[0267] Preset speed n i Satisfies the following formula:

[0268]

[0269] Among them, P max Used to indicate the maximum power of the motor, T max Used to indicate the maximum torque of the motor.

[0270] For example, when the maximum power of the motor is 180KW and the maximum torque of the motor is 380N·m, the preset speed n i It is 4523rad / min.

[0271] Optionally, the motor power satisfies the following formula:

[0272] P(t) = T(t)n(t) / 9550;

[0273] Among them, T(t) is used to represent the motor torque, and n(t) is used to represent the motor speed.

[0274] Optionally, the motor power also satisfies the following formula:

[0275] P(t)=T(t)W(t);

[0276] Among them, T(t) is used to represent the motor torque and W(t) is used to represent the angular velocity.

[0277] Therefore, when n <n iWhen the throttle depth remains unchanged, the motor torque is a constant value. i And when the throttle depth remains unchanged, the motor power is a constant value.

[0278] In some embodiments, in combination Fig.11 ,like Fig.12 As shown, the deviation information includes: the deviation information of the lateral position of the front axle, the driving state information includes: the center point of the front axle, the planned path information includes: the front axle target tracking point and the front axle preview point, the target driving state includes: the front wheel preview angle, the compensation information includes: the front wheel compensation angle, and the control parameters include: the front wheel steering angle. In S1002, the target driving state is compensated according to the compensation information, and the control parameters of the vehicle are determined according to the compensated target driving state, which specifically include:

[0279] S1201. Determine a direction vector from the front axle center point to the front axle target tracking point as the front axle target direction vector.

[0280] In one achievable manner, in the process of determining the control parameters by the vehicle control device, the vehicle control device determines the control parameters inaccurately only based on the target driving state. Therefore, after determining the compensation information, the vehicle control device can compensate for the target driving state based on the compensation information, and determine the control parameters of the vehicle based on the compensated target driving state. The compensation information includes: the front wheel compensation angle, and the target driving state includes: the front wheel preview angle. The vehicle control device needs to determine the front wheel preview angle first. In the process of determining the front wheel preview angle, the vehicle control device can determine the direction vector from the center point of the front axle to the front axle target tracking point as the front axle target direction vector.

[0281] For example, Fig.13 Another driving schematic diagram of a vehicle is shown. Fig.13 As shown, the front axle center point is marked as F, the rear axle center point is marked as R, and the front axle target tracking point is marked as P f0 , the rear axle target tracking point is marked as P r0 , the front axis preview point is marked as P f , the rear axis preview point is marked as P r The distance between the front axle center point and the front axle preview point in the Y-axis direction of the vehicle coordinate system is the preview distance d fp .

[0282] Optionally, the front axle preview point is determined based on the preview distance. In this way, when determining the front axle preview point, both the deviation information of the lateral position of the front axle and the heading deviation from the target tracking point are considered, which is more feasible.

[0283] Combination Fig.13, the vehicle control device can determine the direction vector from the front axle center point to the front axle target tracking point as the front axle target direction vector, and mark the front axle target direction vector as Front axis target direction vector Satisfies the following formula:

[0284]

[0285] Among them, X f (t) is used to represent the horizontal coordinate of the front axis target tracking point in the global coordinate system, X of (t) is used to represent the horizontal coordinate of the center point of the front axle in the global coordinate system, Y f (t) is used to represent the ordinate of the front axis target tracking point in the global coordinate system, Y of (t) is used to represent the ordinate of the center point of the front axle in the global coordinate system.

[0286] Optional, X f (t) can also be used to represent the horizontal coordinate of the front axle target tracking point in the vehicle coordinate system, X of (t) can also be used to represent the horizontal coordinate of the center point of the front axle in the vehicle coordinate system, Y f (t) can also be used to represent the ordinate of the front axle target tracking point in the vehicle coordinate system, Y of (t) can also be used to represent the longitudinal coordinate of the center point of the front axle in the vehicle coordinate system.

[0287] S1202: Determine a direction vector from the center point of the front axle to the front axle preview point as the front axle preview direction vector.

[0288] In one practicable manner, the vehicle control device may also determine a direction vector from the front axle center point to the front axle preview point as the front axle preview direction vector during the process of determining the front wheel preview turning angle.

[0289] Combination Fig.13 , the vehicle control device may determine the direction vector from the center point of the front axle to the front axle preview point as the front axle preview direction vector, and mark the front axle preview direction vector as Front axis preview direction vector Satisfies the following formula:

[0290]

[0291] Among them, X f_tray (t) is used to represent the horizontal coordinate of the front axis preview point in the global coordinate system, X of (t) is used to represent the horizontal coordinate of the center point of the front axle in the global coordinate system, Y f_tray (t) is used to represent the ordinate of the front axis preview point in the global coordinate system, Y of(t) is used to represent the ordinate of the center point of the front axle in the global coordinate system.

[0292] Optional, X f_tray (t) can also be used to represent the horizontal coordinate of the front axle preview point in the vehicle coordinate system, X of (t) can also be used to represent the horizontal coordinate of the center point of the front axle in the vehicle coordinate system, Y f_tray (t) can also be used to represent the ordinate of the front axle preview point in the vehicle coordinate system, Y of (t) can also be used to represent the longitudinal coordinate of the center point of the front axle in the vehicle coordinate system.

[0293] S1203: Determine the front wheel preview angle according to the front axle target direction vector and the front axle preview direction vector.

[0294] In one practicable manner, during the process of determining the front wheel preview angle, after determining the front axle target direction vector and the front axle preview direction vector, the vehicle control device can determine the front wheel preview angle based on the relationship between the two vectors.

[0295] Combination Fig.13 , the vehicle control device can set the front axle target direction vector and the front axis preview direction vector The vector sum is determined as Satisfies the following formula:

[0296]

[0297] in, Used to represent the front axis target direction vector, Used to represent the front axis preview direction vector.

[0298] Optionally, when the current axis target direction vector is larger, the vector sum is biased toward the target direction vector, and when the current axis target direction vector is smaller, the vector sum is biased toward the front axis preview direction vector.

[0299] Optional, in When the coordinates are calculated in the global coordinate system, the vehicle control device can obtain the coordinates in the vehicle coordinate system according to the conversion formula between the global coordinate system and the vehicle coordinate system. Satisfies the following formula:

[0300]

[0301] Among them, A 10 is the transformation matrix, is the vector sum in the global coordinate system.

[0302] The vehicle control device combines the vector sum with The angle between the Y axis and the vehicle coordinate system is determined as the front wheel preview angle δ 11 Front wheel preview angle δ 11 Satisfies the following formula:

[0303]

[0304] in, Used to represent the value of a vector on the Y axis. Used to represent the value of a vector on the X-axis.

[0305] S1204: Compensate the front wheel preview angle according to the front wheel compensation angle, and determine the compensated front wheel preview angle as the front wheel steering angle.

[0306] In one achievable manner, during the process of the vehicle control device determining the control parameters, the vehicle control device determines the control parameters inaccurately only based on the target driving state. Therefore, after determining the compensation information, the vehicle control device can compensate for the target driving state based on the compensation information, and determine the control parameters of the vehicle based on the compensated target driving state. The compensation information includes: the front wheel compensation angle, the target driving state includes: the front wheel preview angle, and the vehicle control device also needs to determine the front wheel compensation angle first. Then, the vehicle control device compensates the front wheel preview angle based on the front wheel compensation angle. Next, the vehicle control device determines the compensated front wheel preview angle as the front wheel steering angle.

[0307] Optional, deviation information of the lateral position of the front axle f (t) satisfies the following formula:

[0308]

[0309] Among them, X f (t) is used to represent the horizontal coordinate of the front axis target tracking point in the global coordinate system, X of (t) is used to represent the horizontal coordinate of the center point of the front axle in the global coordinate system, Y f (t) is used to represent the ordinate of the front axis target tracking point in the global coordinate system, Y of (t) is used to represent the ordinate of the center point of the front axle in the global coordinate system.

[0310] The front wheel compensation angle satisfies the following formula:

[0311]

[0312] Among them, e f (t) is used to indicate the deviation information of the lateral position of the front axle, K p3 Used to express the proportionality factor, T i3 Used to represent the integration time constant, T d3Used to represent the differential time constant.

[0313] The vehicle control device can compensate the front wheel preview angle according to the front wheel compensation angle, and determine the compensated front wheel preview angle as the front wheel steering angle. The front wheel steering angle satisfies the following formula:

[0314] δ1(t)=w1δ 11 (t)+w2δ 12 (t);

[0315] Among them, δ 11 (t) is used to represent the front wheel preview angle, δ 12 (t) is used to represent the front wheel compensation steering angle, w1 is used to represent the weighted value of the front wheel preview steering angle, and w2 is used to represent the weighted value of the front wheel compensation steering angle.

[0316] In some embodiments, in combination Fig.12 ,like Fig.14 As shown, the deviation information includes: the deviation information of the lateral position of the rear axle, the driving state information includes: the center point of the rear axle, the planned path information includes: the rear axle target tracking point and the rear axle preview point, the target driving state includes: the rear wheel preview angle, the compensation information includes: the rear wheel compensation angle, and the control parameters include: the rear wheel steering angle. In S1002, the target driving state is compensated according to the compensation information, and the control parameters of the vehicle are determined according to the compensated target driving state, which specifically include:

[0317] S1401. Determine a direction vector from the rear axle center point to the rear axle target tracking point as the rear axle target direction vector.

[0318] In one achievable manner, in the process of determining the control parameters by the vehicle control device, the vehicle control device determines the control parameters inaccurately only based on the target driving state. Therefore, after determining the compensation information, the vehicle control device can compensate for the target driving state according to the compensation information, and determine the control parameters of the vehicle according to the compensated target driving state. The compensation information includes: the rear wheel compensation angle, and the target driving state includes: the rear wheel preview angle. The vehicle control device needs to determine the rear wheel preview angle first. In the process of determining the rear wheel preview angle, the vehicle control device can determine the direction vector of the rear axle center point pointing to the rear axle target tracking point as the rear axle target direction vector.

[0319] Combination Fig.13 , the vehicle control device can determine the direction vector from the rear axle center point to the rear axle target tracking point as the rear axle target direction vector, and mark the rear axle target direction vector as Rear axle target direction vector Satisfies the following formula:

[0320]

[0321] Among them, X r (t) is used to represent the horizontal coordinate of the target tracking point on the rear axis in the global coordinate system, X or (t) is used to represent the horizontal coordinate of the center point of the rear axle in the global coordinate system, Y r (t) is used to represent the ordinate of the target tracking point on the rear axle in the global coordinate system, Y or (t) is used to represent the ordinate of the center point of the rear axle in the global coordinate system.

[0322] Optional, X r (t) can also be used to represent the horizontal coordinate of the target tracking point on the rear axle in the vehicle coordinate system, X or (t) can also be used to represent the horizontal coordinate of the rear axle center point in the vehicle coordinate system, Y r (t) can also be used to represent the ordinate of the target tracking point on the rear axle in the vehicle coordinate system, Y or (t) can also be used to represent the longitudinal coordinate of the center point of the rear axle in the vehicle coordinate system.

[0323] S1402, determining a direction vector from the rear axle center point to the rear axle preview point as the rear axle preview direction vector.

[0324] In one practicable manner, the vehicle control device may also determine a direction vector from the rear axle center point to the rear axle preview point as the rear axle preview direction vector during the process of determining the rear wheel preview turning angle.

[0325] Combination Fig.13 , the vehicle control device can determine the direction vector from the rear axle center point to the rear axle preview point as the rear axle preview direction vector, and mark the rear axle preview direction vector as Rear axis preview direction vector Satisfies the following formula:

[0326]

[0327] Among them, X r_tray (t) is used to represent the horizontal coordinate of the rear axis preview point in the global coordinate system, X or (t) is used to represent the horizontal coordinate of the center point of the rear axle in the global coordinate system, Y r_tray (t) is used to represent the ordinate of the rear axis preview point in the global coordinate system, Y or (t) is used to represent the ordinate of the center point of the rear axle in the global coordinate system.

[0328] Optional, X r_tray (t) can also be used to represent the horizontal coordinate of the rear axle preview point in the vehicle coordinate system, X or (t) can also be used to represent the horizontal coordinate of the rear axle center point in the vehicle coordinate system, Yr_tray (t) can also be used to represent the ordinate of the rear axle preview point in the vehicle coordinate system, Y or (t) can also be used to represent the longitudinal coordinate of the center point of the rear axle in the vehicle coordinate system.

[0329] S1403: Determine a rear wheel preview angle according to the rear axle target direction vector and the rear axle preview direction vector.

[0330] In one practicable manner, during the process of determining the rear wheel preview angle, after determining the rear axle target direction vector and the rear axle preview direction vector, the vehicle control device can determine the rear wheel preview angle based on the relationship between the two vectors.

[0331] Combination Fig.13 , the vehicle control device can set the rear axle target direction vector and the rear axis preview direction vector The vector sum is determined as Satisfies the following formula:

[0332]

[0333] in, Used to represent the target direction vector of the rear axle, Used to represent the rear axis preview direction vector.

[0334] Optional, in When the coordinates are calculated in the global coordinate system, the vehicle control device can obtain the coordinates in the vehicle coordinate system according to the conversion formula between the global coordinate system and the vehicle coordinate system. Satisfies the following formula:

[0335]

[0336] Among them, A 10 is the transformation matrix, is the vector sum in the global coordinate system.

[0337] The vehicle control device combines the vector sum with The angle between the Y axis and the vehicle coordinate system is determined as the rear wheel preview angle δ 11 . Rear wheel preview turning angle δ 11 Satisfies the following formula:

[0338]

[0339] in, Used to represent the value of a vector on the Y axis. Used to represent the value of a vector on the X-axis.

[0340] S1404: Compensate the rear wheel preview angle according to the rear wheel compensation angle, and determine the compensated rear wheel preview angle as the rear wheel steering angle.

[0341] In one achievable manner, during the process of the vehicle control device determining the control parameters, the vehicle control device determines the control parameters inaccurately only based on the target driving state. Therefore, after determining the compensation information, the vehicle control device can compensate for the target driving state based on the compensation information, and determine the control parameters of the vehicle based on the compensated target driving state. The compensation information includes: the rear wheel compensation angle, the target driving state includes: the rear wheel preview angle, and the vehicle control device also needs to determine the rear wheel compensation angle first. Then, the vehicle control device compensates the rear wheel preview angle based on the rear wheel compensation angle. Next, the vehicle control device determines the compensated rear wheel preview angle as the rear wheel steering angle.

[0342] Optional, information on the deviation of the lateral position of the rear axle r (t) satisfies the following formula:

[0343]

[0344] Among them, X r (t) is used to represent the horizontal coordinate of the target tracking point on the rear axis in the global coordinate system, X or (t) is used to represent the horizontal coordinate of the center point of the rear axle in the global coordinate system, Y r (t) is used to represent the ordinate of the target tracking point on the rear axle in the global coordinate system, Y or (t) is used to represent the ordinate of the center point of the rear axle in the global coordinate system.

[0345] The rear wheel compensation angle satisfies the following formula:

[0346]

[0347] Among them, e r (t) is used to indicate the deviation information of the lateral position of the rear axle, K p4 Used to express the proportionality factor, T i4 Used to represent the integration time constant, T d4 Used to represent the differential time constant.

[0348] The vehicle control device can compensate the rear wheel preview angle according to the rear wheel compensation angle, and determine the compensated rear wheel preview angle as the rear wheel steering angle. The rear wheel steering angle satisfies the following formula:

[0349] δ2(t)=w1δ 21 (t)+w2δ 22 (t);

[0350] Among them, δ 21(t) is used to represent the rear wheel preview angle, δ 22 (t) is used to represent the rear wheel compensation steering angle, w1 is used to represent the weighted value of the rear wheel preview steering angle, and w2 is used to represent the weighted value of the rear wheel compensation steering angle.

[0351] The above vehicle control method can be applied to a four-wheel steering (4WS) vehicle. The front axle of the 4WS vehicle can be driven under the control of the driver or under the control of the vehicle control device.

[0352] Optionally, after the vehicle control device determines the accelerator depth and the brake pressure, the vehicle's execution layer can control the vehicle's driving according to the accelerator depth and the brake pressure.

[0353] Optionally, after the vehicle control device determines the front wheel steering angle and the rear wheel steering angle, the vehicle's Electric Power Steering (EPS) system can control the vehicle steering according to the front wheel steering angle and the rear wheel steering angle.

[0354] Optional, Fig.15 A schematic diagram of a process for a vehicle control device to determine a vehicle longitudinal control parameter is shown.

[0355] The fuzzy PID controller includes: longitudinal position fuzzy PID controller and speed fuzzy PID controller.

[0356] Among them, the longitudinal position fuzzy PID controller determines the compensation speed according to the deviation information of the longitudinal position.

[0357] The speed fuzzy PID controller determines the compensation acceleration according to the speed deviation information.

[0358] Combination Figure 1 First, the vehicle control device can obtain driving status information (including: front axle center point, current driving speed and motor speed) from the vehicle-mounted sensor, and the vehicle control device can obtain upper-level planned path information (including: upper-level planned path includes: path planning information and target driving status, path planning information includes: front axle target tracking point) from the data storage device.

[0359] Then, the vehicle control device determines the compensation speed according to the front axle target tracking point, the front axle center point and the longitudinal position fuzzy PID controller.

[0360] Next, the vehicle control device determines the compensation acceleration according to the current driving speed, the target driving speed and the speed fuzzy PID controller.

[0361] In this way, the vehicle control device can determine the longitudinal control parameters.

[0362] Next, the vehicle control device determines the motor torque and brake pressure according to the target driving speed, target acceleration, compensation speed, compensation acceleration, motor speed and throttle brake joint calibration table to control the vehicle.

[0363] Optional, Fig.16 A schematic diagram of a process for a vehicle control device to determine a vehicle lateral control parameter is shown.

[0364] The fuzzy PID controller includes: a front axle lateral position fuzzy PID controller and a rear axle lateral position fuzzy PID controller.

[0365] Among them, the front axle lateral position fuzzy PID controller determines the front wheel compensation angle according to the deviation information of the front axle lateral position.

[0366] The rear axle lateral position fuzzy PID controller determines the rear wheel compensation angle based on the deviation information of the rear axle lateral position.

[0367] The vehicle control device can determine the target control value parameters in the front axle lateral position fuzzy PID controller according to the deviation information of the front axle lateral position and the current driving speed, and determine the front wheel steering angle according to the deviation information of the front axle lateral position and the preview distance.

[0368] The vehicle control device determines the front wheel steering angle according to the deviation information of the lateral position of the front axle and the preview distance, specifically including:

[0369] The vehicle control device determines the front wheel compensation angle according to the deviation information of the lateral position of the front axle, and determines the front wheel preview angle according to the preview distance. Then, the vehicle control device determines the front wheel steering angle according to the front wheel compensation angle and the front wheel preview angle.

[0370] The vehicle control device can determine the target control value parameters in the rear axle lateral position fuzzy PID controller according to the deviation information of the rear axle lateral position and the sideslip angle of the center of mass, and determine the rear wheel steering angle according to the deviation information of the rear axle lateral position and the preview distance.

[0371] The vehicle control device determines the rear wheel steering angle according to the deviation information of the rear axle lateral position and the preview distance, specifically including:

[0372] The vehicle control device determines the rear wheel compensation angle according to the deviation information of the rear axle lateral position, and determines the rear wheel preview angle according to the preview distance. Then, the vehicle control device determines the rear wheel steering angle according to the rear wheel compensation angle and the rear wheel preview angle.

[0373] In this way, the vehicle control device can determine the lateral control parameters.

[0374] Optional, Fig.17 A schematic diagram of the process of controlling vehicle driving is shown.

[0375] The fuzzy PID controller includes: a double fuzzy PID longitudinal controller and a preview fuzzy PID lateral controller.

[0376] The dual fuzzy PID longitudinal controller combines the longitudinal position fuzzy PID controller and the speed fuzzy PID controller together, and can determine the vehicle's throttle depth and brake pressure based on the longitudinal position deviation information and the speed deviation information.

[0377] The preview fuzzy PID lateral controller is a combination of the front axle lateral position fuzzy PID controller and the rear axle lateral position fuzzy PID controller. The front wheel steering angle and the rear wheel steering angle of the vehicle can be determined according to the deviation information of the front axle lateral position and the deviation information of the rear axle lateral position.

[0378] Optionally, the vehicle control system may also include a positioning device, and the vehicle control device can obtain the front axle center point and the rear axle center point in the driving status information, as well as the front axle target tracking point, the front axle preview point, the rear axle target tracking point and the rear axle preview point in the planned path information from the positioning device.

[0379] Optionally, the on-board sensors can also obtain surrounding environment information.

[0380] The vehicle control device obtains surrounding environment information and driving status information from the on-board sensors, and determines the vehicle's throttle depth and brake pressure based on the dual fuzzy PID longitudinal controller and the throttle-brake joint calibration table. The vehicle can also determine the motor torque based on the throttle depth and motor speed.

[0381] The vehicle control device can also obtain driving state information and planned path information from the positioning device, and determine the front wheel steering angle and the rear wheel steering angle based on the preview fuzzy PID lateral controller.

[0382] The vehicle control device can control the vehicle according to the motor torque, brake pressure, front wheel steering angle and rear wheel steering angle.

[0383] From the above, it can be seen that the vehicle control device controls the vehicle driving according to the vehicle control method to improve the control accuracy, stability and steering flexibility, improve driving safety and riding comfort, and reduce the degree of tire wear caused by steering.

[0384] For example, the relevant parameters of the vehicle include: the mass of the vehicle is 1270 kg, the wheelbase is 2910 mm, the radius of the front axle tire is 334 mm, the radius of the rear wheel tire is 334 mm, and the moment of inertia about the x-axis is 536.6 kg·m 2 The moment of inertia around the y-axis is 1536.7 kg·m 2 The moment of inertia around the z-axis is 1536.7 kg·m 2In the case of a vehicle that is not in a predetermined range, the embodiment of the present application further provides a method for controlling the vehicle to start driving on the planned path A from an initial driving speed of 10 km / h using a vehicle control method. The vehicle control device collects vehicle driving speed data, speed deviation information, actual driving route, longitudinal position deviation information, front wheel steering angle and other data in real time, and draws a curve of the above data changing over time.

[0385] Among them, the planned path A is a straight road.

[0386] Fig.18 A graph showing vehicle data changing over time is shown.

[0387] in, Fig.18 (a) in the figure shows the curve of the actual driving speed and the planned driving speed of the vehicle changing with time.

[0388] Fig.18 (b) in FIG. 1 shows a curve showing the variation of the deviation information of the vehicle speed with time.

[0389] Fig.18 (c) in the figure shows the curve of the actual driving route and the planned driving route of the vehicle changing over time.

[0390] Fig.18 (d) in the figure shows a curve showing the variation of the deviation information of the longitudinal position of the vehicle with time.

[0391] Depend on Fig.18 It can be seen that the vehicle control device controls the vehicle driving, and the deviation information of the longitudinal position is controlled within 0.16m, and the deviation information of the speed is controlled within 0.15m / s. The safety and riding comfort of the vehicle can be improved.

[0392] As another example, the relevant parameters of the vehicle include: the mass of the vehicle is 1270 kg, the wheelbase is 2910 mm, the radius of the front axle tire is 334 mm, the radius of the rear wheel tire is 334 mm, and the moment of inertia about the x-axis is 536.6 kg·m 2 The moment of inertia around the y-axis is 1536.7 kg·m 2 The moment of inertia around the z-axis is 1536.7 kg·m 2 In the case of a vehicle that is in a predetermined path B and has a speed of 25 km / h, the embodiment of the present application also provides a method for controlling the vehicle to travel along the planned path B at a speed of 25 km / h. The vehicle control device collects data such as the rear wheel steering angle, steering wheel angle, deviation information of the lateral position of the front axle, deviation information of the lateral position of the rear axle, sideslip angle of the center of mass, lateral force on the front wheel, and lateral force on the rear wheel in real time, and draws a curve of the above data changing with time.

[0393] The planned path B is a path composed of straight line segments, arc segments with different turning radii, and lane changes, and the road adhesion coefficient of the planned path B is 0.85.

[0394] Fig.19 A graph showing vehicle data changing over time is shown.

[0395] in, Fig.19 (a) in the figure shows the curve of the vehicle's front wheel steering angle changing with time.

[0396] Fig.19 (b) in the figure shows the curve of the vehicle rear wheel steering angle changing with time.

[0397] Fig.19 (c) in the figure shows the curve of the vehicle steering wheel angle changing with time.

[0398] Fig.19 (d) in the figure shows a curve showing the variation of the deviation information of the lateral position of the front axle of the vehicle with time.

[0399] Fig.19 (e) in the figure shows a curve showing the variation of the deviation information of the lateral position of the rear axle of the vehicle with time.

[0400] Fig.19 (f) in the figure shows the curve of the vehicle's center of mass sideslip angle changing with time.

[0401] Fig.19 (g) in FIG. 1 shows a curve of the lateral force on the front wheels of the vehicle changing with time.

[0402] Fig.19 (h) in the figure shows the curve of the lateral force on the rear wheels of the vehicle changing with time.

[0403] Depend on Fig.19 It can be seen that the vehicle control device controls the vehicle's driving, the deviation information of the lateral position of the front axle is controlled within 0.1m, and the vehicle's center of mass side slip angle is controlled within 4°. This can improve the stability of the vehicle and control the lateral force on the tire within a smaller range, reducing tire wear.

[0404] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. In order to realize the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware 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 exceed the scope of the present application.

[0405] The embodiment of the present application can divide the functional modules of the vehicle control device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. Optionally, the division of modules in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0406] Fig. 20 FIG. 1 is a schematic diagram showing the structure of a vehicle control device provided in an embodiment of the present application. Fig. 20 As shown, the vehicle control device includes: a communication unit 2001 and a processing unit 2002.

[0407] The communication unit 2001 is used to obtain the driving state information and the planned path information of the vehicle; the processing unit 2002 is used to determine the target PID parameters of the fuzzy proportional integral differential PID controller of the vehicle according to the driving state information and the planned path information; the processing unit 2002 is also used to determine the control parameters of the vehicle according to the driving state information, the planned path information and the target PID parameters; the processing unit 2002 is also used to control the driving of the vehicle according to the control parameters.

[0408] Optionally, the processing unit 2002 is specifically used to: determine deviation information based on driving status information and planned path information; the deviation information is used to indicate the deviation between the driving status information and the planned path information; determine the fuzzy coefficient based on the deviation information and the membership function corresponding to the deviation information; different deviation information corresponds to different fuzzy coefficients; the fuzzy coefficient is a coefficient for determining the target PID parameters; the product of the fuzzy coefficient and the initial PID parameters of the fuzzy PID controller is determined as the target PID parameters of the fuzzy PID controller.

[0409] Optionally, the driving status information includes: the center point of the front axle, and the planned path information includes: the front axle target tracking point; the processing unit 2002 is specifically used to: determine the difference between the front axle target tracking point and the front axle center point in the first direction as the deviation information of the longitudinal position, and determine the difference between the front axle target tracking point and the front axle center point in the second direction as the deviation information of the lateral position of the front axle; the first direction is perpendicular to the second direction.

[0410] Optionally, the driving status information includes: the rear axle center point, and the planned path information includes: the rear axle target tracking point; the processing unit 2002 is specifically used to: determine the difference between the rear axle target tracking point and the rear axle center point in the second direction as the deviation information of the rear axle lateral position.

[0411] Optionally, when the driving status information also includes: current driving speed, and the planned path information also includes: target driving speed, the processing unit 2002 is specifically used to: determine the difference between the target driving speed and the current driving speed as speed deviation information.

[0412] Optionally, when the control parameters include lateral control parameters and the lateral control parameters include the front wheel steering angle, the deviation information includes: the deviation information of the lateral position of the front axle; the driving status information includes: the current driving speed; the membership function includes the deviation information of the lateral position of the front axle, the current driving speed and the corresponding relationship between the fuzzy coefficient; when the control parameters include lateral control parameters and the lateral control parameters include the rear wheel steering angle, the deviation information includes: the deviation information of the lateral position of the rear axle; the driving status information includes: the sideslip angle of the center of mass; the membership function includes the deviation information of the lateral position of the rear axle, the corresponding relationship between the sideslip angle of the center of mass and the fuzzy coefficient.

[0413] Optionally, the processing unit 2002 is specifically used to: determine compensation information of the target driving state based on the deviation information and the target PID parameters; compensate the target driving state based on the compensation information, and determine the control parameters of the vehicle based on the compensated target driving state.

[0414] Optionally, the deviation information includes: deviation information of longitudinal position and deviation information of speed; the compensation information includes: compensation speed and compensation acceleration; the control parameters include: motor torque and brake pressure; the driving state information includes: motor speed; the target driving state includes: target driving speed and target acceleration; the processing unit 2002 is specifically used to: compensate the target driving speed according to the compensation speed to obtain the compensated target driving speed, and compensate the target acceleration according to the compensation acceleration to obtain the compensated target acceleration; determine the throttle depth and brake pressure of the vehicle according to the compensated target driving speed, the compensated target acceleration, the correspondence between the motion parameters and the control parameters; the motion parameters include compensation speed and compensation acceleration; the control parameters include throttle depth and brake pressure; the correspondence between the motion parameters and the control parameters includes: the correspondence between the motion parameters and the throttle depth and the correspondence between the motion parameters and the brake pressure; determine the motor torque of the vehicle according to the throttle depth and the motor speed.

[0415] Optionally, the deviation information includes: deviation information of the lateral position of the front axle; the driving state information includes: the front axle center point; the planned path information includes: the front axle target tracking point and the front axle preview point; the target driving state includes: the front wheel preview angle; the compensation information includes: the front wheel compensation angle; the control parameters include: the front wheel steering angle; the processing unit 2002 is specifically used to: determine the direction vector pointing from the front axle center point to the front axle target tracking point as the front axle target direction vector; determine the direction vector pointing from the front axle center point to the front axle preview point as the front axle preview direction vector; determine the front wheel preview angle according to the front axle target direction vector and the front axle preview direction vector; compensate the front wheel preview angle according to the front wheel compensation angle, and determine the compensated front wheel preview angle as the front wheel steering angle.

[0416] Optionally, the deviation information includes: deviation information of the lateral position of the rear axle; the driving state information includes: the center point of the rear axle; the planned path information includes: the rear axle target tracking point and the rear axle preview point; the target driving state includes: the rear wheel preview angle; the compensation information includes: the rear wheel compensation angle; the control parameters include: the rear wheel steering angle; the processing unit 2002 is specifically used to: determine the direction vector pointing from the center point of the rear axle to the rear axle target tracking point as the rear axle target direction vector; determine the direction vector pointing from the center point of the rear axle to the rear axle preview point as the rear axle preview direction vector; determine the rear wheel preview angle according to the rear axle target direction vector and the rear axle preview direction vector; compensate the rear wheel preview angle according to the rear wheel compensation angle, and determine the compensated rear wheel preview angle as the rear wheel steering angle.

[0417] Optionally, when the control parameters include longitudinal control parameters, the membership function includes the correspondence between deviation information and fuzzy coefficients; when the control parameters include lateral control parameters, the membership function includes the correspondence between deviation information, driving state information and fuzzy coefficients.

[0418] An embodiment of the present application also provides a computer-readable storage medium, which includes computer-executable instructions. When the computer-executable instructions are executed on a computer, the computer executes the vehicle control method provided in the above embodiment.

[0419] An embodiment of the present application also provides a computer program, which can be directly loaded into a memory and contains software code. After being loaded and executed by a computer, the computer program can implement the vehicle control method provided in the above embodiment.

[0420] Those skilled in the art should be aware that in one or more of the above examples, the functions described in this application can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer-readable storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. Storage media can be any available media that can be accessed by general or special-purpose computers.

[0421] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0422] In several embodiments provided in the present application, it should be understood that the disclosed 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 modules or units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The unit described as a separate component may or may not be physically separated, and the component displayed as a unit may be a physical unit or multiple physical units, that is, it may be located in one place, or it may be distributed in multiple different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0423] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the general technology or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a ROM, a RAM, a disk, or an optical disk.

[0424] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A vehicle control method, characterized in that: The method comprises: Obtain the vehicle's driving status information and planned path information; Determining target PID parameters of a fuzzy proportional-integral-derivative PID controller of the vehicle according to the driving state information and the planned path information; Determining control parameters of the vehicle according to the driving state information, the planned path information and the target PID parameters; The vehicle is controlled to travel according to the control parameters.

2. The method according to claim 1, characterized in that The step of determining target PID parameters of the fuzzy PID controller of the vehicle according to the driving state information and the planned path information includes: Determining deviation information according to the driving state information and the planned path information; the deviation information is used to indicate the deviation between the driving state information and the planned path information; Determine a fuzzy coefficient according to the deviation information and a membership function corresponding to the deviation information; different deviation information corresponds to different fuzzy coefficients; the fuzzy coefficient is a coefficient for determining the target PID parameter; The product of the fuzzy coefficient and the initial PID parameter of the fuzzy PID controller is determined as the target PID parameter of the fuzzy PID controller.

3. The method according to claim 2, characterized in that The driving state information includes: a front axle center point, and the planned path information includes: a front axle target tracking point; and the deviation information is determined according to the driving state information and the planned path information, including: The difference between the front axle target tracking point and the front axle center point in the first direction is determined as the deviation information of the longitudinal position, and the difference between the front axle target tracking point and the front axle center point in the second direction is determined as the deviation information of the front axle lateral position; the first direction is used to indicate the direction in which the rear axle center point points to the front axle center point; the first direction is perpendicular to the second direction.

4. The method according to claim 3, characterized in that The driving state information includes: the rear axle center point, and the planned path information includes: the rear axle target tracking point; and the deviation information is determined according to the driving state information and the planned path information, including: The difference between the rear axle target tracking point and the rear axle center point in the second direction is determined as deviation information of the rear axle lateral position.

5. The method according to claim 2, characterized in that: The driving state information further includes: a current driving speed, and the planned path information further includes: a target driving speed; and the determining of the deviation information according to the driving state information and the planned path information includes: The difference between the target driving speed and the current driving speed is determined as speed deviation information.

6. The method according to claim 2, characterized in that In the case where the control parameter includes a lateral control parameter, and the lateral control parameter includes a front wheel steering angle, the deviation information includes: deviation information of a lateral position of a front axle; the driving state information includes: a current driving speed; the membership function includes a correspondence between the deviation information of the lateral position of the front axle, the current driving speed and the fuzzy coefficient; When the control parameter includes the lateral control parameter, and the lateral control parameter includes the rear wheel steering angle, the deviation information includes: the deviation information of the lateral position of the rear axle; the driving state information includes: the sideslip angle of the center of mass; the membership function includes the deviation information of the lateral position of the rear axle, the corresponding relationship between the sideslip angle of the center of mass and the fuzzy coefficient.

7. The method according to claim 2, characterized in that: The determining the control parameters of the vehicle according to the driving state information, the planned path information and the target PID parameters includes: Determining compensation information of a target driving state according to the deviation information and the target PID parameter; The target driving state is compensated according to the compensation information, and the control parameters of the vehicle are determined according to the compensated target driving state.

8. The method according to claim 7, characterized in that The deviation information includes: deviation information of longitudinal position and deviation information of speed; the compensation information includes: compensation speed and compensation acceleration; the control parameters include: motor torque and brake pressure; the driving state information includes: motor speed; the target driving state includes: target driving speed and target acceleration; The compensating the target driving state according to the compensation information and determining the control parameters of the vehicle according to the compensated target driving state includes: Compensating the target driving speed according to the compensation speed to obtain a compensated target driving speed, and compensating the target acceleration according to the compensation acceleration to obtain a compensated target acceleration; Determine the throttle depth and brake pressure of the vehicle according to the compensated target driving speed, the compensated target acceleration, and the correspondence between the motion parameters and the control parameters; the motion parameters include the compensated speed and the compensated acceleration; the control parameters include the throttle depth and the brake pressure; the correspondence between the motion parameters and the control parameters includes: the correspondence between the motion parameters and the throttle depth and the correspondence between the motion parameters and the brake pressure; The motor torque of the vehicle is determined according to the throttle depth and the motor speed.

9. The method according to claim 7, characterized in that: The deviation information includes: deviation information of the lateral position of the front axle; the driving state information includes: the center point of the front axle; the planned path information includes: the front axle target tracking point and the front axle preview point; the target driving state includes: the front wheel preview angle; the compensation information includes: the front wheel compensation angle; the control parameter includes: the front wheel steering angle; The compensating the target driving state according to the compensation information and determining the control parameters of the vehicle according to the compensated target driving state includes: Determine a direction vector pointing from the front axle center point to the front axle target tracking point as a front axle target direction vector; Determine a direction vector pointing from the front axle center point to the front axle preview point as a front axle preview direction vector; Determining the front wheel preview angle according to the front axle target direction vector and the front axle preview direction vector; The front wheel preview angle is compensated according to the front wheel compensation angle, and the compensated front wheel preview angle is determined as the front wheel steering angle.

10. The method according to claim 7, characterized in that The deviation information includes: the deviation information of the lateral position of the rear axle; the driving state information includes: the center point of the rear axle; the planned path information includes: the rear axle target tracking point and the rear axle preview point; the target driving state includes: the rear wheel preview angle; the compensation information includes: the rear wheel compensation angle; the control parameter includes: the rear wheel steering angle; The compensating the target driving state according to the compensation information and determining the control parameters of the vehicle according to the compensated target driving state includes: Determine the direction vector of the rear axle center point pointing to the rear axle target tracking point as the rear axle target direction vector; Determine a direction vector pointing from the rear axle center point to the rear axle preview point as a rear axle preview direction vector; Determining the rear wheel preview angle according to the rear axle target direction vector and the rear axle preview direction vector; The rear wheel preview turning angle is compensated according to the rear wheel compensation turning angle, and the compensated rear wheel preview turning angle is determined as the rear wheel steering angle.

11. The method according to claim 2, characterized in that When the control parameters include longitudinal control parameters, the membership function includes the corresponding relationship between the deviation information and the fuzzy coefficient; when the control parameters include lateral control parameters, the membership function includes the corresponding relationship between the deviation information, the driving state information and the fuzzy coefficient.

12. A vehicle control device, characterized in that: The device comprises: a communication unit and a processing unit; The communication unit is used to obtain the driving state information and planned path information of the vehicle; The processing unit is used to determine the target PID parameters of the fuzzy proportional integral differential PID controller of the vehicle according to the driving state information and the planned path information; The processing unit is further used to determine the control parameters of the vehicle according to the driving state information, the planned path information and the target PID parameters; The processing unit is further used to control the driving of the vehicle according to the control parameters.

13. A vehicle control device, characterized in that: include: A processor and a memory; wherein the memory is used to store one or more programs, and the one or more programs include computer-executable instructions. When the device is running, the processor executes the computer-executable instructions stored in the memory to enable the device to perform the method described in any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that: When the computer-executable instructions stored in the computer-readable storage medium are executed by a processor of a vehicle control device, the vehicle control device is capable of performing the method according to any one of claims 1 to 11.

15. A computer program product, characterized in that The computer program product comprises: a computer program or instructions, and when the computer program or instructions are run on a computer, the computer is caused to perform the method according to any one of claims 1 to 11.

16. A vehicle, characterized in that: The vehicle is used to implement the method according to any one of claims 1 to 11.

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