Vehicle path tracking control method, device, readable storage medium and electronic device

Abstract

A method, device, readable storage medium and electronic device for controlling vehicle path tracking, the method comprising: determining the data packet receiving state of a predefined state variable according to real-time sensor data collection; determining whether the vehicle is under network attack at the current moment according to the data packet receiving state of the state variable at the current moment; if so, calculating the value of the control variable at the previous moment according to the data of the state variable at the previous moment; calculating the estimated value of the state variable at the current moment according to the calculated value of the control variable using the state estimation equation, and performing vehicle path tracking control according to the estimated value. The present invention can improve the network information security of intelligent networked vehicles, so that the vehicle still has a certain fault tolerance when encountering a network attack, and improves the path tracking performance of the vehicle.

Description

Technical Field

[0001] The present invention relates to the field of network control, and in particular to a vehicle path tracking control method, device, readable storage medium and electronic equipment. Background Art

[0002] Intelligent connected vehicles integrate modern network and communication technologies on the basis of traditional vehicles, which improves the transmission and processing speed of vehicle driving data, effectively improves the performance of vehicle components and the entire vehicle, and is the main development direction of future vehicles.

[0003] However, while network and communication technologies promote the intelligence and networking of automobiles, they also provide opportunities for cyber attacks. Since intelligent connected vehicles are open and shared, their control systems are vulnerable to malicious attacks, resulting in delays, disorder, missing and other undesirable phenomena in communication data interaction, which directly reduce the driving performance of the vehicle and even cause the vehicle to lose control, seriously affecting road traffic safety. Path tracking control is one of the keys to the realization of autonomous driving of intelligent connected vehicles. The accuracy of vehicle tracking and the handling stability determine the effect of path tracking. When intelligent connected vehicles are attacked by cyber attacks during path tracking, the accuracy of path tracking will inevitably be reduced, making the vehicle's autonomous driving function unprotected. Therefore, it is of great significance to solve the negative impact of cyber attacks on intelligent connected vehicles.

[0004] Currently, there are few studies on the control of intelligent connected vehicles considering cyber attacks. The relevant studies mainly involve vehicle path tracking control methods and target cyber attacks on general cyber-physical systems. The impact of cyber attacks on vehicle path tracking is not considered, and no research is conducted on the information security of vehicles. Summary of the invention

[0005] In view of the above situation, it is necessary to provide a vehicle path tracking control method, device, readable storage medium and electronic device to improve the network information security of intelligent connected vehicles, so that the vehicle still has a certain fault tolerance when encountering a network attack, and improves the vehicle's path tracking performance.

[0006] The present invention discloses a vehicle path tracking control method, comprising:

[0007] Determine the data packet receiving state of the predefined state variable according to the real-time data collected by the sensor;

[0008] Determine whether the vehicle is under a network attack at the current moment according to the data packet receiving state of the state variable at the current moment;

[0009] If so, the value of the control variable at the previous moment is calculated according to the data of the state variable at the previous moment;

[0010] According to the calculated value of the control variable, the estimated value of the state variable at the current moment is calculated using the state estimation equation, and the vehicle path tracking control is performed according to the estimated value.

[0011] Furthermore, in the above-mentioned vehicle path tracking control method, the calculation formula of the estimated value of the state variable at the current moment is:

[0012]

[0013] Where, Λ(k-1)=[∑(k-1) -1 +α k-1 C T N -1 C-γ -2 Q] -1 ,

[0014]

[0015]

[0016] γ is the interference suppression degree, k1 and k2 are the front and rear wheel cornering stiffness, a and b are the distances from the center of mass to the front and rear axles, I Z is the yaw moment of inertia, N is the strategy space of player 2, Q is the positive definite weight matrix, u(k-1) is the control variable at time k-1, x(k-1) is the state variable at time k-1, is the estimated value of the state variable at time k.

[0017] Furthermore, in the above-mentioned vehicle path tracking control method, the calculation formula of the value of the control variable at the previous moment is:

[0018] u(k-1)=-B T Γ(k-1)A(I-γ -2 ∑(k-1)M(k-1)) -1 x(k-1),

[0019] Where Γ(k-1)=[M(k-1) -1 +BB T -γ -2 DD T ] -1 , M(k-1)=A T [M(k-1) -1 +BB T -γ -2 DD T ] -1 A+Q,∑(k-1)=AΛ(k-1)A T +DD T , γ is the interference suppression degree, I Z is the yaw moment of inertia, Q is the positive definite weight matrix, M(k-1) is the strategy space of player 1 at time k-1, and x(k-1) is the state variable at time k-1.

[0020] Furthermore, in the above-mentioned vehicle path tracking control method, the step of performing vehicle path tracking control according to the estimated value comprises:

[0021] The value of the control variable at the current moment is calculated according to the estimated value of the state variable, and the value of the control variable at the current moment is sent to the actuator of the vehicle to perform path tracking control on the vehicle.

[0022] Furthermore, in the above-mentioned vehicle path tracking control method, the state variables include the sideslip angle of the center of mass, the yaw angular velocity, the lateral deviation and the heading angle deviation.

[0023] The present invention also discloses a vehicle path tracking control device, comprising:

[0024] A first determination module, used to determine a data packet receiving state of a predefined state variable according to real-time data collected by the sensor;

[0025] A second determination module, used to determine whether the vehicle is under a network attack at the current moment according to the data packet receiving state of the state variable at the current moment;

[0026] A first calculation module, used for calculating the value of the control variable at the previous moment according to the data of the state variable at the previous moment;

[0027] The second calculation module is used to calculate the estimated value of the state variable at the current moment according to the calculated value of the control variable using the state estimation equation, and perform vehicle path tracking control according to the estimated value.

[0028] Furthermore, the above-mentioned vehicle path tracking control device, wherein:

[0029] The calculation formula for the estimated value of the state variable at the current moment is:

[0030]

[0031] Where, Λ(k-1)=[∑(k-1) -1 +α k-1 C T N -1 C-γ -2 Q] -1 ,

[0032]

[0033] γ is the interference suppression degree, k1 and k2 are the front and rear wheel cornering stiffness, a and b are the distances from the center of mass to the front and rear axles, I Z is the yaw moment of inertia, N is the strategy space of player 2, Q is the positive definite weight matrix, u(k-1) is the control variable at time k-1, x(k-1) is the state variable at time k-1, is the estimated value of the state variable at time k.

[0034] Furthermore, the above-mentioned vehicle path tracking control device, wherein:

[0035] The calculation formula of the value of the control variable at the previous moment is:

[0036] u(k-1)=-B T Γ(k-1)A(I-γ -2 ∑(k-1)M(k-1)) -1 x(k-1),

[0037] Where Γ(k-1)=[M(k-1) -1 +BB T -γ -2 DD T ] -1 , M(k-1)=A T [M(k-1) -1 +BB T -γ -2 DD T ] -1 A+Q,∑(k-1)=AΛ(k-1)A T +DD T , γ is the interference suppression degree, I Z is the yaw moment of inertia, Q is the positive definite weight matrix, M(k-1) is the strategy space of player 1 at time k-1, and x(k-1) is the state variable at time k-1.

[0038] The present invention also discloses an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any one of the above-described methods when executing the computer program.

[0039] The present invention also discloses a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, any of the above-mentioned methods is implemented.

[0040] Aiming at the situation that intelligent connected vehicles are subject to network attacks and external interference during path tracking driving conditions, the present invention designs a path tracking fault-tolerant control mechanism based on game theory. When the intelligent connected vehicle is subject to network attacks, the system has certain fault-tolerant characteristics and can still ensure a certain path tracking accuracy and handling stability of the intelligent connected vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 Schematic diagram of information interaction flow of the vehicle path tracking control method in an embodiment of the present invention;

[0042] Figure 2 A flow chart of a vehicle path tracking control method provided by an embodiment of the present invention;

[0043] Figure 3 is a structural block diagram of a vehicle path tracking control device in an embodiment of the present invention;

[0044] Figure 4 Schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0046] These and other aspects of the embodiments of the present invention will become clear with reference to the following description and drawings. In these descriptions and drawings, some specific implementations of the embodiments of the present invention are specifically disclosed to represent some ways of implementing the principles of the embodiments of the present invention, but it should be understood that the scope of the embodiments of the present invention is not limited thereto. On the contrary, the embodiments of the present invention include all changes, modifications and equivalents that fall within the spirit and connotation of the appended claims.

[0047] Intelligent networked vehicles are typical cyber-physical systems (CPS), integrating information, communication and control. Intelligent networked vehicles are subject to cyber attacks and external interference during path tracking driving conditions, and cyber attacks are prone to occur between sensors and controllers, and between controllers and actuators.

[0048] In the prior art, the attack space method is used to describe the network attack phenomenon, and whether the system receives the data packet normally is used to determine whether the network attack exists. From the perspective of control variables, the key to the path tracking of intelligent networked vehicles is the front wheel steering angle δ and the vehicle speed u cTaking the front wheel steering angle δ as an example, considering the existence of network attacks, the control variable of the steering gear acting on the front wheel steering angle is defined as:

[0049] δ(k)=(1-ε(k))Kx(k) (4)

[0050] Where K is the state feedback gain, ε(k) describes the transmission status of the data packet, ε(k)∈{0,1}, when ε(k)=0, the data packet transmission at time k is successful, and the actuator receives δ(k)=Kx(k); when ε(k)=1, the data packet transmission at time k fails, and the actuator receives δ(k)=0.

[0051] The vehicle path tracking control method in this application starts from the control perspective and designs a path tracking fault-tolerant controller based on game theory. When the intelligent networked vehicle is attacked by the network, the system has certain fault-tolerant characteristics and can still ensure a certain path tracking accuracy and control stability of the intelligent networked vehicle. The overall idea and control scheme are as follows Figure 1 shown.

[0052] Taking into account the lateral stability and tracking accuracy of the intelligent connected vehicle during path tracking, a linear two-degree-of-freedom vehicle handling model and path tracking model are established, as shown in Figure (1).

[0053]

[0054] Where: k1 and k2 are the front and rear wheel cornering stiffnesses respectively; a and b are the distances from the center of mass to the front and rear axles respectively; m is the total mass of the vehicle; u c is the longitudinal speed; r is the yaw rate; ρ is the road curvature; δ is the front wheel turning angle; β is the sideslip angle of the center of mass; I Z is the yaw moment of inertia, ψ e is the heading angle deviation; e is the lateral deviation.

[0055] By the sideslip angle β and the yaw rate ω r Evaluate the lateral stability of intelligent connected vehicles by lateral deviation e and heading angle deviation ψ e To evaluate the path tracking accuracy of intelligent connected vehicles, define the state variable: x = [βω r eψ e ], control input: u = δ, road curvature disturbance: Define the output as the system state variable, that is, y=x.

[0056] Therefore, equation (1) can be transformed into a continuous state space equation as follows:

[0057]

[0058] in:

[0059]

[0060]

[0061] Further discretizing equation (2) yields the following equation (3):

[0062]

[0063] Where: k is the system time.

[0064] analyze Figure 1 In the embodiment of the present invention, it is considered that the system is subjected to network attacks and external interference during the path tracking of the intelligent networked vehicle: the network attack mainly occurs between the sensor and the controller, and between the controller and the actuator, where x(k) and u(k) are the state and control quantities before the network attack, and x'(k) and u'(k) are the state and control quantities after the network attack; the external interference ω(k) is inevitable, and is considered to exist between the sensor and the actuator, and is described by white noise.

[0065] The information interaction process of the intelligent connected vehicle path tracking control system is as follows: the sensor collects information such as vehicle speed, wheel speed, front wheel angle, etc. Before the state variable x(k) reaches the controller, it is attacked by the network. Through the designed game theory-based minimax controller, the control variable u(k) is estimated, thereby ensuring that the actuator can still use the estimated control quantity to ensure the vehicle's handling stability and path tracking accuracy during path tracking in an attack environment.

[0066] The embodiment of the present invention designs a minimax controller based on robust output feedback according to the relevant theories of zero-sum game theory, so as to achieve the purpose of improving the path tracking control effect of intelligent networked vehicles. Figure 2 , is a vehicle path tracking control method in an embodiment of the present invention, comprising steps S11 to S14.

[0067] Step S11, determining a data packet receiving state of a predefined state variable according to real-time data collected by the sensor.

[0068] Step S12, determining whether the vehicle is under a network attack at the current moment according to the data packet receiving state of the state variable at the current moment.

[0069] The defined state variable is: x = [βω r eψ e]. According to the data collected and transmitted by the sensor, the interaction state of the path tracking information is determined. The state variable x(k) is mainly monitored. By observing the receiving state of the state variable data packet, it is determined whether the path tracking process of the intelligent connected vehicle is attacked by the network. That is, when the state variable data packet is received, let α k =1; when no state variable data packet is received, let α k =0.

[0070] Step S13: If yes, calculate the value of the control variable at the previous moment according to the data of the state variable at the previous moment.

[0071] Step S14, according to the calculated value of the control variable, using the state estimation equation to calculate the estimated value of the state variable at the current moment, and performing vehicle path tracking control according to the estimated value.

[0072] When α k =1, when the system is in a normal state, update x(k), y(k), u(k); when α k =0, when the system is in a network attack state, the control law is calculated using the data at time k-1, that is, the value of the control variable u(k-1) at the previous moment:

[0073] u(k-1)=-B T Γ(k-1)A(I-γ -2 ∑(k-1)M(k-1)) -1 x(k-1) (4)

[0074] in:

[0075] Γ(k-1)=[M(k-1) -1 +BB T -γ -2 DD T ] -1 ;

[0076] M(k-1)=A T [M(k-1) -1 +BB T -γ -2 DD T ] -1 A+Q;

[0077] ∑(k-1)=AΛ(k-1)A T +DD T ;

[0078] γ is the interference suppression degree, γ>0;

[0079] M represents the strategy space of player 1;

[0080] Q represents a positive definite weight matrix, and ∑(k-1) are solutions to the game algebra Riccati equation, where Q0 is a positive definite weight matrix of moderate dimension.

[0081] use The state estimation equation is:

[0082]

[0083] Where: Λ(k-1)=[∑(k-1) -1 +α k-1 C T N -1 C-γ -2 Q] -1 , N represents the strategy space of player 2.

[0084] According to formula (4), the value of the control variable u(k-1) at time k-1 can be calculated, and u(k-1) can be substituted into formula (5) to estimate the state variable x(k) at time k.

[0085] This embodiment has the following advantages:

[0086] (1) In terms of research objects, the path tracking control of intelligent connected vehicles is taken as the research object, and the focus is on considering the possible adverse effects of network attacks on vehicle path tracking control. Existing related research has basically ignored the disadvantages of network information security issues such as network attacks on the operation of intelligent connected vehicles. Therefore, considering the path tracking control of intelligent connected vehicles with network attacks is more in line with the actual situation of the path tracking movement of intelligent connected vehicles from a practical perspective;

[0087] (2) In terms of network attack description, for types of attacks such as denial of service attacks (DoS attacks), replay attacks, and false data injection attacks, the attack space method is used to describe network attack phenomena. By observing whether the system receives data packets, it is determined whether a network attack has occurred. In terms of network attack description, it is more accurate than some existing research methods.

[0088] (3) In terms of control algorithm, the zero-sum game theory is used to develop a minimax controller based on robust output feedback. This control algorithm is specifically used for the control of cyber-physical systems (CPS) with cyber attacks. This patent uses it for path tracking control of intelligent connected vehicles with cyber attacks. Research shows that this control algorithm has good control effects.

[0089] (4) In terms of evaluation mechanism, this patent evaluates the effect of path tracking motion of intelligent connected vehicles under cyber attacks from two aspects: path tracking accuracy and lateral stability. The evaluation indicators of path tracking accuracy include lateral deviation and heading angle deviation, and the evaluation indicators of lateral stability include yaw rate and center of mass sideslip angle. Compared with other related studies, the evaluation mechanism involved in this patent is more complete.

[0090] See also Figure 3 , is a vehicle path tracking control device in an embodiment of the present invention, comprising:

[0091] A first determination module 31 is used to determine a data packet receiving state of a predefined state variable according to real-time sensor collection data;

[0092] A second determination module 32, used to determine whether the vehicle is under a network attack at the current moment according to the data packet receiving state of the state variable at the current moment;

[0093] A first calculation module 33, used to calculate the value of the control variable at the previous moment according to the data of the state variable at the previous moment;

[0094] The second calculation module 34 is used to calculate the estimated value of the state variable at the current moment according to the calculated value of the control variable using the state estimation equation, and perform vehicle path tracking control according to the estimated value.

[0095] Furthermore, in the above-mentioned vehicle path tracking control device, the calculation formula of the estimated value of the state variable at the current moment is:

[0096]

[0097] Where, v(k-1)=[∑(k-1) -1 +α k-1 C T N -1 C-γ -2 Q] -1 ,

[0098] γ is the interference suppression degree, k1 and k2 are the front and rear wheel cornering stiffness, a and b are the distances from the center of mass to the front and rear axles, I Z is the yaw moment of inertia, N is the strategy space of player 2, Q represents the positive definite weight matrix, u(k-1) is the control variable at time k-1, x(k-1) is the state variable at time k-1, is the estimated value of the state variable at time k.

[0099] Furthermore, in the above-mentioned vehicle path tracking control device, the calculation formula of the value of the control variable at the previous moment is:

[0100] u(k-1)=-B T Γ(k-1)A(I-γ -2 ∑(k-1)M(k-1)) -1 x(k-1),

[0101] Where Γ(k-1)=[M(k-1) -1 +BB T -γ -2 DD T ] -1 , M(k-1)=A T [M(k-1) -1 +BB T -γ -2 DD T ] -1 A+Q,∑(k-1)=AΛ(k-1)A T +DD T , γ is the interference suppression degree, I Z is the yaw moment of inertia, Q represents the positive definite weight matrix, M(k-1) is the strategy space of player 1 at time k-1, and x(k-1) is the state variable at time k-1.

[0102] The vehicle path tracking control device provided in the embodiment of the present invention has the same implementation principle and technical effects as those of the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0103] Another aspect of the present invention provides an electronic device, see Figure 4 , shown is an electronic device in an embodiment of the present invention, including a processor 10, a memory 20, and a computer program 30 stored in the memory and executable on the processor, and when the processor 10 executes the computer program 30, the vehicle path tracking control method as described above is implemented.

[0104] The electronic device may be, but is not limited to, a controller, a personal computer, etc. In some embodiments, the processor 10 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip, for running program codes stored in the memory 20 or processing data.

[0105] Among them, the memory 20 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. The memory 20 may be an internal storage unit of an electronic device in some embodiments, such as a hard disk of the electronic device. The memory 20 may also be an external storage device of an electronic device in other embodiments, such as a plug-in hard disk equipped on the electronic device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. Further, the memory 20 may also include both an internal storage unit of the electronic device and an external storage device. The memory 20 may be used not only to store application software and various types of data installed in the electronic device, but also to temporarily store data that has been output or is to be output.

[0106] Optionally, the electronic device may also include a user interface, a network interface, a communication bus, etc. The user interface may include a display (Display), an input unit such as a keyboard (Keyboard), and the optional user interface may also include a standard wired interface and a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface. The network interface may optionally include a standard wired interface, a wireless interface (such as a WI-FI interface), which is generally used to establish a communication connection between the device and other electronic devices. The communication bus is used to realize the connection communication between these components.

[0107] It should be pointed out that Figure 4 The structure shown does not constitute a limitation on the electronic device. In other embodiments, the electronic device may include fewer or more components than those shown in the figure, or combine certain components, or arrange the components differently.

[0108] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the vehicle path tracking control method as described above is implemented.

[0109] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be specifically implemented in any computer-readable medium for use by an instruction execution system or device (such as a computer-based system, a system including a processor, or other system that can obtain instructions from an instruction execution system or device and execute instructions), or in conjunction with such instruction execution systems or devices. For purposes of this specification, "computer-readable medium" may be any device that can contain, store, communicate, propagate, or transmit a program for use by an instruction execution system or device, or in conjunction with such instruction execution systems or devices.

[0110] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0111] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0112] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0113] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A vehicle path tracking control method, characterized in that: include, Determine the data packet receiving state of the predefined state variable according to the real-time data collected by the sensor; Determine whether the vehicle is under a network attack at the current moment according to the data packet receiving state of the state variable at the current moment; If so, the value of the control variable at the previous moment is calculated according to the data of the state variable at the previous moment; According to the calculated value of the control variable, the estimated value of the state variable at the current moment is calculated using the state estimation equation, and the vehicle path tracking control is performed according to the estimated value; The calculation formula for the estimated value of the state variable at the current moment is: where, Λ(k - 1) = [∑(k - 1) -1 + α k-1 C T N -1 C - γ -2 Q] -1 , γ is the interference suppression degree, k1 and k2 are the front and rear wheel cornering stiffness, a and b are the distances from the center of mass to the front and rear axles, I Z is the yaw moment of inertia, N is the strategy space of player 2, Q is the positive definite weight matrix, u(k-1) is the control variable at time k-1, x(k-1) is the state variable at time k-1, is the estimated value of the state variable at time k; The calculation formula of the value of the control variable at the previous moment is: u(k-1)=-B T Γ(k-1)A(I-γ -2 ∑(k-1)M(k-1)) -1 x(k-1), Where Γ(k-1)=[M(k-1) -1 +BB T -γ -2 DD T ] -1 , M(k-1)=A T [M(k-1) -1 +BB T -γ -2 DD T ] -1 A+Q,∑(k-1)=AΛ(k-1)A T +DD T , γ is the interference suppression degree, I Z is the yaw moment of inertia, Q is the positive definite weight matrix, M(k-1) is the strategy space of player 1 at time k-1, and x(k-1) is the state variable at time k-1.

2. The vehicle path tracking control method according to claim 1, characterized in that: The step of performing vehicle path tracking control according to the estimated value comprises: The value of the control variable at the current moment is calculated according to the estimated value of the state variable, and the value of the control variable at the current moment is sent to the actuator of the vehicle to perform path tracking control on the vehicle.

3. The vehicle path tracking control method according to claim 1, characterized in that: The state variables include sideslip angle of center of mass, yaw rate, lateral deviation and heading angle deviation.

4. A vehicle path tracking control device, characterized in that: include: A first determination module, used to determine a data packet receiving state of a predefined state variable according to real-time data collected by the sensor; A second determination module, used to determine whether the vehicle is under a network attack at the current moment according to the data packet receiving state of the state variable at the current moment; A first calculation module, used for calculating the value of the control variable at the previous moment according to the data of the state variable at the previous moment; A second calculation module is used to calculate the estimated value of the state variable at the current moment according to the calculated value of the control variable using the state estimation equation, and perform vehicle path tracking control according to the estimated value; The calculation formula for the estimated value of the state variable at the current moment is: where, Λ(k - 1) = [∑(k - 1) -1 + α k-1 C T N -1 C - γ -2 Q] -1 , γ is the interference suppression degree, k1 and k2 are the front and rear wheel cornering stiffness, a and b are the distances from the center of mass to the front and rear axles, I Z is the yaw moment of inertia, N is the strategy space of player 2, Q is the positive definite weight matrix, u(k-1) is the control variable at time k-1, x(k-1) is the state variable at time k-1, is the estimated value of the state variable at time k; The calculation formula of the value of the control variable at the previous moment is: u(k-1)=-B T Γ(k-1)A(I-γ -2 ∑(k-1)M(k-1)) -1 x(k-1), Where Γ(k-1)=[M(k-1) -1 +BB T -γ -2 DD T ] -1 , M(k-1)=A T [M(k-1) -1 +BB T -γ -2 DD T ] -1 A+Q,∑(k-1)=AΛ(k-1)A T +DD T , γ is the interference suppression degree, I Z is the yaw moment of inertia, Q is the positive definite weight matrix, M(k-1) is the strategy space of player 1 at time k-1, and x(k-1) is the state variable at time k-1.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 3 is implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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