Safety boundary setting method and system for transient drift condition of autonomous vehicle

Abstract

The invention relates to the technical field of active safety control, and particularly discloses a safety boundary setting method and system for a transient drift working condition of an automatic driving vehicle, and the method comprises the steps: constructing a three-degree-of-freedom vehicle dynamics model, and constructing a tire dynamics model based on a UniTi-Ctrl model; solving a system balance point under a drifting condition based on the three-degree-of-freedom vehicle dynamic model and the tire dynamic model, and analyzing tangent plane characteristics near the balance point; on the basis of a phase plane invariant set theory, a drift stability envelope is constructed in combination with control input, and the stability envelope comprises a yaw dynamics stability boundary, a front wheel guiding capacity preservation boundary, a drift state and steady state driving mode conversion boundary and an extended safety operation domain based on a control invariant set; and a drift path tracking controller is designed, and online control is realized through an optimization algorithm. According to the invention, closed-loop transient drift control can be realized, the safety of state conversion of the drifting vehicle is improved, and a safety guarantee is provided for limit control of transient drift of the vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of active safety control, and particularly to a safety boundary setting method and system for transient drift working conditions of an autonomous vehicle. BACKGROUND

[0002] Vehicle drift is a form of vehicle extreme motion existing in a highly nonlinear region. In professional driving, it maintains a controllable oversteering state through precise steering and throttle intervention. With the development of autonomous driving technology, autonomous drift has become a frontier topic in the field of vehicle dynamics control. Existing researches usually track the target drift trajectory by designing advanced control algorithms to coordinate steering and driving torque.

[0003] However, drift state is inherently dynamically unstable. The stability of the system is extremely susceptible to external disturbances and model mismatches, among which, the instability during transient drift is a major risk source. When the ideal state of the controller changes sharply, it will lead to a sharp decline in control effectiveness, and further cause vehicle instability.

[0004] Therefore, to ensure the robustness and safety of the autonomous vehicle during drift, strict safety boundary constraints must be introduced into the control algorithm. The core purpose of the constraint is to define and guard the stable boundary of vehicle motion. It not only needs to prevent the vehicle from losing control due to excessive side slip (i.e., breaking the upper boundary of the drift state), but also needs to ensure that the vehicle will not spontaneously return to traditional stable driving (i.e., avoid falling into the lower boundary attractor of the non-drift state), so as to ensure that the system can operate stably and reliably within the expected drift region. SUMMARY

[0005] The purpose of the present application is to provide a safety boundary setting method and system for transient drift working conditions of an autonomous vehicle to solve the problems raised in the background art.

[0006] To achieve the above purpose, the present application provides the following technical solutions:

[0007] The safety boundary setting method for transient drift working conditions of an autonomous vehicle comprises:

[0008] Constructing a three-degree-of-freedom vehicle dynamics model, the three-degree-of-freedom vehicle dynamics model including three degrees of freedom of longitudinal, lateral and yaw of the vehicle, and introducing an additional yaw moment as a key control variable;

[0009] Constructing a tire dynamics model based on the UniTire-Ctrl model;

[0010] Solving the system equilibrium point under the drifting condition based on the three-degree-of-freedom vehicle dynamics model and the tire dynamics model, and analyzing the tangent plane characteristics near the equilibrium point;

[0011] Based on the phase plane invariant set theory, combining with the control input, a drifting stability envelope is constructed, the stability envelope includes a yaw dynamics stability boundary, a front wheel steering ability preservation boundary, a mode conversion boundary between the drifting state and the steady state driving, and an extended safe operation domain based on the control invariant set;

[0012] Based on the stability envelope, a drifting path tracking controller is designed, and an online control is realized through an optimization algorithm.

[0013] As a further scheme of the application, the three-degree-of-freedom vehicle dynamics model is described by the following differential equations:

[0014] ;

[0015] ;

[0016] ;

[0017] Wherein, m is the self weight of the vehicle, V x is the longitudinal speed of the vehicle, β is the mass center side slip angle of the vehicle, r is the yaw angular velocity of the vehicle, δ is the front wheel steering angle of the vehicle, is the additional yaw moment of the vehicle, I Z is the whole vehicle moment of inertia, F xr and F yr are the longitudinal force and lateral force of the rear wheel of the vehicle, l f is the distance from the mass center to the front wheel, F yf is the front wheel lateral force of the vehicle, l r is the distance from the mass center to the rear wheel.

[0018] As a further scheme of the application, the tire force calculation of the UniTire-Ctrl model includes:

[0019] Normalized dimensionless total shear force calculation:

[0020] ;

[0021] Longitudinal force and lateral force calculation:

[0022] ;

[0023] ;

[0024] Wherein, E is the curvature factor of the total shear force curve, is the longitudinal adhesion coefficient, the lateral adhesion coefficient, , and are the normalized longitudinal slip ratio, lateral slip ratio and combined slip ratio, respectively, is the relative comprehensive slip rate, F z is the tire vertical force.

[0025] As a further aspect of the application, the yaw dynamics stability boundary is determined by:

[0026] ;

[0027] where µ is the road adhesion coefficient and g is the gravity acceleration.

[0028] As a further aspect of the application, the front wheel alignment capability preservation boundary is defined by the front wheel saturation side slip angle:

[0029] ;

[0030] where, is the side slip angle corresponding to the saturation of the front wheel, is the maximum negative front wheel steering angle that the vehicle can provide to prevent the saturation of the front wheel.

[0031] As a further aspect of the application, the drift mode to steady state driving mode transition boundary is determined by the rear wheel saturation side slip angle:

[0032] ;

[0033] where, is the side slip angle corresponding to the saturation of the rear wheel.

[0034] As a further aspect of the application, the extended safe operating domain based on the control invariant set is defined by:

[0035] ;

[0036] where, , defines the intersection of the maximum steady state yaw rate boundary and the rear wheel saturation maximum side slip angle as , is the minimum yaw rate derivative, is the side slip angle derivative corresponding to the minimum yaw rate, is the slope of the line connecting the point to the .

[0037] As a further aspect of the application, the design of the drift path following controller employs a model predictive control approach, which is achieved by solving the following finite time domain optimization problem:

[0038] ;

[0039] wherein Q is a state weight matrix, R is a control weight matrix, N is a prediction step, and ε is a relaxation variable, denotes a penalty coefficient of the relaxation variable.

[0040] The application also provides a safety boundary setting system for transient drift working conditions of an autonomous vehicle, and the system comprises:

[0041] a vehicle dynamics model construction module, configured to construct a three-degree-of-freedom vehicle dynamics model, wherein the three-degree-of-freedom vehicle dynamics model comprises three degrees of freedom of a vehicle, i.e., longitudinal, lateral and yaw, and an additional yaw moment is introduced as a key control variable;

[0042] a tire dynamics model construction module, configured to construct a tire dynamics model based on a UniTire-Ctrl model;

[0043] an analysis module, configured to solve a system equilibrium point in a drift working condition based on the three-degree-of-freedom vehicle dynamics model and the tire dynamics model, and analyze tangent plane characteristics near the equilibrium point;

[0044] an envelope module, configured to construct a drift stability envelope based on a phase plane invariant set theory and in combination with a control input, wherein the stability envelope comprises a yaw dynamics stability boundary, a front wheel steering ability preservation boundary, a modal conversion boundary between a drift state and a steady state driving, and an extended safe operating domain based on a control invariant set;

[0045] an optimization module, configured to design a drift path tracking controller based on the stability envelope, and realize online control through an optimization algorithm.

[0046] Compared with the prior art, the application has the beneficial effects that: the application innovatively proposes a multi-level drift safety boundary architecture, which comprises a yaw dynamics stability boundary, a front wheel steering ability preservation boundary, a modal conversion boundary between a drift state and a steady state driving, and an extended safe operating domain based on a control invariant set. This boundary system ensures the safety of a drift process from different dimensions: it prevents a vehicle from losing control due to excessive side slip (breaking through an upper boundary of a drift state), and avoids a vehicle from unintentionally returning to traditional steady state driving (falling into a lower boundary attractor domain of a non-drift state), thereby providing comprehensive safety guarantee for drift control.

[0047] The application provides a complete technical chain from model establishment, boundary analysis to controller design, and provides a systematic solution for safety control of an autonomous vehicle in extreme working conditions such as drift. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application.

[0049] Figure 1 A flow chart of a safety boundary setting method for a transient drift working condition of an autonomous vehicle is provided in the embodiments of the present application.

[0050] Figure 2 A tangent plane graph of a drift balance point near a vehicle speed of 60 km / h and a steering wheel angle of 0 deg is provided in the embodiments of the present application.

[0051] Figure 3 A phase plane graph of a drift balance point near a vehicle speed of 60 km / h and a steering wheel angle of 0 deg is provided in the embodiments of the present application.

[0052] Figure 4 A drift stability envelope design graph of a vehicle at a vehicle speed of 60 km / h and a steering wheel angle of 0 deg is provided in the embodiments of the present application. DETAILED DESCRIPTION

[0053] In order to make the technical problems to be solved by the present application, technical solutions and beneficial effects more clearly understood, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not used to limit the present application.

[0054] Figure 1 A flow chart of a safety boundary setting method for a transient drift working condition of an autonomous vehicle is provided, and in the embodiments of the present application, the safety boundary setting method for the transient drift working condition of the autonomous vehicle, the method comprises:

[0055] A three-degree-of-freedom vehicle dynamics model is constructed, the three-degree-of-freedom vehicle dynamics model includes three degrees of freedom of longitudinal, lateral and yaw of the vehicle, and an additional yaw moment is introduced as a key control variable;

[0056] A tire dynamics model based on a UniTire-Ctrl model is constructed;

[0057] Based on the three-degree-of-freedom vehicle dynamics model and the tire dynamics model, the system balance point under the drift working condition is solved, and the tangent plane characteristics near the balance point are analyzed;

[0058] Based on the phase plane invariant set theory, a drift stability envelope is constructed in combination with the control input, and the stability envelope includes a yaw dynamics stability boundary, a front wheel steering ability preservation boundary, a modal conversion boundary between a drift state and a steady state driving, and an extended safety operating domain based on a control invariant set;

[0059] Based on the stability envelope, a drift path tracking controller is designed, and an online control is realized through an optimization algorithm.

[0060] In this embodiment,

[0061] As a preferred embodiment of the present application, the three-degree-of-freedom vehicle dynamics model is described by the following differential equations:

[0062] ;

[0063] ;

[0064] ;

[0065] where m is the self-weight of the vehicle, V x is the longitudinal speed of the vehicle, β is the vehicle's center of mass side slip angle, r is the vehicle's yaw rate, δ is the vehicle's front wheel steering angle, is the additional yaw moment of the vehicle, I Z is the vehicle's moment of inertia, F xr and F yr are the longitudinal and lateral forces of the vehicle's rear wheels, l f is the distance from the center of mass to the front wheels, F yf is the lateral force of the vehicle's front wheels, l r is the distance from the center of mass to the rear wheels.

[0066] In this embodiment, to balance between computational efficiency and model accuracy, a simplified vehicle dynamics model suitable for drift control is derived to meet the computational constraints of real-time controllers. The model considers the longitudinal, lateral and yaw three degrees of freedom of the vehicle, and introduces an additional yaw moment as a key control variable to accurately represent the intervention ability of the distributed drive system on the vehicle's yaw motion.

[0067] As a preferred embodiment of the present application, the tire force calculation of the UniTire-Ctrl model includes:

[0068] Normalized dimensionless total shear force calculation:

[0069] ;

[0070] Longitudinal and lateral force calculation:

[0071] ;

[0072] ;

[0073] where E is the curvature factor of the total shear force curve, the longitudinal adhesion coefficient, the lateral adhesion coefficient, , and are the normalized longitudinal slip ratio, lateral slip ratio and combined slip ratio, respectively, is the relative overall slip rate, F z is the tire vertical force.

[0074] In this embodiment, a tire dynamics model is established, which adopts the UniTire-Ctrl model, and the corresponding tire parameters are fitted according to the MatLab toolbox.

[0075] Based on the vehicle dynamics model and the tire model, drift equilibrium points and tangent plane analysis are performed. This step aims to determine the steady-state equilibrium points and tangent plane states of the vehicle in the drift working condition, and to provide model reference for subsequent safety boundary design. Specifically, first, nonlinear differential equations describing the lateral, yaw and longitudinal motion of the vehicle are established, denoted as , wherein x is the system state vector, and u is the control input vector.

[0076] The equilibrium point is a working point where the system state derivative no longer changes, that is, it satisfies . By letting , and substituting the given reference vehicle speed and front wheel angle, the corresponding system equilibrium state can be solved. This state represents a steady-state drift working condition under specific operating conditions.

[0077] Tangent space calculation: to analyze the dynamic characteristics near the equilibrium point, the vehicle model is calculated near the equilibrium point, which can obtain the tangent space near the point, and provide the basis for designing the drift safety boundary, as shown in Figure 2 .

[0078] As a preferred embodiment of the present application, the yaw dynamics stability boundary is determined by the following formula:

[0079] ;

[0080] wherein µ is the road adhesion coefficient, and g is the gravitational acceleration.

[0081] In this embodiment, drift stability envelope construction based on the phase plane invariant set theory is performed. By analyzing the phase plane and tangent plane near the equilibrium point in the drift working condition, the corresponding safety boundary is obtained.

[0082] During the vehicle drift process, the vehicle theoretical peak yaw angular velocity determined by the ground adhesion condition at a certain vehicle speed is defined as , which establishes the theoretical limit for maintaining the yaw stability of the vehicle.

[0083] In a preferred embodiment of the present invention, the front wheel steering capability preservation boundary is defined by the front wheel saturation sideslip angle. To ensure that the front wheel maintains the necessary lateral force reserve to sustain steering capability during drifting, its sideslip angle must be limited to the saturation point. Therefore, the front wheel should be in an unsaturated state. Thus, for the β-r phase plane, the safety boundary for the front wheel is:

[0084] ;

[0085] in, This represents the sideslip angle corresponding to the front wheel's saturation. The maximum reverse front wheel steering angle that the vehicle can provide to prevent front wheel saturation.

[0086] In a preferred embodiment of the present invention, the mode transition boundary between drift state and steady state driving is determined by the rear wheel saturation sideslip angle:

[0087] ;

[0088] in, The side slip angle is the angle corresponding to the rear wheel going from unsaturated to saturated. The boundary of the steady-state driving zone is determined by the intersection of the steady-state yaw rate and the rear wheel saturation characteristic line.

[0089] In this embodiment, to prevent the system from unintentionally exiting the drift mode and returning to a non-drift steady-state driving, the boundary between the two modes needs to be clearly defined. This boundary is determined by the rear wheel reaching force saturation. This is the critical sideslip angle.

[0090] In a preferred embodiment of the present invention, the extended safe operating domain based on the control invariant set is defined by the following conditions:

[0091] ;

[0092] in, The intersection of the maximum steady-state yaw rate boundary and the maximum saturated sideslip angle of the rear wheel is defined as... , The derivative of the minimum yaw rate. The minimum yaw rate corresponds to the derivative of the sideslip angle. Points to be found in the β-r phase plane The slope.

[0093] In this embodiment, in addition to the above-mentioned safety boundary design for the vehicle β-r phase plane, consideration should be given to... In state space, the vehicle extension boundary is determined by incorporating the influence of the feasible region of the control input u. Taking left drift as an example, the intersection of the maximum steady-state yaw rate boundary and the maximum saturated sideslip angle of the rear wheels is defined as... . After introducing the closed-loop control action, the reachability analysis of the system is essential. Then, outside the steady yaw rate boundary, the linearized system has a minimum yaw rate derivative and its corresponding side slip angle derivative with a slope to the origin should satisfy a slope to greater than the slope of the β-r phase plane at the point of interest , as shown by the tangent plane and Figure 2 the β-r phase plane. Figure 3

[0094] The region in the β-r phase plane that satisfies this condition is then the positively invariant set obtained after considering the control input, which is the final extended safe operating domain. As shown in Figure 4 , the outer yellow envelope is the drift safety envelope considering the control input, and the inner red envelope is the steady-state driving mode of the vehicle. The vehicle also avoids entering this envelope region during drifting.

[0095] As a preferred embodiment of the present application, the design of the drift path tracking controller adopts the model predictive control method. At each sampling time, the controller solves the following finite time domain optimization problem based on the current vehicle state:

[0096] ;

[0097] where Q is the state weight matrix, R is the control weight matrix. N is the prediction step, ε is the relaxation variable, and ε represents the penalty coefficient of the relaxation variable.

[0098] In this embodiment, the purpose is to design a drift path tracking controller that considers the control input and guarantees safety based on the analysis results of the previous steps and to verify it. Specifically, based on the obtained equilibrium point position and safety boundary, combined with the model predictive control algorithm, and converting the safety boundary into the constraint and penalty term of the optimization problem, a finite time domain optimization problem is constructed. The drift path tracking controller is designed.

[0099] The purpose is to handle the safety boundary as a soft constraint, allowing slight violations in extreme cases to avoid the optimization problem having no solution, thereby improving the feasibility and robustness of the controller.

[0100] By repeatedly solving this optimization problem online, the model predictive controller can dynamically plan an optimal control sequence that satisfies the vehicle dynamics constraints and strictly respects the safety boundary, and the effectiveness is verified through carsim and simulink joint simulation, finally realizing accurate and robust tracking of the target drift path. ​

[0101] The application designs closed-loop drift boundaries according to the dynamics characteristics of the vehicle itself in the drift process combined with the control input of the vehicle. First, the front wheel saturation side slip angle boundary and the rear wheel saturation maximum side slip angle boundary are designed according to the dynamics saturation characteristics of the front and rear wheels in the drift process. Secondly, the maximum steady-state yaw rate boundary is defined according to the maximum steady-state yaw rate of the vehicle, that is, the intersection of the maximum steady-state yaw rate boundary and the rear wheel saturation maximum side slip angle, and according to the intersection, the upper and lower drift boundaries considering the closed-loop control input are designed. After the drift boundary is designed, the model predictive control method is used to convert the safety boundary into the constraints and penalties of the optimization problem. Through the solution of the optimization problem, the drift controller satisfying the vehicle dynamics constraints is finally obtained, which provides a technical scheme for the closed-loop drift. The application designs closed-loop drift boundaries according to the dynamics characteristics of the vehicle itself in the drift process combined with the control input of the vehicle. First, the front wheel saturation side slip angle boundary and the rear wheel saturation maximum side slip angle boundary are designed according to the dynamics saturation characteristics of the front and rear wheels in the drift process. Secondly, the maximum steady-state yaw rate boundary is defined according to the maximum steady-state yaw rate of the vehicle, that is, the intersection of the maximum steady-state yaw rate boundary and the rear wheel saturation maximum side slip angle, and according to the intersection, the upper and lower drift boundaries considering the closed-loop control input are designed. After the drift boundary is designed, the model predictive control method is used to convert the safety boundary into the constraints and penalties of the optimization problem. Through the solution of the optimization problem, the drift controller satisfying the vehicle dynamics constraints is finally obtained, which provides a technical scheme for the closed-loop drift.

[0102] The embodiment of the application also provides a safety boundary setting system for transient drift working conditions of an automatic driving vehicle, and the system comprises:

[0103] A vehicle dynamics model construction module is configured to construct a three-degree-of-freedom vehicle dynamics model, wherein the three-degree-of-freedom vehicle dynamics model comprises three degrees of freedom of a vehicle, i.e., longitudinal, lateral and yaw, and an additional yaw moment is introduced as a key control variable;

[0104] A tire dynamics model construction module is configured to construct a tire dynamics model based on a UniTire-Ctrl model;

[0105] An analysis module is configured to solve system equilibrium points in a drift working condition based on the three-degree-of-freedom vehicle dynamics model and the tire dynamics model, and analyze tangent plane characteristics near the equilibrium points;

[0106] An envelope module is configured to construct a drift stability envelope based on a phase plane invariant set theory combined with a control input, wherein the stability envelope comprises a yaw dynamics stability boundary, a front wheel steering ability preservation boundary, a mode conversion boundary between a drift state and a steady-state driving, and an extended safety operating domain based on a control invariant set;

[0107] An optimization module is configured to design a drift path tracking controller based on the stability envelope, and realize online control through an optimization algorithm.

[0108] The above only describes the preferred embodiments of the application and is not used to limit the application, and any modification, equivalent replacement and improvement made within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A method for setting safety boundaries for transient drift operating conditions of an autonomous vehicle, characterized in that, The method comprises: a three-degree-of-freedom vehicle dynamics model is constructed, the three-degree-of-freedom vehicle dynamics model comprises three degrees of freedom of a vehicle in longitudinal, lateral and yaw directions, and an additional yaw moment is introduced as a key control variable; a tire dynamics model based on a UniTire-Ctrl model is constructed; a system equilibrium point in a drifting working condition is solved based on the three-degree-of-freedom vehicle dynamics model and the tire dynamics model, and a tangent plane characteristic near the equilibrium point is analyzed; a drifting stability envelope is constructed based on a phase plane invariant set theory and in combination with a control input, the stability envelope comprising a yaw dynamics stability boundary, a front wheel steering ability preservation boundary, a mode conversion boundary between a drifting state and a steady state driving, and an extended safe operation domain based on a control invariant set; a drifting path tracking controller is designed based on the stability envelope, and online control is realized through an optimization algorithm.

2. The method of claim 1, wherein, The three-degree-of-freedom vehicle dynamics model is described by the following differential equations: ； ； ； where m is the self-weight of the vehicle, V x is the longitudinal vehicle speed, β is the vehicle's mass center side slip angle, r is the vehicle's yaw rate, δ is the vehicle's front wheel steering angle, is the vehicle's additional yaw moment, I Z is the vehicle's moment of inertia, F xr and F yr are the vehicle's rear wheel longitudinal and lateral forces, l f is the distance from the mass center to the front wheels, F yf is the vehicle's front wheel lateral force, l r is the distance from the mass center to the rear wheels.

3. The method of claim 2, wherein, Calculation of tire forces of the UniTire-Ctrl model comprises: Calculation of a normalized dimensionless total shear force: ； Calculation of longitudinal and lateral forces: ； ； where E is the curvature factor of the total shear curve, is the longitudinal adhesion coefficient, is the lateral adhesion coefficient, , and are the normalized longitudinal slip ratio, lateral slip ratio and combined slip ratio, respectively, is the relative overall slip ratio, F z is the tire vertical force.

4. The method of claim 3, wherein, The yaw dynamics stability boundary is determined by the following formula: ； Wherein, µ is a road surface adhesion coefficient, and g is a gravity acceleration.

5. The method of claim 4, wherein, The front wheel steering ability preservation boundary is limited by a front wheel saturation side slip angle: ； wherein, is the corresponding side slip angle at saturation of the front wheels, is the maximum negative front wheel steering angle that the vehicle can provide to prevent saturation of the front wheels.

6. The method of claim 5, wherein, The mode conversion boundary between the drifting state and the steady state driving is determined by a rear wheel saturation side slip angle: ； wherein, is the corresponding side slip angle from unsaturation to saturation for the rear wheel.

7. The method of claim 6, wherein, The extended safe operation domain based on the control invariant set is defined by the following conditions: ； wherein, , defining the intersection of the maximum steady state yaw rate boundary and the rear wheel saturation maximum side slip angle as , is the minimum yaw rate derivative, is the minimum yaw rate corresponding side slip angle derivative, is the slope of the line from the point on the β-r phase plane to .

8. The method of claim 1, wherein, The drifting path tracking controller is designed by using a model predictive control method, and is realized by solving the following finite time domain optimization problem: ； wherein Q is a state weight matrix, R is a control weight matrix, N is a prediction step, and ε is a relaxation variable, denotes a penalty coefficient for the relaxation variable.

9. A system for setting safety boundaries for transient drift conditions of an autonomous vehicle, for implementing the method for setting safety boundaries for transient drift conditions of an autonomous vehicle according to any one of claims 1-8, characterized in that, The system comprises: a vehicle dynamics model construction module, configured to construct a three-degree-of-freedom vehicle dynamics model, the three-degree-of-freedom vehicle dynamics model comprising three degrees of freedom of a vehicle in longitudinal, lateral and yaw directions, and an additional yaw moment being introduced as a key control variable; a tire dynamics model construction module, configured to construct a tire dynamics model based on a UniTire-Ctrl model; an analysis module, configured to solve a system equilibrium point in a drifting working condition based on the three-degree-of-freedom vehicle dynamics model and the tire dynamics model, and analyze a tangent plane characteristic near the equilibrium point; an envelope module, configured to construct a drifting stability envelope based on a phase plane invariant set theory and in combination with a control input, the stability envelope comprising a yaw dynamics stability boundary, a front wheel steering ability preservation boundary, a mode conversion boundary between a drifting state and a steady state driving, and an extended safe operation domain based on a control invariant set; an optimization module, configured to design a drifting path tracking controller based on the stability envelope, and realize online control through an optimization algorithm.

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