A control method and system for eliminating crosswind disturbances during high-speed automatic driving of commercial vehicles

Abstract

The present invention provides a control method and system for eliminating crosswind disturbances during high-speed autonomous driving of commercial vehicles. By adding a first-order sliding film control feedforward to the commercial vehicle's autonomous driving control system, the vehicle's longitudinal velocity, lateral velocity, lateral acceleration, yaw angular velocity, trajectory target curvature, heading angle, and heading angular rate are used as module inputs to generate compensation values ​​for external lateral disturbances. This method can effectively cope with crosswind disturbances at high speeds and improve the lateral control accuracy of autonomous vehicles under crosswind disturbances.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving, and in particular to a control method and system for eliminating crosswind disturbances during high-speed autonomous driving of a commercial vehicle. Background Art

[0002] As a key vehicle for the new wave of technological revolution and industrial integration and innovation, autonomous vehicles have become a key strategic direction for the development of the global automotive industry. Commercial vehicles operate on a single, single route, and their cargo-carrying nature doesn't require driver comfort, only safety. Therefore, commercial vehicles are the most promising vehicles for implementing L4 autonomous driving technology. L4 autonomous driving can achieve autonomous driving in normal weather conditions without relying on a driver. However, when commercial vehicles are driving at high speeds, crosswinds can significantly impact the vehicle's lateral control accuracy. Crosswinds exert an external lateral force on the vehicle, causing unintended lateral displacement. Upon detecting lateral deviation, the control system immediately corrects for the deviation. Once the vehicle returns to the road centerline, it compensates for the deviation, further deviating from the centerline. This cycle causes the vehicle to sway from side to side, compromising driving stability and the safety of other road users. Furthermore, due to their large side surfaces and high chassis, commercial vehicles are more susceptible to crosswinds during high-speed autonomous driving, causing the vehicle to sway side to side, creating a "dragon-shaped" phenomenon. This can affect autonomous control accuracy and lead to accidents.

[0003] The prior art discloses a method for controlling a vehicle in crosswind conditions, which mainly uses a vehicle camera to identify crosswind signs on the road, and then uses an assisted driving system to actively take over and slow down the vehicle to pass through the crosswind area. This method relies on road signs, but most open roads do not have signs, so the scope of application is very limited. In addition, this is an assisted driving system, and the method is not suitable for autonomous vehicles. It can be seen that in the current development of autonomous driving technology, there is no sensor that can identify key information such as the current wind speed and the lateral force of the vehicle in response to crosswind interference. Therefore, there is currently no better solution. The only solution is to limit the maximum operating speed of the vehicle to reduce the impact of lateral disturbances, but this method greatly limits the operating efficiency of commercial vehicles.

[0004] It can be seen that during the operation of commercial autonomous driving vehicles, it is necessary to design appropriate control strategies to avoid the impact of crosswinds, improve the stability of commercial vehicles when driving at high speeds and their ability to resist external disturbances, so as to ensure driving safety. Summary of the Invention

[0005] In response to the defects in the prior art, the purpose of the present invention is to provide a method and system for eliminating crosswind disturbance control in high-speed automatic driving of commercial vehicles, effectively deal with crosswind disturbances at high speeds, and improve the lateral control accuracy of automatic driving vehicles under crosswind disturbances.

[0006] In order to achieve the above technical effects, the present invention adopts the following technical solutions:

[0007] According to a first aspect of the present invention, a method for eliminating crosswind disturbances during high-speed automatic driving of a commercial vehicle is provided, comprising the following steps:

[0008] Step S1. The perception data processing unit receives input information from the vehicle sensor, identifies the surrounding environment information, and outputs obstacle information to the planning module;

[0009] Step S2. The decision-making and planning module plans a safe and comfortable target vehicle driving trajectory in real time based on the actual vehicle surrounding environment information and sends it to the control module; the control module calculates the target control instruction 1 through an optimization algorithm based on the deviation between the actual vehicle positioning and the target position;

[0010] Step S3. Add a disturbance feedforward compensation module. The disturbance feedforward compensation module consists of two parts: an external disturbance judgment module and an external disturbance compensation module. The module takes the vehicle longitudinal velocity, lateral velocity, lateral acceleration, yaw rate, trajectory target curvature, heading angle, and heading angular rate as module inputs, generates a compensation value for the external lateral disturbance, and outputs an angle control instruction. Specifically, the module includes the following steps:

[0011] S3.1 Establishment of the external disturbance compensation model, specifically including the establishment of the vehicle force model and error model, crosswind disturbance modeling and sliding mode control, and the calculation formula for angle compensation is derived:

[0012]

[0013] Among them, v x is the vehicle longitudinal velocity, C f is the front wheel cornering stiffness, C r is the rear wheel cornering stiffness, is the rate of change of lateral displacement, L f is the distance from the front axle center to the center of mass, L r is the distance from the rear axle center to the center of mass, is the yaw rate, δ f is the front wheel angle, λ is the sliding surface coefficient, λ>0,;

[0014] S3.2 External disturbance judgment and compensation calculation: The external disturbance judgment module judges whether the vehicle is disturbed by external crosswind according to the actual lateral acceleration, lateral velocity, and yaw angle data of the vehicle. If it is judged that the vehicle is not disturbed by external crosswind at this time, the external disturbance judgment module outputs angle control instruction 3 equal to 0; if it is judged that the vehicle is subject to regular external disturbance at this time, the compensation amount δ of the current disturbance is calculated according to the angle compensation calculation formula in S3.1 fd , and output the external disturbance compensation module output angle control instruction 2 equal to δ fd ;

[0015] Step S4. Adding the angle compensation of the angle control instruction 2 or the angle control instruction 3 calculated in step S3 to the target angle control amount;

[0016] Step S5. The accumulated target angle control amount is sent to the vehicle steering actuator through the MCU real-time system via the total angle control instruction, so as to achieve compensation in the presence of crosswind disturbances. The total angle control instruction = angle control instruction 1 + angle control instruction 2 + angle control instruction 3.

[0017] Preferably, in step S1, the vehicle-mounted sensor input information includes: positioning data, camera data including lane line data, information input by the millimeter wave sensor including obstacle data on both sides, and vehicle status data including vehicle chassis data.

[0018] Preferably, in step S3.1, the vehicle force model is the following formula (1):

[0019]

[0020] Where, v x is the vehicle longitudinal velocity, C f is the front wheel cornering stiffness, C r is the rear wheel cornering stiffness, is the rate of change of lateral displacement, L f is the distance from the front axle center to the center of mass, L r is the distance from the rear axle center to the center of mass, is the yaw rate, δ f is the front wheel angle, I z is the longitudinal moment of inertia of the vehicle;

[0021] The error model is:

[0022] e y =y act -y ref (2)

[0023]

[0024] Where y act is the Y-axis coordinate of the vehicle's actual position, y ref is the y-axis coordinate of the target trajectory point, and ρ is the curvature of the target trajectory point;

[0025] During the autonomous driving control process, it is necessary to calculate the appropriate δ f , so that e y =0,

[0026] Preferably, in the crosswind disturbance modeling and sliding mode control in step S3.1, the sliding film surface function is selected as follows:

[0027]

[0028] Where λ is the sliding surface coefficient, λ>0, substitute the expressions in equations (2) and (3) into equation (4), and take the first-order derivative of the sliding surface s to obtain:

[0029]

[0030] After the vehicle reaches steady state, the first-order sliding surface The solution can be obtained as the front wheel angle compensation value δ under disturbance fd

[0031]

[0032] In the formula, α1 is a preset positive number. By adjusting the value of α1, the convergence time of the system can be changed.

[0033] Preferably, in step S3.2, the external disturbance judgment module judges whether the vehicle is subject to regular external disturbances by fitting the change curve using the least squares method. When the change period of the fitting curve is less than the set threshold, it is judged that the vehicle is not subject to regular external disturbances at this time; when the change period of the fitting curve is greater than the set threshold, it is judged that the vehicle is subject to regular external disturbances at this time.

[0034] According to a second aspect of the present invention, a control system for eliminating crosswind disturbances during high-speed automatic driving of a commercial vehicle is provided, which is used to implement the above-mentioned control method for eliminating crosswind disturbances during high-speed automatic driving of a commercial vehicle, and specifically includes the following components:

[0035] Perception data processing unit: used to receive input information from vehicle sensors, identify surrounding environment information, and output obstacle information to the decision-making and planning module;

[0036] Decision-making and planning module: used to plan a safe and comfortable vehicle target driving trajectory in real time based on the actual vehicle surrounding environment information and send it to the control module;

[0037] Control module: used to calculate the target control instruction 1 through optimization algorithm according to the deviation between the actual vehicle positioning and the target position;

[0038] External disturbance judgment module: used to judge whether the vehicle is subject to regular external disturbances based on the vehicle's actual lateral acceleration, lateral velocity, and vehicle yaw angle data by fitting the change curve using the least squares method. If it is judged that the vehicle is not subject to regular external disturbances, the target control instruction 3 = 0 is output;

[0039] External disturbance compensation module: When the external disturbance judgment module determines that the vehicle is subject to regular external disturbances, this module calculates the vehicle's lateral acceleration based on the curvature ρ of the target trajectory and the current vehicle's lateral acceleration. Target lateral acceleration The current vehicle speed Vx, the current vehicle yaw rate The current vehicle heading and the target heading difference are used to calculate the compensation amount of the disturbance at the current moment, and the target control instruction 2 is output;

[0040] Angle control instruction summary module: used to accumulate the angle compensation amount of angle control instruction 2 or angle control instruction 3 to angle control instruction 1 to form a total angle control instruction, and send the total angle control instruction to the MCU real-time system;

[0041] MCU real-time system: used to send the accumulated total angle control command to the vehicle steering actuator to achieve compensation when there is crosswind disturbance. The total angle control command = angle control command 1 + angle control command 2 + angle control command 3.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The control method for eliminating crosswind disturbances during high-speed automatic driving of commercial vehicles provided by the present invention is a low-cost solution that does not require additional sensors. Only adjustments to the software algorithm are required to ensure that the operating speed of the commercial vehicle is not affected and that the vehicle does not need to slow down under external disturbances. This effectively copes with crosswind disturbances at high speeds and improves the lateral control accuracy of the autonomous driving vehicle under crosswind disturbances. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0045] Figure 1 This is a flowchart of the control method for eliminating crosswind disturbances in high-speed automatic driving of a commercial vehicle described in the first embodiment;

[0046] Figure 2This is a flowchart of the steps of the control method for eliminating crosswind disturbances in high-speed automatic driving of a commercial vehicle described in the first embodiment;

[0047] Figure 3 Schematic diagram of the simplified force model and error model of the two-wheeled vehicle described in the first embodiment;

[0048] Figure 4 This is a block diagram of the control system for eliminating crosswind disturbances in high-speed automatic driving of a commercial vehicle as described in the second embodiment. DETAILED DESCRIPTION

[0049] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of 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. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0050] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without creative work are within the scope of protection of the present application.

[0051] First embodiment

[0052] like Figure 1 、 2 As shown, in order to achieve the crosswind interference capability of commercial vehicles during high-speed autonomous driving, this embodiment proposes a control method for eliminating crosswind disturbances during high-speed autonomous driving of commercial vehicles. This method does not rely on sensors to identify weather conditions, but only eliminates the influence of crosswinds through appropriate control strategies. The specific technical solution is as follows:

[0053] Step S1. The perception data processing unit receives on-board sensor input, identifies the surrounding environment, and outputs obstacle information to the planning module. The on-board sensor input includes positioning data, camera data including lane markings, millimeter-wave sensor input including obstacle data on both sides, and vehicle status data including chassis data.

[0054] Step S2: The decision-making and planning module plans a safe and comfortable target driving trajectory for the vehicle in real time based on the actual vehicle surrounding environment information and sends it to the control module. The control module calculates the target control instruction 1 through an optimization algorithm based on the deviation between the actual vehicle position and the target position.

[0055] Step S3. Add a disturbance feedforward compensation module. The disturbance feedforward compensation module consists of two parts: an external disturbance judgment module and an external disturbance compensation module. The module takes the vehicle longitudinal velocity, lateral velocity, lateral acceleration, yaw rate, trajectory target curvature, heading angle, and heading angular rate as module inputs, generates a compensation value for the external lateral disturbance, and outputs an angle control command. Specifically, the module includes the following steps:

[0056] S3.1 Establishment of external disturbance compensation model:

[0057] The establishment of the external disturbance compensation model includes the following two parts: the establishment of the vehicle force model and the error model and the crosswind disturbance modeling and sliding mode control.

[0058] (1) Considering the influence of the lateral force on the vehicle, the error between the current position of the vehicle and the target trajectory point position is modeled based on the dynamic model. The simplified force model and error model diagram of the two-wheeled vehicle are as follows: Figure 3 As shown in Figure 2, the crosswind effect is considered as an external disturbance, and the input of the control system is calculated through the error analysis model.

[0059] The vehicle dynamics model is as follows (1):

[0060]

[0061] Where, v x is the vehicle longitudinal velocity, C f is the front wheel cornering stiffness, C r is the rear wheel cornering stiffness, is the rate of change of lateral displacement, L f is the distance from the front axle center to the center of mass, L r is the distance from the rear axle center to the center of mass, is the yaw rate, δ f is the front wheel angle, I z is the longitudinal moment of inertia of the vehicle;

[0062] The error model is:

[0063] e y =y act -y ref (2)

[0064]

[0065] Where y act is the Y-axis coordinate of the vehicle's actual position, y ref is the y-axis coordinate of the target trajectory point, and ρ is the curvature of the target trajectory point;

[0066] During the autonomous driving control process, it is necessary to calculate the appropriate δ f , so that ey =0,

[0067] (2) Crosswind disturbance modeling and sliding mode control:

[0068] During vehicle operation, the impact of crosswinds on the vehicle is considered an external disturbance. The magnitude of the disturbance force is related to wind speed and frontal area, making it difficult to quantitatively measure using sensors. This embodiment addresses the irregular crosswind disturbances experienced by autonomous vehicles during operation by designing a robust sliding-mode control strategy that accounts for uncertain disturbances. By leveraging the fact that after reaching the sliding-mode surface, the system is independent of the controlled object parameters and disturbances, a sliding-mode control feedforward is selected to mitigate the impact of crosswinds on the vehicle's lateral stability, effectively reducing steering wheel buffeting in vehicles subjected to crosswind disturbances.

[0069] Select the synovial surface function as follows:

[0070]

[0071] Where λ is the sliding surface coefficient, λ>0, substitute the expression in formula (1) into formula (4), and take the first-order derivative of the sliding surface s to obtain:

[0072]

[0073] After the vehicle reaches steady state, the first-order sliding surface The solution can be obtained as the front wheel angle compensation value δ under disturbance fd

[0074]

[0075] Where α1 is a positive number. Adjusting α1 can change the system's convergence time. Calibrate an appropriate α1 based on the actual vehicle model to balance the system's front wheel angle input jitter with the system error. λ is the sliding surface coefficient. Adjusting λ can adjust the controller's dynamic performance, stability, and resistance to external disturbances. Experimental results show that a larger λ value results in a faster system rejection of external disturbances caused by crosswinds, but this may lead to oscillation. A smaller λ value reduces the system's sensitivity to crosswind disturbances.

[0076] S3.2 Judgment and compensation calculation of external disturbance:

[0077] The external disturbance judgment module fits the change curve using the least squares method based on the vehicle's actual lateral acceleration, lateral velocity, and vehicle yaw angle data. When the fitting curve change period is less than the set threshold, it is determined that the vehicle is not disturbed by external crosswinds at this time, and the external disturbance judgment module outputs angle control instruction 3 equal to 0.

[0078] When the fitting curve changes with a period greater than the set threshold, it is determined that the vehicle is subject to regular external disturbances, and the external disturbance compensation module is used to calculate the compensation angle. Target lateral acceleration The current vehicle speed Vx, the current vehicle yaw rate The current vehicle heading and the target heading difference are calculated according to formula (6) to calculate the current moment disturbance compensation δ fd , the external disturbance compensation module outputs an angle control instruction 2 equal to δ fd .

[0079] From S3.1, we can see that the value of the generated angle compensation control instruction 2 is:

[0080]

[0081] If the vehicle is not disturbed by external crosswind, the external disturbance judgment module outputs an angle control instruction 3 equal to 0, and the external disturbance compensation module does not output an angle control instruction; if the vehicle is disturbed by external crosswind, the external disturbance compensation module outputs an angle control instruction 2 equal to δ fd , the external disturbance judgment module does not output angle control instructions.

[0082] Step S4. Add the angle compensation amount of angle control instruction 2 or angle control instruction 3 calculated in step S3 to the target control amount, angle control instruction = angle control instruction 1 + angle control instruction 2 + angle control instruction 3.

[0083] Step S5: The accumulated angle control command is sent to the vehicle steering actuator through the MCU real-time system to achieve compensation when there is crosswind disturbance.

[0084] Second embodiment

[0085] like Figure 4 As shown, this embodiment provides a control system for eliminating crosswind disturbances for high-speed automatic driving of a commercial vehicle, which is used to implement the control method for eliminating crosswind disturbances for high-speed automatic driving of a commercial vehicle described in the first embodiment, and specifically includes the following components:

[0086] Perception data processing unit: used to receive input information from on-board sensors, identify surrounding environment information, and output obstacle information to the decision-making and planning module.

[0087] Decision-making and planning module: used to plan a safe and comfortable vehicle target driving trajectory in real time based on the actual vehicle surrounding environment information and provide it to the control module.

[0088] Control module: used to calculate the target control instruction 1 through an optimization algorithm based on the deviation between the actual vehicle positioning and the target position.

[0089] External disturbance judgment module: used to judge whether the vehicle is subject to regular external disturbances at this time by fitting the change curve through the least squares method based on the actual lateral acceleration, lateral velocity and yaw angle data of the vehicle. If it is judged that the vehicle is not subject to regular external disturbances at this time, the target control instruction 3 = 0 is output.

[0090] External disturbance compensation module: When the external disturbance judgment module determines that the vehicle is subject to regular external disturbances, this module calculates the vehicle's lateral acceleration based on the curvature ρ of the target trajectory and the current vehicle's lateral acceleration. Target lateral acceleration The current vehicle speed Vx, the current vehicle yaw rate The current vehicle heading and the target heading difference are used to calculate the compensation amount of the disturbance at the current moment, and the target control instruction 2 is output.

[0091] MCU real-time system: used to send the accumulated angle control instructions (angle control instruction 1 + angle control instruction 2 + angle control instruction 3) to the vehicle steering actuator, so as to achieve compensation in the presence of crosswind disturbances.

[0092] The above describes the specific embodiments of the present invention. Based on the above description, relevant personnel can make various changes and modifications without departing from the scope of the technical concept of this invention.

Claims

1. A control method for eliminating crosswind disturbances during high-speed automatic driving of a commercial vehicle, characterized in that: The specific steps include: Step S1. The perception data processing unit receives input information from the vehicle sensor, identifies the surrounding environment information, and outputs obstacle information to the planning module; Step S2. The decision-making and planning module plans a safe and comfortable target vehicle driving trajectory in real time based on the actual vehicle surrounding environment information and sends it to the control module; the control module calculates the target control instruction 1 through an optimization algorithm based on the deviation between the actual vehicle positioning and the target position; Step S3. Add a disturbance feedforward compensation module. The disturbance feedforward compensation module consists of two parts: an external disturbance judgment module and an external disturbance compensation module. The module takes the vehicle longitudinal velocity, lateral velocity, lateral acceleration, yaw rate, trajectory target curvature, heading angle, and heading angular rate as module inputs, generates a compensation value for the external lateral disturbance, and outputs an angle control instruction. Specifically, the module includes the following steps: S3.1 Establishment of the external disturbance compensation model, specifically including the establishment of the vehicle force model and error model, crosswind disturbance modeling and sliding mode control, and the calculation formula for angle compensation is derived: Among them, v x is the vehicle longitudinal velocity, C f is the front wheel cornering stiffness, C r is the rear wheel cornering stiffness, is the rate of change of lateral displacement, L f is the distance from the front axle center to the center of mass, L r is the distance from the rear axle center to the center of mass, ψ is the yaw rate, δ f is the front wheel angle, λ is the sliding surface coefficient, λ>0; S3.2 External disturbance judgment and compensation calculation: The external disturbance judgment module judges whether the vehicle is disturbed by external crosswind according to the actual lateral acceleration, lateral velocity, and yaw angle data of the vehicle. If it is judged that the vehicle is not disturbed by external crosswind at this time, the external disturbance judgment module outputs angle control instruction 3 equal to 0; if it is judged that the vehicle is subject to regular external disturbance at this time, the compensation amount δ of the current disturbance is calculated according to the angle compensation calculation formula in S3.1 fd , and output the external disturbance compensation module output angle control instruction 2 equal to δ fd ; Step S4. Adding the angle compensation of the angle control instruction 2 or the angle control instruction 3 calculated in step S3 to the target angle control amount; Step S5. The accumulated target angle control amount is sent to the vehicle steering actuator through the MCU real-time system via the total angle control instruction, so as to achieve compensation in the presence of crosswind disturbances. The total angle control instruction = angle control instruction 1 + angle control instruction 2 + angle control instruction 3.

2. The control method for eliminating crosswind disturbances in high-speed automatic driving of a commercial vehicle according to claim 1 is characterized in that: In step S1 , the vehicle-mounted sensor input information includes: positioning data, camera data including lane line data, information input by the millimeter wave sensor including obstacle data on both sides, and vehicle status data including vehicle chassis data.

3. The control method for eliminating crosswind disturbances in high-speed automatic driving of a commercial vehicle according to claim 1 is characterized in that: In step S3.1, the vehicle force model is the following formula (1): Where, v x is the vehicle longitudinal velocity, C f is the front wheel cornering stiffness, C r is the rear wheel cornering stiffness, is the rate of change of lateral displacement, L f is the distance from the front axle center to the center of mass, L r is the distance from the rear axle center to the center of mass, is the yaw rate, δ f is the front wheel angle, I z is the longitudinal moment of inertia of the vehicle; The error model is: and y =and act -and ref (2) Where y act is the Y-axis coordinate of the vehicle's actual position, y ref is the y-axis coordinate of the target trajectory point, and ρ is the curvature of the target trajectory point; During the autonomous driving control process, it is necessary to calculate the appropriate δ f , so that e y =0, 4. The control method for eliminating crosswind disturbances in high-speed automatic driving of a commercial vehicle according to claim 3 is characterized in that: In step S3.1, for crosswind disturbance modeling and sliding mode control, the sliding film surface function is selected as follows: Where λ is the sliding surface coefficient, λ>0, substitute the expressions in equations (2) and (3) into equation (4), and take the first-order derivative of the sliding surface s to obtain: After the vehicle reaches steady state, the first-order sliding surface s = 0, and the front wheel angle compensation value δ under disturbance can be obtained by solving fd In the formula, α1 is a preset positive number. By adjusting the value of α1, the convergence time of the system can be changed.

5. The control method for eliminating crosswind disturbances in high-speed automatic driving of a commercial vehicle according to claim 1 is characterized in that: In step S3.2, the external disturbance judgment module uses the least squares method to fit the change curve to determine whether the vehicle is subject to regular external disturbances. When the change period of the fitting curve is less than the set threshold, it is judged that the vehicle is not subject to regular external disturbances at this time; when the change period of the fitting curve is greater than the set threshold, it is judged that the vehicle is subject to regular external disturbances at this time.

6. A control system for eliminating crosswind disturbances in high-speed automatic driving of commercial vehicles, characterized in that: The method for eliminating crosswind disturbance control for high-speed automatic driving of a commercial vehicle according to any one of claims 1 to 5 is used to implement the method, which specifically comprises the following components: Perception data processing unit: used to receive input information from vehicle sensors, identify surrounding environment information, and output obstacle information to the decision-making and planning module; Decision-making and planning module: used to plan a safe and comfortable vehicle target driving trajectory in real time based on the actual vehicle surrounding environment information and send it to the control module; Control module: used to calculate the target control instruction 1 through optimization algorithm according to the deviation between the actual vehicle positioning and the target position; External disturbance judgment module: used to judge whether the vehicle is subject to regular external disturbances based on the vehicle's actual lateral acceleration, lateral velocity, and vehicle yaw angle data by fitting the change curve using the least squares method. If it is judged that the vehicle is not subject to regular external disturbances, the target control instruction 3 = 0 is output; External disturbance compensation module: When the external disturbance judgment module determines that the vehicle is subject to regular external disturbances, this module calculates the vehicle's lateral acceleration based on the curvature ρ of the target trajectory and the current vehicle's lateral acceleration. Target lateral acceleration The current vehicle speed Vx, the current vehicle yaw rate The current vehicle heading and the target heading difference are used to calculate the compensation amount of the disturbance at the current moment, and the target control instruction 2 is output; Angle control instruction summary module: used to accumulate the angle compensation amount of angle control instruction 2 or angle control instruction 3 to angle control instruction 1 to form a total angle control instruction, and send the total angle control instruction to the MCU real-time system; MCU real-time system: used to send the accumulated total angle control command to the vehicle steering actuator to achieve compensation when there is crosswind disturbance. The total angle control command = angle control command 1 + angle control command 2 + angle control command 3.

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