Lateral control compensation method for automatic driving vehicle on roll road

Abstract

The invention relates to the technical field of automatic driving, in particular to a transverse control compensation method for an automatic driving vehicle on a roll road. Comprising the following steps: according to a closed-loop control algorithm, obtaining a transverse control quantity for driving a vehicle along a road center line; measuring a roll angle of the vehicle-mounted inertial navigation system, and judging whether the vehicle is in an inclined road working condition; calculating the compensation amount of transverse control according to the roll angle and the transverse deviation; calculating according to the transverse control quantity and the compensation quantity to obtain a transverse control instruction required by automatic driving of the vehicle; the vehicle executes the transverse control instruction, whether the number of times of executing the transverse control instruction by the vehicle reaches a threshold value or not is judged, and if yes, the process is ended; and if not, the process is cycled again. The fuzzy control theory is adopted, the transverse control quantity is dynamically compensated according to the inclination angle and the transverse deviation of the vehicle, and the transverse control precision and the driving safety of the automatic driving vehicle on the inclined road are improved.

Description

Technical Field

[0001] This invention relates to the field of autonomous driving technology, and in particular to a method for lateral control compensation of autonomous vehicles on tilted roads. Background Technology

[0002] In recent years, autonomous driving technology has developed rapidly. Assisted driving technologies such as cruise control, adaptive cruise control, and lane keeping have gradually entered people's daily transportation lives, demonstrating enormous development potential and broad application prospects. Lateral control technology is one of the key technologies in the field of autonomous driving. It changes the vehicle's heading and yaw rate by controlling the steering system, while ensuring comfort, safety, and following accuracy. Following accuracy is an important indicator for evaluating lateral control technology.

[0003] Current research mainly focuses on vehicle dynamics modeling and algorithm optimization, emphasizing the solution of upper-level control algorithm problems. On flat roads, dynamics modeling is simple, and fewer factors affect the lateral control of the vehicle, allowing traditional algorithms to achieve high-precision lateral control. However, when autonomous vehicles travel on inclined roads, the lateral control accuracy of traditional algorithms decreases, impacting the safety of autonomous driving. Summary of the Invention

[0004] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this invention provides a lateral control compensation method for autonomous vehicles on inclined roads, which dynamically compensates for lateral control quantities based on the vehicle's tilt angle and lateral deviation, thereby improving the lateral control accuracy and driving safety of autonomous vehicles on inclined roads.

[0005] This invention provides a method for lateral control compensation of autonomous vehicles on tilted roads, comprising the following steps: S1: Based on the pure tracking algorithm, obtain the lateral control quantity that makes the vehicle travel along the center line of the road; S2: Measure the vehicle roll angle of the vehicle-mounted inertial navigation system to determine whether the vehicle is in a tilted road condition. If it is in a tilted road condition, proceed to S3; otherwise, proceed to S5. S3: Calculate the compensation amount for lateral control based on the vehicle roll angle and lateral deviation; S4: Calculate the lateral control commands required for autonomous driving of the vehicle based on the lateral control quantity and compensation quantity; S5: The vehicle executes a lateral control command. Determine whether the number of times the vehicle executes the lateral control command has reached the threshold. If yes, end the process; otherwise, return to step S1.

[0006] According to the present invention, a lateral control compensation method for an autonomous vehicle on a tilted road includes step S1: The lateral control parameters for a vehicle traveling along the road centerline are calculated using a pure tracking method: in, Lateral control variables calculated for an autonomous driving system. The distance between the front and rear wheels of a vehicle. This refers to the lateral deviation of the vehicle from the centerline of the road. This is the aiming distance.

[0007] According to the present invention, a lateral control compensation method for an autonomous vehicle on a tilted road includes step S2: Based on the absolute value of the vehicle's roll angle, a comparison with a threshold is made to determine whether the vehicle is on a sloping road. Then it is in the condition of a sloping road; if Then it is not in a sloping road condition, among which, The vehicle roll angle, This is the threshold value for the vehicle roll angle.

[0008] According to the present invention, a lateral control compensation method for an autonomous vehicle on a tilted road includes step S3 as follows: S31: Set the universe of discourse for the input variable: in, This is the lateral deviation. This represents the lower limit of the lateral deviation. This represents the upper limit of the lateral deviation. The vehicle roll angle, This represents the lower limit of the vehicle's roll angle. This represents the upper limit of the vehicle's roll angle. For compensation amount, This is the lower limit of the compensation amount. This is the upper limit of the compensation amount; S32: Fuzzyenize the vehicle roll angle and lateral deviation, and define the roll angle fuzzy set as {roll angle negative large, roll angle negative medium, roll angle negative small, roll angle zero, roll angle positive small, roll angle positive medium, roll angle positive large}, and the lateral deviation fuzzy set as {deviation negative large, deviation negative medium, deviation negative small, deviation zero, deviation positive small, deviation positive medium, deviation positive large}. Calculate the vehicle roll angle membership degree based on the vehicle roll angle, and calculate the lateral deviation membership degree based on the vehicle lateral deviation. S33: The compensation amount is the output variable of the fuzzy control. Define the fuzzy set of the compensation amount {compensation negative large, compensation negative medium, compensation negative small, compensation zero, compensation positive small, compensation positive medium, compensation positive large}, and use a Gaussian function as the membership function. The input is the compensation amount, and the output is the membership degree of the compensation amount. S34: Develop fuzzy rules for lateral deviation, vehicle roll angle, and compensation amount; S35: Based on the membership degree of vehicle roll angle and lateral deviation and fuzzy rules, derive the membership degree set of compensation amount; S36: Using a discretized numerical integration method, the membership degree of the compensation quantity is defuzzified to obtain the compensation quantity. .

[0009] According to the present invention, a lateral control compensation method for an autonomous vehicle on a tilted road is provided, wherein step S32 includes: S321: Calculate the vehicle roll angle membership degree based on the vehicle roll angle: in, Let i be the membership degree corresponding to the i-th state in the tilt angle fuzzy set. For the i-th state of the tilt angle fuzzy set, Let be the variance parameter of the tilt angle fuzzy set, and i be the state ordinal number of the tilt angle fuzzy set, i=1,2,...,7; S322: Calculate the membership degree of lateral deviation based on vehicle lateral deviation: in, Let j be the membership degree corresponding to the j-th state in the lateral deviation fuzzy set. There are j states with lateral deviation fuzziness. Let j be the variance parameter of the lateral deviation fuzzy set, and j be the state ordinal number of the lateral deviation fuzzy set, j=1,2,...,7.

[0010] According to the lateral control compensation method for autonomous vehicles on lateral roads provided by the present invention, the fuzzy rules for the lateral deviation, vehicle roll angle and compensation amount in step S34 are shown in Table 1: Table 1 Fuzzy Rule Table .

[0011] According to the present invention, a lateral control compensation method for an autonomous vehicle on a tilted road includes step S36: in, For the k-th state of the fuzzy set of compensation quantity, Let be the membership degree corresponding to the k-th state in the fuzzy set of compensation quantities, where k is the state ordinal number of the fuzzy set of compensation quantities, k=1,2,...,7.

[0012] According to the present invention, an autonomous driving vehicle lateral control compensation method for a side-tilting road is provided, wherein the method for providing the lateral control commands required for autonomous driving of the vehicle in step S4 is as follows: in, For lateral control, These are the lateral control commands required for autonomous driving of vehicles.

[0013] The present invention also provides a lateral control compensation system for autonomous vehicles on tilted roads, comprising: Control quantity calculation module: Based on the pure tracking algorithm, obtain the lateral control quantity that enables the vehicle to travel along the center line of the road; Tilt Angle Detection Module: Used to measure the tilt angle of the vehicle's inertial navigation system and determine whether the vehicle is in a tilted road condition. If it is in a tilted road condition, it enters the compensation calculation module; otherwise, it enters the control execution module. Compensation Calculation Module: Used to calculate the compensation amount for lateral control based on the roll angle and lateral deviation; Control command calculation module: used to calculate the lateral control commands required for autonomous driving of the vehicle based on the lateral control quantity and compensation quantity; Control execution module: Used for the vehicle to execute lateral control commands, and determines whether the number of times the vehicle executes lateral control commands has reached the threshold. If yes, the process ends; otherwise, it returns to the step control quantity calculation module.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the lateral control compensation method for autonomous vehicles on tilted roads as described above.

[0015] The above-described one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects: This invention provides a lateral control compensation method for autonomous vehicles on inclined roads. By using fuzzy control theory, the lateral control quantity is dynamically compensated based on the vehicle tilt angle and lateral deviation, thereby improving the lateral control accuracy and driving safety of autonomous vehicles on inclined roads.

[0016] It overcomes the problem that traditional algorithms suffer from reduced lateral control accuracy when autonomous vehicles are driving on inclined roads, which affects the safety of autonomous driving.

[0017] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the lateral control compensation method for autonomous vehicles on tilted roads provided by the present invention.

[0020] Figure 2 This is a map showing the membership distribution of vehicle tilt angles.

[0021] Figure 3 This is a distribution diagram of the lateral deviation membership degree.

[0022] Figure 4 This is a membership distribution diagram of the compensation amount.

[0023] Figure 5 This is a diagram showing the driving route, road inclination angle, and route curvature of the vehicle in an embodiment of the present invention.

[0024] Figure 6 This is a comparison diagram of the lateral deviation between the embodiments of the present invention and the conventional method.

[0025] Figure 7 This is a function graph of the compensation amount in an embodiment of the present invention.

[0026] Figure 8 This is a structural block diagram of the lateral control compensation device for autonomous vehicles on tilted roads provided by the present invention.

[0027] Figure 9 This is a schematic diagram of the structure of the electronic device provided by the present invention.

[0028] Figure Labels 810, Processor; 820, Communication interface; 830, Memory; 840, Communication bus. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention. The following embodiments are used to illustrate this invention but cannot be used to limit the scope of this invention.

[0030] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0031] The following is combined with Figures 1 to 9 This invention is described.

[0032] Example like Figure 1 As shown, Figure 1 This invention provides a flowchart illustrating a method for lateral control compensation of an autonomous vehicle on a tilted road, comprising the following steps: S1: Based on the pure tracking algorithm, obtain the lateral control quantity that makes the vehicle travel along the center line of the road; S2: Measure the vehicle roll angle of the vehicle-mounted inertial navigation system to determine whether the vehicle is in a tilted road condition. If it is in a tilted road condition, proceed to S3; otherwise, proceed to S5. S3: Calculate the compensation amount for lateral control based on the vehicle roll angle and lateral deviation; S4: Calculate the lateral control commands required for autonomous driving of the vehicle based on the lateral control quantity and compensation quantity; S5: The vehicle executes a lateral control command. Determine whether the number of times the vehicle executes the lateral control command has reached the threshold. If yes, end the process; otherwise, return to step S1.

[0033] Specifically, step S1 includes: The lateral control parameters for a vehicle traveling along the road centerline are calculated using a pure tracking method: in, Lateral control variables calculated for an autonomous driving system. The distance between the front and rear wheels of a vehicle. This refers to the lateral deviation of the vehicle from the centerline of the road. This is the aiming distance.

[0034] Specifically, step S2 includes: Based on the absolute value of the vehicle's roll angle, a comparison with a threshold is made to determine whether the vehicle is on a sloping road. Then it is in the condition of a sloping road; if Then it is not in a sloping road condition, among which, The vehicle roll angle, This is the threshold value for the vehicle roll angle.

[0035] Specifically, step S3 includes: S31: Set the universe of discourse for the input variable: in, This is the lateral deviation. This represents the lower limit of the lateral deviation. This represents the upper limit of the lateral deviation. The vehicle roll angle, This represents the lower limit of the vehicle's roll angle. This represents the upper limit of the vehicle's roll angle. For compensation amount, This is the lower limit of the compensation amount. This is the upper limit of the compensation amount; considering the actual conditions of autonomous vehicles on roads, to avoid excessively high sensitivity of fuzzy control or untimely compensation actions, the domain of discourse for the vehicle tilt angle is set to... The universe of discourse for the lateral bias is set as The universe of discourse for the compensation quantity is set to .

[0036] S32: Fuzzyenize the vehicle roll angle and lateral deviation, defining the roll angle fuzzy set as {negative large roll angle, negative medium roll angle, negative small roll angle, zero roll angle, positive small roll angle, positive medium roll angle, positive large roll angle}, and calculate the vehicle roll angle membership degree based on the vehicle roll angle: in, Let i be the membership degree corresponding to the i-th state in the tilt angle fuzzy set. For the i-th state of the tilt angle fuzzy set, Let be the variance parameter of the tilt angle fuzzy set, and i be the state ordinal number of the tilt angle fuzzy set, i=1,2,...,7; Vehicle tilt angle membership distribution as follows Figure 2 As shown in the embodiments of the present invention The values ​​are [-12, -8, -4, 0, 4, 8, 12]. The value is 2, in the embodiments of the present invention. When the angle is -6deg, the membership set of the vehicle tilt angle is {0.011, 0.606, 0.606, 0.011, 0, 0, 0}.

[0037] The fuzzy set of lateral deviation {negative large deviation, negative medium deviation, negative small deviation, zero deviation, positive small deviation, positive medium deviation, positive large deviation} is used to calculate the vehicle roll angle membership degree based on the vehicle roll angle, and the lateral deviation membership degree is calculated based on the vehicle lateral deviation. in, Let j be the membership degree corresponding to the j-th state in the lateral deviation fuzzy set. There are j states with lateral deviation fuzziness. Let j be the variance parameter of the lateral deviation fuzzy set, and j be the state ordinal number of the lateral deviation fuzzy set, j=1,2,...,7.

[0038] Lateral deviation membership distribution as follows Figure 3 As shown in the embodiments of the present invention The values ​​are [-0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6]. The value is 0.1, in this embodiment of the invention. When the deviation is 0.3m, the membership set of the lateral deviation is {0, 0, 0, 0.011, 0.606, 0.606, 0.011}.

[0039] S33: The compensation amount is the output variable of the fuzzy control. A fuzzy set of compensation amounts is defined as {compensation negative large, compensation negative medium, compensation negative small, compensation zero, compensation positive small, compensation positive medium, compensation positive large}, and a Gaussian function is used as the membership function. The input is the compensation amount, and the output is the membership degree of the compensation amount. Compensation amount membership function: in, The membership degree corresponding to the k-th state in the fuzzy set of compensation quantities. For the k-th state of the fuzzy set of compensation quantity, Let be the variance parameter of the fuzzy set of the compensation quantity, and k be the state ordinal number of the fuzzy set of the compensation quantity, k = 1, 2, ..., 7. The membership distribution of the compensation quantity is as follows: Figure 4 As shown in the embodiments of the present invention. The values ​​are [-0.9, -0.6, -0.3, 0, 0.3, 0.6, 0.9]. The value is 0.12.

[0040] S34: Formulating Fuzzy Rules for Lateral Deviation, Vehicle Roll Angle, and Compensation Amount. The fuzzy rules for lateral deviation, vehicle roll angle, and compensation amount in step S34 are shown in Table 1. Table 1 Fuzzy Rule Table

[0041] S35: Based on the membership degrees of the vehicle roll angle and lateral deviation, and fuzzy rules, derive the membership set of the compensation amount. (In this embodiment of the invention) -6deg When the value is 0.3m, the membership set of the compensation amount The expression is {0, 0, 0, 0.606, 0.606, 0.011, 0}; S36: Using a discretized numerical integration method, the membership degree of the compensation quantity is defuzzified to obtain the compensation quantity. .

[0042] Step S36 includes: in, For the k-th state of the fuzzy set of compensation quantity, Let be the membership degree corresponding to the k-th state in the fuzzy set of compensation quantities, where k is the state ordinal number of the fuzzy set of compensation quantities, k=1,2,...,7.

[0043] Specifically, the method for providing lateral control commands required for autonomous driving in step S4 is as follows: in, These are the lateral control commands required for autonomous driving of vehicles.

[0044] This invention proposes a lateral control compensation method for autonomous vehicles on inclined roads, improving the lateral control accuracy and driving safety of autonomous vehicles on sloping roads. When the vehicle activates its autonomous driving function and is on an inclined road, the lateral control compensation is calculated based on the vehicle's tilt angle and lateral deviation. This invention is tested using the Matlab-Carsim co-simulation platform. The driving route, road tilt angle, and route curvature diagram of the vehicle's driving path in this embodiment are shown below. Figure 5 As shown. Figure 5 (a) shows the simulated vehicle's driving route. Figure 5 In the middle (b), the road inclination and trajectory curvature of the simulated road are shown.

[0045] like Figure 6 As shown, the lateral deviations of not using the present invention and using the present invention are very large. The extreme value of the lateral deviation without the compensation method of the present invention is -1.58m, while the extreme value of the lateral deviation with the compensation method of the present invention is -0.63m, which greatly improves the lateral control accuracy.

[0046] Compensation amount such as Figure 7 As shown, during the operation of an autonomous vehicle, the method proposed in this invention dynamically adjusts the compensation amount based on the vehicle's tilt angle and lateral deviation.

[0047] like Figure 8As shown, the present invention also provides a lateral control compensation system for autonomous vehicles on tilted roads, comprising: Control quantity calculation module: Based on the pure tracking algorithm, obtain the lateral control quantity that enables the vehicle to travel along the center line of the road; Tilt Angle Detection Module: Used to measure the tilt angle of the vehicle's inertial navigation system and determine whether the vehicle is in a tilted road condition. If it is in a tilted road condition, it enters the compensation calculation module; otherwise, it enters the control execution module. Compensation Calculation Module: Used to calculate the compensation amount for lateral control based on the roll angle and lateral deviation; Control command calculation module: used to calculate the lateral control commands required for autonomous driving of the vehicle based on the lateral control quantity and compensation quantity; Control execution module: Used for the vehicle to execute lateral control commands, and determines whether the number of times the vehicle executes lateral control commands has reached the threshold. If yes, the process ends; otherwise, it returns to the step control quantity calculation module.

[0048] Figure 9 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 9 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 can call logical instructions from the memory 830 to execute a lateral control compensation method for an autonomous vehicle on a side-tilt road, the method including: S1: Based on the closed-loop control algorithm, obtain the lateral control quantity that enables the vehicle to travel along the centerline of the road; S2: Measure the vehicle roll angle of the vehicle-mounted inertial navigation system to determine whether the vehicle is in a tilted road condition. If it is in a tilted road condition, proceed to S3; otherwise, proceed to S5. S3: Calculate the compensation amount for lateral control based on the vehicle roll angle and lateral deviation; S4: Calculate the lateral control commands required for autonomous driving of the vehicle based on the lateral control quantity and compensation quantity; S5: The vehicle executes a lateral control command. Determine whether the number of times the vehicle executes the lateral control command has reached the threshold. If yes, end the process; otherwise, return to step S1.

[0049] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0050] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0051] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0053] It should be noted that the embodiments of this disclosure can be implemented using hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a programmable memory or a data carrier such as an optical or electronic signal carrier.

[0054] Furthermore, although the operation of the methods of this disclosure is described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Rather, the steps depicted in the flowcharts may be performed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps. It should also be noted that the features and functions of two or more devices according to this disclosure may be embodied in one device. Conversely, the features and functions of one device described above may be further divided and embodied by multiple devices.

[0055] While this disclosure has been described with reference to several specific embodiments, it should be understood that this disclosure is not limited to the specific embodiments disclosed. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A method for lateral control compensation of an autonomous vehicle on a tilted road, characterized in that, Includes the following steps: S1: Based on the pure tracking algorithm, obtain the lateral control quantity that makes the vehicle travel along the center line of the road; S2: Measure the vehicle roll angle of the vehicle-mounted inertial navigation system to determine whether the vehicle is in a tilted road condition. If it is in a tilted road condition, proceed to S3; otherwise, proceed to S5. S3: Calculate the compensation amount for lateral control based on the vehicle roll angle and lateral deviation; S4: Calculate the lateral control commands required for autonomous driving of the vehicle based on the lateral control quantity and compensation quantity; S5: The vehicle executes a lateral control command. Determine whether the number of times the vehicle executes the lateral control command has reached the threshold. If yes, end the process; otherwise, return to step S1.

2. The lateral control compensation method for an autonomous vehicle on a tilted road according to claim 1, characterized in that, Step S1 includes: The lateral control parameters for a vehicle traveling along the road centerline are calculated using a pure tracking algorithm: in, For lateral control, The distance between the front and rear wheels of a vehicle. This is the lateral deviation. This is the aiming distance.

3. The lateral control compensation method for an autonomous vehicle on a tilted road according to claim 1, characterized in that, Step S2 includes: Based on the absolute value of the vehicle's roll angle, a comparison with a threshold is made to determine whether the vehicle is on a sloping road. Then it is in the condition of a sloping road; if Then it is not in a sloping road condition, among which, The vehicle roll angle, This is the threshold value for the vehicle roll angle.

4. The lateral control compensation method for an autonomous vehicle on a tilted road according to claim 1, characterized in that, Step S3 includes: S31: Set the universe of discourse for the input variable: in, This is the lateral deviation. This represents the lower limit of the lateral deviation. This represents the upper limit of the lateral deviation. The vehicle roll angle, This represents the lower limit of the vehicle's roll angle. This represents the upper limit of the vehicle's roll angle. For compensation amount, This is the lower limit of the compensation amount. This is the upper limit of the compensation amount; S32: Fuzzyenize the vehicle roll angle and lateral deviation, defining the roll angle fuzzy set as {roll angle negative large, roll angle negative medium, roll angle negative small, roll angle zero, roll angle positive small, roll angle positive medium, roll angle positive large}; and the lateral deviation fuzzy set as {deviation negative large, deviation negative medium, deviation negative small, deviation zero, deviation positive small, deviation positive medium, deviation positive large}. Calculate the vehicle roll angle membership degree based on the vehicle roll angle, and calculate the lateral deviation membership degree based on the vehicle lateral deviation. S33: The compensation amount is the output variable of the fuzzy control. Define the fuzzy set of the compensation amount {compensation negative large, compensation negative medium, compensation negative small, compensation zero, compensation positive small, compensation positive medium, compensation positive large}, and use a Gaussian function as the membership function. The input is the compensation amount, and the output is the membership degree of the compensation amount. S34: Develop fuzzy rules for lateral deviation, vehicle roll angle, and compensation amount; S35: Based on the membership degree of vehicle roll angle and lateral deviation and fuzzy rules, derive the membership degree set of compensation amount; S36: Using a discretized numerical integration method, the membership degree of the compensation quantity is defuzzified to obtain the compensation quantity. .

5. A lateral control compensation method for an autonomous vehicle on a side-tilting road according to claim 4, characterized in that, Step S32 includes the following steps: S321: Calculate the vehicle roll angle membership degree based on the vehicle roll angle: in, Let i be the membership degree corresponding to the i-th state in the tilt angle fuzzy set. For the i-th state of the tilt angle fuzzy set, Let be the variance parameter of the tilt angle fuzzy set, and i be the state ordinal number of the tilt angle fuzzy set, i=1,2,...,7; S322: Calculate the membership degree of lateral deviation based on vehicle lateral deviation: in, Let j be the membership degree corresponding to the j-th state in the lateral deviation fuzzy set. There are j states with lateral deviation fuzziness. Let j be the variance parameter of the lateral deviation fuzzy set, and j be the state ordinal number of the lateral deviation fuzzy set, j=1,2,...,7.

6. A lateral control compensation method for an autonomous vehicle on a tilted road according to claim 4, characterized in that, The fuzzy rules for lateral deviation, vehicle roll angle, and compensation amount in step S34 are shown in Table 1: Table 1 Fuzzy Rule Table 。 7. A lateral control compensation method for an autonomous vehicle on a tilted road according to claim 4, characterized in that, Step S36 includes: in, For the k-th state of the fuzzy set of compensation quantity, Let be the membership degree corresponding to the k-th state in the fuzzy set of compensation quantities, where k is the state ordinal number of the fuzzy set of compensation quantities, k=1,2,...,7.

8. A lateral control compensation method for an autonomous vehicle on a side-tilting road according to claim 4, characterized in that, The method for providing lateral control commands required for autonomous driving in step S4 is as follows: in, For lateral control, These are the lateral control commands required for autonomous driving of vehicles.

9. A lateral control compensation system for an autonomous vehicle on a laterally tilted road, used to execute the lateral control compensation method for an autonomous vehicle on a laterally tilted road as described in any one of claims 1 to 8, characterized in that, include: Control quantity calculation module: Based on the pure tracking algorithm, obtain the lateral control quantity that enables the vehicle to travel along the center line of the road; Tilt Angle Detection Module: Used to measure the tilt angle of the vehicle's inertial navigation system and determine whether the vehicle is in a tilted road condition. If it is in a tilted road condition, it enters the compensation calculation module; otherwise, it enters the control execution module. Compensation Calculation Module: Used to calculate the compensation amount for lateral control based on the roll angle and lateral deviation; Control command calculation module: used to calculate the lateral control commands required for autonomous driving of the vehicle based on the lateral control quantity and compensation quantity; Control execution module: Used for the vehicle to execute lateral control commands, and determines whether the number of times the vehicle executes lateral control commands has reached the threshold. If yes, the process ends; otherwise, it returns to the step control quantity calculation module.

10. An electronic device, comprising a processor, a communication interface, a memory, and a communication bus, characterized in that, When the processor executes a computer program, it implements the steps of the lateral control compensation method for an autonomous vehicle on a tilted road as described in any one of claims 1 to 8.

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