Method and system for acquiring trailer included angle of vehicle, vehicle and equipment

Abstract

The invention discloses a trailer included angle obtaining method and system of a vehicle, the vehicle and equipment. The method for obtaining the trailer included angle of the vehicle comprises the steps of obtaining a dynamic model of the vehicle; the difference value between the tractor course angle and the trailer course angle of the vehicle sensed by the sensing module is obtained; according to the dynamic model and the difference value between the tractor course angle and the trailer course angle, a change rate function of the trailer included angle along with time is obtained; and determining the trailer included angle according to the change rate function of the trailer included angle along with the time. By the adoption of the method, hardware sensors such as a rotary encoder are not used, structural change of a vehicle chassis is avoided, sensors do not need to be added, the vehicle cost is saved, multi-source sensor information is fused, sensing, positioning and vehicle chassis information are effectively combined, and the robustness of included angle estimation is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a method, system, vehicle and equipment for obtaining a trailer angle of a vehicle. Background Art

[0002] In the field of autonomous driving trucks, the trailer angle (i.e., the relative angle between the trailer and the tractor) is a key parameter that affects the vehicle's dynamic behavior, control stability, and safety. Accurately estimating the trailer angle is of great significance for improving the robustness of the autonomous driving system, optimizing path planning, and controlling strategies. At present, the common trailer angle estimation methods mainly include: First, the measurement method based on vehicle sensors, which measures the vehicle's posture and motion state through IMU (inertial measurement unit), GPS, wheel angle sensor and other devices to calculate the trailer angle; second, the estimation method based on the vehicle dynamics model, which uses a single vehicle model or a vehicle dynamics model with a trailer, combined with the position and speed information of the truck and trailer, and uses state estimation algorithms such as Kalman filter (KF), extended Kalman filter (EKF) or unscented Kalman filter (UKF) to calculate the angle; third, the estimation method based on vision and radar, which detects the outline of the trailer through a camera, and uses image processing and deep learning technology to calculate the trailer angle, or uses millimeter-wave radar or lidar to detect the relative position change between the tractor and the trailer, thereby estimating the angle.

[0003] The above scheme has the following shortcomings: First, the sensor measurement error is large and the environmental adaptability is poor. The IMU is affected by drift error. Long-term operation may lead to inaccurate angle estimation. Hardware sensors such as rotary encoders may be affected by installation errors and mechanical wear, reducing measurement accuracy. Second, the dynamic model estimation method is highly dependent on parameters. Vehicle parameters (such as tire stiffness and suspension characteristics) are difficult to obtain accurately, resulting in model deviation. When the vehicle is in non-uniform motion (such as acceleration, sudden braking, and ramp driving), the traditional dynamic model may not be able to accurately describe the changes in the trailer angle, making it difficult to achieve robust angle estimation. Summary of the invention

[0004] Based on this, it is necessary to provide a method, system, vehicle and equipment for obtaining the trailer angle of a vehicle in response to the above-mentioned technical problems. This method can avoid using hardware sensors such as rotary encoders, avoid structural changes to the vehicle chassis and the need to add sensors, thereby saving vehicle costs. By fusing multi-source sensor information and effectively combining perception, positioning and vehicle chassis information, the robustness of angle estimation can be improved.

[0005] In a first aspect, a method for obtaining a trailer angle of a vehicle is provided, comprising:

[0006] Obtaining a dynamic model of the vehicle;

[0007] Obtaining a difference between a tractor heading angle and a trailer heading angle of the vehicle sensed by the perception module;

[0008] Obtaining a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle;

[0009] The trailer angle is determined according to the rate of change function of the trailer angle over time.

[0010] In some examples, before obtaining the rate of change function of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle, the method further includes:

[0011] The dynamic model is simplified to obtain a simplified model, wherein the simplified model includes a function of the rate of change of the tractor's heading angle over time and a function of the rate of change of the trailer's heading angle over time.

[0012] In some examples, obtaining a function of the rate of change of the trailer angle over time based on the dynamic model and the difference between the tractor heading angle and the trailer heading angle includes:

[0013] The rate of change function of the trailer angle over time is obtained according to the simplified model and the difference between the tractor heading angle and the trailer heading angle of the vehicle sensed by the perception module.

[0014] In some examples, determining the trailer angle according to the rate of change function of the trailer angle over time includes:

[0015] Linearizing the rate of change function of the trailer angle over time;

[0016] Discretize the rate of change function of trailer angle with time after linearization to obtain the Kalman filter prediction model;

[0017] The trailer angle is obtained according to the Kalman filter prediction model.

[0018] In some examples, the linearizing the rate of change function of the trailer angle over time includes:

[0019] Obtaining a linearized position, wherein the linearized position is a corresponding position of the trailer angle sensed at the calculation time and the front wheel turning angle obtained by the chassis at the calculation time;

[0020] The rate of change function of the trailer angle over time is linearized at the linearization position to obtain the rate of change function of the trailer angle over time after linearization.

[0021] In some examples, obtaining a dynamic model of the vehicle includes:

[0022] Get the parameters of the vehicle;

[0023] A dynamic model of the vehicle is obtained according to the parameters of the vehicle.

[0024] In a second aspect, a system for obtaining a trailer angle of a vehicle is provided, comprising:

[0025] An acquisition module, used for obtaining a dynamic model of a vehicle;

[0026] a difference determination module, configured to obtain a difference between a tractor heading angle and a trailer heading angle of the vehicle sensed by the perception module;

[0027] A generating module, for obtaining a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle;

[0028] The determination module is used to determine the trailer angle according to the rate of change function of the trailer angle over time.

[0029] In a third aspect, a vehicle is provided, comprising: a trailer angle acquisition system for the vehicle according to the second aspect.

[0030] In a fourth aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the method for obtaining the trailer angle of a vehicle according to the first aspect and any possible implementation of the first aspect are implemented.

[0031] In a fifth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the steps of the method for obtaining the trailer angle of a vehicle in the above-mentioned first aspect and any possible implementation of the first aspect are implemented.

[0032] In a sixth aspect, a computer program product is provided, on which a computer program is stored, and when the program is executed by a processor, the steps of the method for obtaining the trailer angle of a vehicle in the above-mentioned first aspect and any possible implementation of the first aspect are implemented.

[0033] By adopting the embodiment of the present application, the dynamic model of the vehicle is obtained, the difference between the heading angle of the tractor and the heading angle of the trailer of the vehicle sensed by the perception module is obtained, and the rate of change function of the trailer angle over time is obtained according to the dynamic model and the difference between the heading angle of the tractor and the heading angle of the trailer. Finally, the trailer angle is determined according to the rate of change function of the trailer angle over time. It is possible to avoid structural changes to the vehicle chassis and the need to add sensors without using hardware sensors such as rotary encoders, saving vehicle costs, and effectively combining perception, positioning and vehicle chassis information by fusing multi-source sensor information to improve the robustness of angle estimation. The fusion estimation algorithm using multi-source data has high robustness. It has excellent performance under single-source noise and multi-source noise conditions. It is also insensitive to positioning errors and steering errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0035] Figure 1 A flow chart of a method for obtaining a trailer angle of a vehicle provided in an embodiment of the present application;

[0036] Figure 2 A schematic diagram of vehicle parameters in a method for obtaining a vehicle trailer angle provided in an embodiment of the present application;

[0037] Figure 3 The performance of the vehicle trailer angle acquisition method provided in the embodiment of the present application under single-source noise;

[0038] Figure 4 The performance of the vehicle trailer angle acquisition method provided in the embodiment of the present application under multi-source noise conditions;

[0039] Figure 5 A schematic diagram showing the characteristics of the vehicle trailer angle acquisition method provided in an embodiment of the present application being insensitive to positioning errors;

[0040] Figure 6 A schematic diagram showing the characteristics of the method for obtaining the trailer angle of a vehicle provided in an embodiment of the present application being insensitive to steering errors;

[0041] Figure 7 A structural block diagram of a vehicle trailer angle acquisition system provided in an embodiment of the present application;

[0042] Figure 8 A structural block diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The present application is further described in detail below in conjunction with the embodiments and drawings. It is to be understood that the specific embodiments described herein are only used to explain the relevant application, rather than to limit the application. It is also necessary to explain that, for ease of description, only the parts related to the application are shown in the drawings.

[0044] It should be noted that, in the absence of conflict, the embodiments of the present application, that is, the features of the embodiments, can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0045] The following describes in detail the method, system, vehicle and equipment for obtaining the trailer angle of a vehicle according to an embodiment of the present application in conjunction with the accompanying drawings.

[0046] Figure 1 FIG. 1 is a flow chart of a method for obtaining a vehicle trailer angle according to an embodiment of the present application. Figure 1 As shown, the method for obtaining the trailer angle of a vehicle according to an embodiment of the present application includes the following steps:

[0047] S101: Obtain a dynamic model of the vehicle.

[0048] In one embodiment of the present application, obtaining a dynamic model of a vehicle includes: acquiring parameters of the vehicle; and obtaining the dynamic model of the vehicle according to the parameters of the vehicle.

[0049] Take a truck with a trailer as an example, Figure 2 As shown, the vehicle parameters include but are not limited to the tractor rear axle center x 1 Coordinate, y center of rear axle of tractor 1 Coordinates, tractor heading angle, tractor wheelbase, tractor rear axle center speed, trailer rear axle center x 2 Coordinate, trailer rear axle center y 2 Coordinates, trailer heading angle, trailer wheelbase, speed of the trailer rear axle center point, tractor front wheel steering angle, distance from the tractor rear axle center to the hinge point, and speed at the hinge point, etc.

[0050] Based on these vehicle parameters, the vehicle dynamics model is obtained. For example, the vehicle dynamics formula for a semi-trailer commercial vehicle is:

[0051]

[0052] After obtaining the dynamic model of the vehicle, it can be simplified. Specifically, the dynamic model is simplified to obtain a simplified model, wherein the simplified model includes a function of the rate of change of the tractor's heading angle over time and a function of the rate of change of the trailer's heading angle over time. That is, since the heading angle of the trailer is calculated in the trailer pose estimation, the above dynamic model can be simplified to the following model:

[0053]

[0054] S102: Obtaining a difference between a tractor heading angle and a trailer heading angle of the vehicle sensed by a perception module.

[0055] S103: Obtain a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle.

[0056] In one embodiment of the present application, a rate of change function of the trailer angle over time is obtained based on the dynamic model and the difference between the tractor heading angle and the trailer heading angle, including: obtaining a rate of change function of the trailer angle over time based on the simplified model and the difference between the tractor heading angle and the trailer heading angle of the vehicle sensed by the perception module.

[0057] Since the angle of the trailer sensed by the perception module is the difference between the heading angle of the tractor and the heading angle of the trailer, let e = ψ 2 -ψ 1 = -λ, v = v x，1 .

[0058] S104: Determine the trailer angle according to the rate of change function of the trailer angle over time.

[0059] In one embodiment of the present application, determining the trailer angle based on the rate function of the trailer angle changing over time includes: linearizing the rate function of the trailer angle changing over time; discretizing the linearized rate function of the trailer angle changing over time to obtain a Kalman filter prediction model; and obtaining the trailer angle based on the Kalman filter prediction model.

[0060] In this example, the rate function of the trailer angle changing over time is linearized, including: obtaining a linearized position, wherein the linearized position is the corresponding position of the trailer angle sensed at the calculation moment and the front wheel turning angle obtained by the chassis at the calculation moment; linearizing the rate function of the trailer angle changing over time at the linearized position to obtain the linearized rate function of the trailer angle changing over time.

[0061] As a specific example, from formula 1-2 we can get:

[0062]

[0063] For formula 1-3 in (e k , δ k ) is linearized (i.e., a first-order Taylor expansion is performed), we can obtain:

[0064]

[0065] in:

[0066]

[0067] Among them, e k is the trailer angle perceived at the time of calculation, d k It is the front wheel turning angle obtained by the chassis at the time of calculation (for example, calculated by the steering wheel angle).

[0068] Discretizing formula 1-4 using the Euler formula, we can get the prediction equation of the Kalman filter:

[0069] e n =Fe n-1 +Bδ+d+w (1-6)

[0070] in:

[0071]

[0072] Where w is the process noise and follows a normal distribution.

[0073] The observation equation of Kalman filter is:

[0074] z n =e n +v (1-8)

[0075] Among them, v is the observation noise, which obeys the normal distribution. The trailer angle of the fused truck can be obtained through the Kalman filter calculation formula.

[0076] According to the method for acquiring the trailer angle of a vehicle in an embodiment of the present application, a dynamic model of the vehicle is obtained, the difference between the tractor heading angle and the trailer heading angle of the vehicle sensed by the perception module is obtained, and the rate of change function of the trailer angle over time is obtained according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle. Finally, the trailer angle is determined according to the rate of change function of the trailer angle over time. It is possible to avoid structural changes to the vehicle chassis and the need to add sensors without using hardware sensors such as rotary encoders, saving vehicle costs. By fusing multi-source sensor information, the perception, positioning and vehicle chassis information are effectively combined to improve the robustness of the angle estimation. The fusion estimation algorithm using multi-source data has high robustness. It has excellent performance under single-source noise and multi-source noise conditions. It is also insensitive to positioning errors and steering errors.

[0077] like Figure 3 , Figure 4 , Figure 5 and Figure 6 As shown, Figure 3Shows the performance under single source noise, Figure 4 Shows performance under multi-source noise conditions, Figure 5 It shows the insensitivity to positioning errors. Figure 6 The characteristic performance is shown to be insensitive to steering errors.

[0078] Figure 7 FIG. 1 is a structural block diagram of a vehicle trailer angle acquisition system according to an embodiment of the present application. Figure 7 As shown, the vehicle trailer angle acquisition system according to the embodiment of the present application includes: an acquisition module 710, a difference determination module 720, a generation module 730 and a determination module 740, wherein:

[0079] An acquisition module 710 is used to obtain a dynamic model of the vehicle;

[0080] A difference determination module 720, for obtaining a difference between a tractor heading angle and a trailer heading angle of the vehicle sensed by the perception module;

[0081] A generating module 730, for obtaining a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle;

[0082] The determination module 740 is used to determine the trailer angle according to the rate of change function of the trailer angle over time.

[0083] Before obtaining the rate of change function of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle, the method further includes:

[0084] The dynamic model is simplified to obtain a simplified model, wherein the simplified model includes a function of the rate of change of the tractor's heading angle over time and a function of the rate of change of the trailer's heading angle over time.

[0085] Wherein, the rate of change function of the trailer angle over time is obtained according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle, including:

[0086] The rate of change function of the trailer angle over time is obtained according to the simplified model and the difference between the tractor heading angle and the trailer heading angle of the vehicle sensed by the perception module.

[0087] Wherein, determining the trailer angle according to the rate of change function of the trailer angle over time includes:

[0088] Linearizing the rate of change function of the trailer angle over time;

[0089] Discretize the rate of change function of trailer angle with time after linearization to obtain the Kalman filter prediction model;

[0090] The trailer angle is obtained according to the Kalman filter prediction model.

[0091] The linearization of the rate of change function of the trailer angle over time includes:

[0092] Obtaining a linearized position, wherein the linearized position is a corresponding position of the trailer angle sensed at the calculation time and the front wheel turning angle obtained by the chassis at the calculation time;

[0093] The rate of change function of the trailer angle over time is linearized at the linearization position to obtain the rate of change function of the trailer angle over time after linearization.

[0094] Wherein, obtaining the dynamic model of the vehicle includes:

[0095] Get the parameters of the vehicle;

[0096] A dynamic model of the vehicle is obtained according to the parameters of the vehicle.

[0097] According to the trailer angle acquisition system of the vehicle of the embodiment of the present application, the dynamic model of the vehicle is obtained, the difference between the tractor heading angle and the trailer heading angle of the vehicle sensed by the perception module is obtained, and the rate of change function of the trailer angle over time is obtained according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle. Finally, the trailer angle is determined according to the rate of change function of the trailer angle over time. It is possible to avoid structural changes to the vehicle chassis and the need to add sensors without using hardware sensors such as rotary encoders, saving vehicle costs. By fusing multi-source sensor information, the perception, positioning and vehicle chassis information are effectively combined to improve the robustness of the angle estimation. The fusion estimation algorithm using multi-source data has high robustness. It has excellent performance under single-source noise and multi-source noise conditions. And it is insensitive to positioning errors and steering errors.

[0098] The specific definition of the trailer angle acquisition system of the vehicle can be found in the definition of the trailer angle acquisition method of the vehicle mentioned above, which will not be repeated here. The various modules of the trailer angle acquisition system of the vehicle mentioned above can be implemented in whole or in part by software, hardware and their combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0099] Furthermore, a vehicle is provided, comprising: a trailer angle acquisition system for a vehicle according to any one of the above embodiments. The vehicle can avoid using hardware sensors such as rotary encoders, avoid structural changes to the vehicle chassis and do not need to add sensors, saving vehicle costs. By fusing multi-source sensor information, it effectively combines perception, positioning and vehicle chassis information to improve the robustness of angle estimation. The fusion estimation algorithm using multi-source data has high robustness. It has excellent performance under single-source noise and multi-source noise conditions. It is also insensitive to positioning errors and steering errors.

[0100] In addition, other structures and functions of the vehicle according to the embodiment of the present application are known to ordinary technicians in the field and will not be elaborated here.

[0101] In one embodiment, a computer device is provided. Figure 8 This is a block diagram of the computer device provided in the embodiment of the present application, refer to Figure 8 The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the method for obtaining the trailer angle of the vehicle described above is implemented. For example, the following steps are performed: obtaining a dynamic model of the vehicle;

[0102] Obtaining a difference between a tractor heading angle and a trailer heading angle of the vehicle sensed by the perception module;

[0103] Obtaining a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle;

[0104] The trailer angle is determined according to the rate of change function of the trailer angle over time.

[0105] The embodiment of the present application further provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and the processor executes the computer program to implement the above-mentioned vehicle trailer angle acquisition method embodiment. For example, the following steps are performed: obtaining a vehicle dynamics model;

[0106] Obtaining a difference between a tractor heading angle and a trailer heading angle of the vehicle sensed by the perception module;

[0107] Obtaining a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle;

[0108] The trailer angle is determined according to the rate of change function of the trailer angle over time.

[0109] The present application embodiment provides a computer program product, which includes instructions. When the instructions are executed, the method described in the embodiment of the present application is executed. For example, it can be executed Figure 1 The various steps of the method for obtaining the trailer angle of the vehicle shown, for example, are performed: obtaining a dynamic model of the vehicle;

[0110] Obtaining a difference between a tractor heading angle and a trailer heading angle of the vehicle sensed by the perception module;

[0111] Obtaining a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle;

[0112] The trailer angle is determined according to the rate of change function of the trailer angle over time.

[0113] Those of ordinary skill in the art can understand that all or part of the processes in the methods for implementing the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0114] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0115] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A method for obtaining a trailer angle of a vehicle, characterized in that: include: Obtaining a dynamic model of the vehicle; Obtaining a difference between a tractor heading angle and a trailer heading angle of the vehicle sensed by the perception module; Obtaining a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle; The trailer angle is determined according to the rate of change function of the trailer angle over time.

2. The method for obtaining the trailer angle of a vehicle according to claim 1, characterized in that: Before obtaining the rate of change function of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle, the method further includes: The dynamic model is simplified to obtain a simplified model, wherein the simplified model includes a function of the rate of change of the tractor's heading angle over time and a function of the rate of change of the trailer's heading angle over time.

3. The method for obtaining the trailer angle of a vehicle according to claim 2, characterized in that: The method of obtaining a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle comprises: The rate of change function of the trailer angle over time is obtained according to the simplified model and the difference between the tractor heading angle and the trailer heading angle of the vehicle sensed by the perception module.

4. The method for obtaining the trailer angle of a vehicle according to claim 1, characterized in that: Determining the trailer angle according to the rate of change function of the trailer angle over time includes: Linearizing the rate of change function of the trailer angle over time; Discretize the rate of change function of trailer angle with time after linearization to obtain the Kalman filter prediction model; The trailer angle is obtained according to the Kalman filter prediction model.

5. The method for obtaining the trailer angle of a vehicle according to claim 4, characterized in that: The linearizing of the rate of change function of the trailer angle over time includes: Obtaining a linearized position, wherein the linearized position is a corresponding position of the trailer angle sensed at the calculation time and the front wheel turning angle obtained by the chassis at the calculation time; The rate of change function of the trailer angle over time is linearized at the linearization position to obtain the rate of change function of the trailer angle over time after linearization.

6. The method for obtaining the vehicle trailer angle according to any one of claims 1 to 5, characterized in that: The obtaining of the dynamics model of the vehicle comprises: Get the parameters of the vehicle; A dynamic model of the vehicle is obtained according to the parameters of the vehicle.

7. A vehicle trailer angle acquisition system, characterized in that: include: An acquisition module, used for obtaining a dynamic model of a vehicle; a difference determination module, configured to obtain a difference between a tractor heading angle and a trailer heading angle of the vehicle sensed by the perception module; A generating module, for obtaining a function of the rate of change of the trailer angle over time according to the dynamic model and the difference between the tractor heading angle and the trailer heading angle; The determination module is used to determine the trailer angle according to the rate of change function of the trailer angle over time.

8. A vehicle, characterized in that: include: The vehicle trailer angle acquisition system according to claim 7.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method for obtaining the trailer angle of the vehicle according to any one of claims 1-6 is implemented.

10. A computer-readable storage medium, comprising a memory and a computer program stored in the memory and executable on a processor, characterized in that: When the program is executed by a processor, the method for obtaining the trailer angle of a vehicle according to any one of claims 1 to 6 is implemented.

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