Trailer angle detection method, trailer vehicle, medium and program product

Abstract

The invention discloses a trailer angle detection method for a trailer vehicle, the trailer vehicle, a medium and a program product. The towing vehicle comprises a towing vehicle head and a towing device detachably towed to the towing vehicle head, and the towing angle detection method comprises the steps that a rear laser radar arranged behind the towing vehicle head is used for collecting point cloud data of a part, at least comprising a reference target, of the towing device, and the reference target is located in an area below a vehicle frame of the towing device; performing clutter filtering processing on the point cloud data to obtain three-dimensional coordinate data representing the reference target; and obtaining the towing angle of the towing device relative to the towing vehicle head based on the obtained three-dimensional coordinate data of the reference target and the geometric position data of the reference target in the towing device. According to the method provided by the invention, the influence of the environment on the detection of the pull angle is small, and the full-angle high-precision detection can be carried out.

Description

Technical Field

[0001] The present invention relates to the technical field of lidar calibration, and more particularly to the technical field of detecting the towing angle of a towing vehicle with a towing device. Background Art

[0002] In recent years, in scenarios such as ports and airport cargo terminals, automated freight vehicles have gradually come into use. These vehicles typically use detachable tractor heads and towing devices to transport goods such as containers. During vehicle operation, the relative angle between the towing device and the tractor head (i.e., the towing angle) is crucial for the anti-collision system and path planning of automated driving. The accuracy and stability of the towing angle directly affect the safety and efficiency of vehicle automated driving. Therefore, high-precision detection of the towing angle is particularly important.

[0003] Currently, some electronic or magnetic-based angle detection devices have been used to detect the towing angle. However, for detachable towing devices, there are relatively high requirements for the installation and arrangement of electronic or magnetic angle detection devices.

[0004] Some existing towing angle detection solutions for automated driving vehicles mainly rely on lidars or cameras installed on the tractor head. Camera-based detection solutions are affected by environmental light and occlusion, and usually have low detection accuracy. For lidar-based solutions, most detect the side of the trailer, fit the side plane of the trailer using laser point clouds, and then calculate the towing angle. This solution is suitable for trailers with relatively flat sides, but for trailers with irregular sides, there will be problems where some detection angles cannot be detected, and the detection accuracy is significantly reduced compared to trailers with relatively flat sides.

[0005] In summary, with the development of technology, it is hoped that the existing solutions for measuring the towing angle of a towing vehicle using lidar can be improved to further enhance the accuracy and stability of towing angle detection, thereby improving the safety and efficiency of fully automated operation of automated freight vehicles in scenarios such as ports and airport cargo terminals. Summary of the Invention

[0006] To overcome the deficiencies in the prior art, the present invention provides a method for detecting the towing angle of a towed vehicle. The towed vehicle includes a towing tractor head and a towing device detachably towed to the towing tractor head. The method for detecting the towing angle includes: using a rear-mounted lidar disposed behind the towing tractor head to collect point cloud data of at least a part of the towing device including a reference target, where the reference target is located in the area below the frame of the towing device; performing clutter filtering processing on the point cloud data to obtain three-dimensional coordinate data representing the reference target; and obtaining the towing angle of the towing device relative to the towing tractor head based on the obtained three-dimensional coordinate data of the reference target and the geometric position data of the reference target in the towing device.

[0007] Preferably, performing clutter filtering processing on the point cloud data to obtain three-dimensional coordinate data representing the reference target further includes: performing noise filtering preprocessing based on the reflectivity information in the point cloud data to obtain preprocessed point cloud data; and filtering the preprocessed point cloud data through an Euclidean clustering algorithm to obtain three-dimensional coordinate data representing the reference target.

[0008] Preferably, obtaining the towing angle of the towing device relative to the towing tractor head based on the obtained three-dimensional coordinate data of the reference target and the geometric position data of the reference target in the towing device further includes: calculating the average value of the three-dimensional coordinate data to obtain the reference three-dimensional coordinates of the reference target; extracting the reference two-dimensional coordinate data of the reference target in the top view plane from the reference three-dimensional coordinates; calculating the towing angle of the towing device relative to the towing tractor head based on the reference two-dimensional coordinate data in the top view plane and the initial geometric position data of the reference target in the towing device; and outputting the towing angle.

[0009] Preferably, using a rear-mounted lidar disposed behind the towing tractor head to collect point cloud data of at least a part of the towing device including a reference target further includes: identifying the reference target within the scanning range of the rear-mounted lidar; and based on the identified reference target, using the rear-mounted lidar to scan and process within the corresponding scanning range to obtain point cloud data.

[0010] Preferably, the reference target identified within the scanning range of the rear-mounted lidar includes a pair of legs located at the bottom of the towing device, a pair of side guards on both sides of the towing device, or the main beam of the towing device.

[0011] According to another aspect of the present invention, when a freight vehicle is traveling along a long straight line, if the obtained towing angle is not zero, automatic zeroing calibration is performed.

[0012] According to another aspect of the present invention, the method includes: arranging the rear lidar behind the chassis of the tractor head.

[0013] In addition, the present invention provides an autonomous towing vehicle, which includes: a tractor head, at least one rear lidar is installed behind the chassis of the tractor head; and a control device, which is used to execute the above-mentioned towing angle detection method for the towing vehicle.

[0014] In addition, the present invention also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it realizes the above-mentioned towing angle detection method for the towing vehicle.

[0015] By using the method and system according to the present invention, the detection accuracy of the towing angle is high, and the actual verification accuracy can reach 0.001 rad. The detected angles are comprehensive without blind spots. Even when the towing device and the tractor head are in a straight line, the rear lidar can still output accurate towing angle values.

[0016] In addition, the arrangement of the rear lidar is not affected by bad weather. The rear lidar is installed directly behind the chassis of the tractor head. During the operation, a part of the towing device will cover the upper part, avoiding the influence of bad weather on the performance of the lidar. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] To more fully understand the present invention, reference may be made to the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0018] Figure 1 A side view schematic diagram of a tractor head equipped with a lidar according to a preferred embodiment of the present invention is shown.

[0019] Figure 2 A top view schematic diagram of a tractor head equipped with a lidar according to a preferred embodiment of the present invention is shown.

[0020] Figure 3 A top view schematic diagram showing the deflection of the towing device relative to the tractor head in the towing vehicle according to a preferred embodiment of the present invention is shown.

[0021] Figure 4 A flowchart of the towing angle detection method according to a preferred embodiment of the present invention is shown.

[0022] LIST OF REFERENCE NUMERALS

[0023] 1 Towing vehicle

[0024] 10 Tractor head

[0025] 11 Chassis

[0026] 12Front wheel

[0027] 13 Rear wheel

[0028] 15 Front LiDAR

[0029] 16 rear laser radar

[0030] 20 trailer

[0031] 21 Legs DETAILED DESCRIPTION

[0032] The present invention is further described below in conjunction with specific embodiments and drawings. More details are elaborated in the following description to facilitate a full understanding of the present invention. However, the present invention can obviously be implemented in a variety of other ways different from the description herein. Those skilled in the art can make similar generalizations and deductions based on actual application situations without violating the connotation of the present invention. Therefore, the protection scope of the present invention should not be limited by the content of this specific embodiment.

[0033] In the following description, the terms "first" and "second" are used for descriptive purposes only and shall not be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. The terms "front / front side" generally refer to the direction or side close to or toward the front of the towing vehicle, and the terms "rear / rear side" generally refer to the direction or side close to or toward the rear of the towing vehicle.

[0034] In the following description, "LiDAR" generally refers to a LiDAR system that includes a transmitter, a receiver, a scanning mechanism, and a data processing module. It acquires three-dimensional information such as the position, speed, and shape of the target object by emitting laser pulses and capturing echo signals. With the help of a multi-angle scanning mechanism, it builds a three-dimensional point cloud map and constructs a three-dimensional space model to provide contour information of the surrounding environment.

[0035] Figure 1 and Figure 2Side and top views of the tractor head 10 of the autonomous towing vehicle 1 according to a preferred embodiment of the present invention are respectively shown. The tractor head 10 is provided with a plurality of lidars 15, 16, which create three-dimensional point cloud data of the surrounding environment by emitting laser beams and receiving the reflected laser signals, and these data can be used for various purposes such as environmental perception, obstacle detection, positioning, and navigation. Specifically, the plurality of lidars of the tractor head 10 include front lidars 15 on the left and right sides in front of the top of the cab of the tractor head, and these front lidars 15 are preferably located on the front side of the front wheels 12 in the front-rear direction of the vehicle head. In addition, a rear lidar 16 is particularly provided at the rear of the tractor head 10 of the autonomous towing vehicle 1 according to the present invention for measuring the towing angle. The rear lidar 16 is generally located at the rear side of the rear wheels 13. In the height direction, the rear lidar 16 is preferably set lower than the front lidars 15.

[0036] Figure 3 A top view of the autonomous towing vehicle 1 according to a preferred embodiment of the present invention is shown. As Figure 3 shown, a towing device 20 is detachably connected behind the tractor head 10, and the tractor head 10 and the rear towing device 20 are not in a straight line. In other words, the axle of the tractor head 10 and the axle of the rear towing device 20 are not parallel, and there is an angle between them. Based on the rear lidar 16 installed behind the tractor head 10, the detection method according to the present invention can detect the towing angle between the tractor head 10 and the towing device 20 with high precision. In this detection method, laser point cloud is used, that is, by emitting a laser beam with a lidar and receiving the reflected signal, measuring the flight time or phase difference of the laser beam, so as to calculate the distance and three-dimensional coordinates of the target object, generating a set of a series of three-dimensional points, and in the following method, this set of points is called point cloud.

[0037] As Figure 4 shown, in a preferred embodiment, the method for detecting the towing angle between the tractor head 10 and the towing device 20 of the towing vehicle 1 includes the following steps:

[0038] Step 110: Using the rear lidar 16 provided behind the tractor head 10 to collect point cloud data of at least a part of the towing device 20 including a reference target, where the reference target is located in the area below the frame of the towing device 20;

[0039] Step 120: Performing a filtering process on the point cloud data to obtain three-dimensional coordinate data representing the reference target; and

[0040] Step 130: Obtain the angle of the trailer device 20 relative to the tractor head 10 based on the obtained three-dimensional coordinate data of the reference target and the geometric position data of the reference target in the trailer device 20.

[0041] According to a preferred embodiment, step 110 in the detection method may further include:

[0042] Step 111: Confirm the reference target within the scanning range of the rear lidar 16; and

[0043] Step 112: Based on the confirmed reference target, use the rear lidar 16 to scan and process within the corresponding scanning range to obtain point cloud data.

[0044] For a tractor head 10, different types or specifications of trailer devices 20 can be towed behind it to transport various types of goods. For different trailer devices 20, the reference targets determined for trailer angle detection may be different. The reference target is usually a component located below the frame of the trailer device 20 to correspond to the rear lidar 16 usually provided behind the chassis 11 of the tractor head 10. Applicable reference targets include paired legs at the bottom of the trailer device 20, paired side guards on both sides of the trailer device 20, or the main beam of the trailer device 20 (such as the main beam parallel to the axle closest to the tractor head). For some special trailer devices 20, dedicated physical components or marks can also be set as reference targets. For this reason, before scanning with the lidar, in step 111, the reference target can be determined according to the connected trailer device 20, or the reference target can be selected according to the scanned components. Subsequently, the method proceeds to step 112 for lidar scanning to obtain point cloud data.

[0045] According to a preferred embodiment, step 120 of the detection method may further include:

[0046] Step 121: Perform noise filtering processing based on the reflectivity information in the point cloud data to obtain preprocessed point cloud data; and

[0047] Step 122: Filter the preprocessed point cloud data through the Euclidean clustering algorithm to obtain three-dimensional coordinate data representing the reference target.

[0048] In step 121, reflectivity filtering of the laser point cloud is performed. In the point cloud data obtained by the lidar, the reflectivity information of different parts or components will vary due to the position, material, surface properties, etc. of the parts or components. Before performing the next data processing, the point cloud data can first be preliminarily screened and processed to remove points outside a specific reflectivity range. The "preprocessed point cloud data" here can be understood as mainly covering the three-dimensional coordinate data of the reference target.

[0049] To better execute the above-mentioned step 121, preferably, the component selected as the reference target or a specially set reference target may have a color, shape, or material surface property different from the surrounding environment to improve the efficiency of reflectivity filtering. Or, preferably, a material with high reflectivity is pasted or coated on the reference target of the towing device 20, so that the distinction between the reflectivity information of the reference target and other parts or components of the towing device 20 is increased. Thus, in step 121, through the reflectivity filtering of the laser point cloud, the preprocessed point cloud data that initially focuses on the reference target is efficiently extracted from the laser point cloud data.

[0050] In step 122, the Euclidean clustering algorithm is adopted. This is a clustering method based on distance measurement. It is mainly used to group the objects in the data set according to their similarity or distance to detect and separate different objects from the point cloud data. By setting an appropriate distance threshold, the algorithm can cluster the points belonging to the reference target together and separate the points of the reference target from the other parts of the towing vehicle 1.

[0051] According to a preferred embodiment, step 130 in the detection method may further include:

[0052] Step 131: Calculate the average value of the three-dimensional coordinate data to obtain the reference three-dimensional coordinates of the reference target;

[0053] Step 132: Extract the two-dimensional coordinate data of the reference target in the top view plane of the freight vehicle from the reference three-dimensional coordinates;

[0054] Step 133: Calculate the towing angle of the towing device 20 relative to the tractor head 10 based on the two-dimensional coordinate data in the top view plane and the initial geometric position data of the reference target in the towing device 20; and

[0055] Step 134: Output the towing angle.

[0056] As Figure 3As shown, a rear-mounted lidar is provided at the rear end of the chassis 11 of the tractor head 10 of the autonomous freight vehicle in the preferred embodiment, preferably centered. The rear-mounted lidar is connected to the control device. The rear-mounted lidar can transmit point cloud data to the control device usually located in the tractor head in real time. After receiving the point cloud data, the control device uses point cloud processing algorithms to perform processing such as noise filtering, characterization, and towing angle calculation, so as to obtain the towing angle in real time. The control device then sends the relevant results to the motor driver to control and adjust the speed and direction of the vehicle to achieve autonomous obstacle avoidance and navigation. The towing device 20, as a non-powered vehicle, generally includes a frame with a girder, a fifth wheel coupling device for connecting to the tractor head 10, a pair of legs 21 located at the bottom of the frame, a pair of side guards located on both sides of the frame, and the like. Advantageously, a pair of legs 21 can be selected as the reference target for towing angle detection. The legs 21 are usually arranged near the front side of the frame at the bottom of the frame. The two legs 21 are spaced apart and extend from the bottom of the frame to the ground for supporting. A reflective strip is pasted on the surface of the legs 21 facing the tractor head.

[0057] Hereinafter, taking the legs 21 with reflective materials pasted thereon as the reference target, the towing angle detection process for detecting the towing angle between the tractor head 10 of the towed vehicle 1 and the towing device 20 according to the present invention will be described.

[0058] First, step 111 is performed to confirm the reference target based on the scanning range of the rear-mounted lidar 16. Specifically, the lidar at the rear end of the rear side of the chassis 11 of the tractor head 10 scans the area below the frame of the towing device 20. When it is confirmed that the legs 21 are within the scanning range of the lidar, the legs are then confirmed as the reference target.

[0059] Then, step 112 is entered. Based on the selected reference target, the rear-mounted lidar scans and processes in the corresponding scanning range to obtain point cloud data. Specifically, the rear-mounted lidar 16 scans the area below the frame of the towing device 20 and obtains point cloud data. The point cloud data obtained by the rear-mounted lidar 16 generally includes distance information, angle information, and reflectivity intensity information of each data point.

[0060] The detection process enters step 121 to perform noise filtering processing based on the reflectivity information of the point cloud data to obtain preprocessed point cloud data. Specifically, since the legs 21 are pasted with reflective materials, a reasonable reflectivity threshold can be set according to the reflectivity characteristics of the reflective materials, and data points with a reflectivity (intensity) higher than the set threshold are screened out from the point cloud data, so as to obtain preprocessed point cloud data for the next step.

[0061] Subsequently, the process enters step 122, where the preprocessed point cloud data is filtered by the Euclidean clustering algorithm to obtain three-dimensional coordinate data representing the reference target. Specifically, the preprocessed point cloud data obtained in the previous step 121, which includes the point cloud data of the legs 21 with reflective materials attached and the point cloud data of other high-reflectivity surfaces, can identify and segment the point cloud data regarding the legs 21 through the Euclidean clustering algorithm, thereby obtaining three-dimensional coordinate data respectively representing the two legs 21.

[0062] The detection process enters step 131, where the average value of the three-dimensional coordinate data is calculated to obtain the reference three-dimensional coordinates of the reference target. Specifically, the three-dimensional coordinate data representing the two legs 21 was obtained in the previous step 122. In step 131, for each leg 21, the average value of the three-dimensional coordinate data of the leg 21 is calculated respectively, thereby obtaining the first reference three-dimensional coordinates regarding one leg 21 and the second reference three-dimensional coordinates regarding the other leg 21.

[0063] The detection process enters step 132, where the planar coordinate data of the reference target in the top view plane of the freight vehicle is extracted from the reference three-dimensional coordinates. Specifically, the three-dimensional point cloud data is projected onto a two-dimensional plane (XY plane), and the Z coordinate information (height information) in the first reference three-dimensional coordinates and the second reference three-dimensional coordinates is removed, while the X and Y coordinates are retained to form the reference two-dimensional coordinate data regarding the first leg 21 and the second leg 21 respectively.

[0064] The detection process enters step 133, where the angle of the trailer device 20 relative to the tractor head 10 is calculated based on the reference two-dimensional coordinate data in the top view plane and the initial geometric position data of the reference target in the trailer device 20. Specifically, a straight-line equation between the two positions is listed based on the reference two-dimensional coordinate data of the first leg 21 and the reference two-dimensional coordinate data of the second leg 21, and in combination with the initial geometric position data of the first leg 21 and the second leg 21, for example, in combination with the initial geometric positions of the first leg 21 and the second leg 21 when the trailer device 20 and the tractor head 10 are in a straight-line state, the relative angle between the trailer device 20 and the tractor head 10 is calculated.

[0065] Finally, the process proceeds to step 134 to output the trailer angle. Specifically, the trailer angle is output to the control device of the autonomous freight vehicle 1.

[0066] Based on the trailer angle, the control device can accurately achieve the autonomous driving and navigation of the autonomous freight vehicle, ensure road driving safety, and realize the fully automatic and safe transportation of goods.

[0067] In addition, an automatic zeroing step can be added to the method according to the present invention, that is, when the towed vehicle 1 travels along a long straight line, if the output towed angle is not zero, zeroing calibration is performed. In this way, the accuracy of the detection data can be ensured. This intelligent zeroing calibration mechanism reduces human intervention and improves the reliability and convenience of the vehicle system.

[0068] The present invention utilizes a rear lidar installed behind the chassis 11 of the towing vehicle head 10, which can accurately scan a specific reference target under the frame of the towing device 20 within an extremely short distance. The lidar 16 can capture subtle position changes of the reference target and accurately calculate the towed angle based on the positional relationship of these reference targets on the towed vehicle. Through actual verification, the detection accuracy of the towed angle according to the present invention can reach 0.001 rad.

[0069] In addition, by adopting the towed angle detection method according to the present invention, even when the towing device 20 is completely aligned with the towing vehicle head 10, the rear lidar 16 can still provide accurate observation data. This full-angle monitoring ability ensures that in any situation, the vehicle control device can accurately understand the position state of the towing device 20, thereby improving the safety of vehicle driving.

[0070] According to the present invention, the detection of the towed angle can avoid the influence of various adverse weather conditions. The lidar 16 is cleverly installed at the rear end of the chassis 11 of the towing vehicle head 10. During the operation process, it will be covered by a part of the towing device 20, usually by the towing pin connection device, thus avoiding the influence of adverse weather such as rain and snow on the performance of the lidar. On the other hand, the method can select the components located under the frame of the towing device 20 as the reference target, which also reduces the adverse influence of adverse weather during detection. Therefore, the vehicle system according to the present invention can work stably in various environments.

[0071] In addition, in addition to measuring the towed angle, the rear lidar 16 can also provide real-time monitoring and perception in the directly rear direction for the automatic driving system of the towed vehicle 1, which is used to support functions such as the reverse driving of the towing vehicle head and automatic coupling.

[0072] The method according to the present invention can be implemented by being executed by a computer program processor, and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium herein may include: any entity or device capable of carrying a computer program, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disc, a computer memory, a read-only memory (ROM), a random access memory (RAM), and a software distribution medium, etc. The computer program includes computer program code. The computer program code may be in the form of source code, object code, an executable file, or some intermediate form, etc. The computer-readable storage medium may include: any entity or device capable of carrying a computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disc, a computer memory, a read-only memory (ROM), a random access memory (RAM), and a software distribution medium, etc.

[0073] In addition, any process or method description shown in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present application includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in a reverse order according to the involved functions, rather than in the order shown or discussed, which should be understood by those skilled in the technical field to which the embodiments of the present application belong.

[0074] In addition, those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been generally described according to their functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0075] Although the present invention is disclosed above with preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, any modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for detecting the towing angle of a towed vehicle, where the towed vehicle includes a towing tractor and a towing device detachably towed to the towing tractor. The method for detecting the towing angle between the towing tractor and the towing device includes: Collecting point cloud data of at least a part of the towing device including a reference target by using a rear-mounted lidar arranged behind the towing tractor, where the reference target is located in the area below the frame of the towing device; Performing clutter filtering processing on the point cloud data to obtain three-dimensional coordinate data representing the reference target; And Obtaining the towing angle of the towing device relative to the towing tractor based on the obtained three-dimensional coordinate data of the reference target and the geometric position data of the reference target in the towing device.

2. The trailer angle detection method according to claim 1, characterized in that, Performing clutter filtering processing on the point cloud data to obtain three-dimensional coordinate data representing the reference target further includes: Performing noise point filtering preprocessing based on the reflectivity information in the point cloud data to obtain preprocessed point cloud data; and Filtering the preprocessed point cloud data through an Euclidean clustering algorithm to obtain three-dimensional coordinate data representing the reference target.

3. The trailer angle detection method according to claim 1, wherein Obtaining the towing angle of the towing device relative to the towing tractor based on the obtained three-dimensional coordinate data of the reference target and the geometric position data of the reference target in the towing device further includes: Calculating the average value of the three-dimensional coordinate data to obtain the reference three-dimensional coordinates of the reference target; Extracting the reference two-dimensional coordinate data of the reference target in the top view plane from the reference three-dimensional coordinates; Calculating the towing angle of the towing device relative to the towing tractor based on the reference two-dimensional coordinate data in the top view plane and the initial geometric position data of the reference target in the towing device; and Outputting the towing angle.

4. The trailer angle detection method according to claim 1, characterized in that Collecting point cloud data of at least a part of the towing device including a reference target by using a rear-mounted lidar arranged behind the towing tractor further includes: Confirming the reference target by the scanning range of the rear-mounted lidar; Based on the confirmed reference target, using the rear-mounted lidar to scan and process in the corresponding scanning range to obtain point cloud data.

5. The trailer angle detection method according to claim 4, characterized in that, The reference target confirmed by the scanning range of the rear-mounted lidar includes a pair of legs at the bottom of the towing device, a pair of side guards on both sides of the towing device, or the girder of the towing device.

6. The trailer angle detection method according to claim 1, wherein, When the vehicle travels along a long straight line, if the obtained towing angle is not zero, zero calibration is performed.

7. The trailer angle detection method according to claim 1, wherein The method includes: Setting the rear-mounted lidar at the rear end of the chassis of the towing tractor.

8. A towed vehicle, where the autonomous towed vehicle includes: A towing tractor, with at least one rear-mounted lidar installed behind the chassis of the towing tractor; And A control device for executing the above method for detecting the towing angle of a towed vehicle.

9. A computer-readable storage medium storing a computer program, characterized in that When the computer program is executed by a processor, it implements the method according to any one of claims 1 to 7.

10. A computer program product, the computer program product comprising a computer program, characterized in that, when the computer program is executed by a processor, it implements the method according to any one of claims 1 to 9.

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