A method, device, and vehicle for measuring trailer angle.

Abstract

This invention provides a method, device, and vehicle for measuring trailer angle, relating to the field of vehicle technology. It is applied to a semi-trailer comprising a tractor and a trailer; at least one multi-line lidar is installed on each side of the tractor; the method includes: obtaining an initial trailer model with the trailer angle as its initial value in a pre-set vehicle coordinate system, and obtaining initial point cloud data on the initial trailer model; controlling the multi-line lidars installed on both sides of the tractor to emit lasers, causing the surface of the trailer to reflect the lasers emitted by the multi-line lidars; controlling each multi-line lidar to receive its corresponding laser point cloud reflected from the surface of the trailer; and calculating the trailer angle using a point cloud matching algorithm based on the corresponding laser point cloud received by each multi-line lidar and the initial point cloud data. This invention provides a simple, fast, and accurate method for measuring trailer angle.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to a method, device, and vehicle for measuring trailer angle. Background Technology

[0002] Currently, with the development of the logistics and transportation industry, the application of semi-trailers (including container trucks and trailers) is becoming increasingly widespread. As a heavy-duty transportation tool, semi-trailers, compared to monocoque trucks, can improve the overall economic efficiency of road transportation. Furthermore, with the development of autonomous driving technology, the trailer angle (e.g., ...) is becoming increasingly important. Figure 1 The top view of the semi-trailer shown shows that the trailer angle (α) refers to the angle between the centerline of the tractor 11 and the centerline of the trailer 12. As the basis for autonomous driving planning and control points, it has become the focus of research.

[0003] Current methods for measuring trailer angles can only be used when the trailer angle is relatively small. For scenarios with larger trailer angles (e.g., greater than ±40°), accurate measurements are difficult to obtain. Therefore, developing a simple, fast, and accurate method for measuring trailer angles has become a pressing issue. Summary of the Invention

[0004] Embodiments of the present invention provide a method, device, and vehicle for measuring trailer angle, so as to achieve a simple, fast, and accurate method for measuring trailer angle.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] On one hand, embodiments of the present invention provide a method for measuring the trailer angle, applied to a semi-trailer, the semi-trailer including a tractor and a trailer; at least one multi-line lidar is respectively provided on both sides of the tractor;

[0007] The method for measuring the trailer angle includes:

[0008] Under a pre-set vehicle coordinate system, the initial model of the trailer with the trailer angle as the initial value is obtained, and the initial point cloud data on the initial model of the trailer is obtained.

[0009] The multi-line lidars installed on both sides of the tractor emit lasers, causing the surface of the trailer to reflect the lasers emitted by the multi-line lidars.

[0010] Control each multi-line lidar to receive the corresponding laser point cloud reflected from the surface of the trailer;

[0011] Based on the corresponding laser point cloud received by each multi-line lidar and the initial point cloud data, the trailer angle is calculated using a point cloud matching algorithm.

[0012] In another aspect, embodiments of the present invention also provide a trailer angle measuring device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described trailer angle measuring method.

[0013] In another aspect, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method for measuring the trailer angle.

[0014] In another aspect, embodiments of the present invention also provide a vehicle, including the aforementioned trailer angle measuring device, as well as a tractor and a trailer; at least one multi-line lidar is respectively provided on both sides of the tractor; the trailer angle measuring device is communicatively connected to the multi-line lidar.

[0015] This invention provides a method, device, and vehicle for measuring trailer angle. It employs at least one multi-line lidar on each side of the tractor unit, which illuminates the trailer surface. The trailer angle is calculated using a point cloud matching algorithm based on the laser point clouds received by each multi-line lidar and an initial point cloud. Furthermore, this invention calculates the trailer angle using the initial point cloud data (based on the laser point clouds received by each multi-line lidar and the trailer angle itself) instead of relying on the laser point cloud data from a single lidar, significantly improving accuracy. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a diagram showing the included angle of the trailer;

[0018] Figure 2 A flowchart of a method for measuring the trailer angle provided in an embodiment of the present invention. Figure 1 ;

[0019] Figure 3 This is a bottom view of the semi-trailer structure in an embodiment of the present invention;

[0020] Figure 4 This is a schematic diagram of the working scenario when only one lidar is installed at the rear of the tractor in an embodiment of the present invention;

[0021] Figure 5 This is a schematic diagram of the working scenario when a multi-line lidar is installed on each side of the tractor in an embodiment of the present invention;

[0022] Figure 6 This is a schematic diagram showing the distribution of multi-line lidar on both sides of the tractor in this embodiment of the invention. Figure 1 ;

[0023] Figure 7 This is a schematic diagram showing the distribution of multi-line lidar on both sides of the tractor in this embodiment of the invention. Figure 2 ;

[0024] Figure 8 A flowchart of a method for measuring the trailer angle provided in an embodiment of the present invention. Figure 2 ;

[0025] Figure 9 This is a schematic diagram of the acquisition environment of the external multi-line lidar in an embodiment of the present invention;

[0026] Figure 10 This is a schematic diagram of the preset area range in an embodiment of the present invention;

[0027] Figure 11 This is a schematic diagram of a lidar coordinate system established in an embodiment of the present invention;

[0028] Figure 12 This is a schematic diagram of the curve of the angle data to be processed in an embodiment of the present invention;

[0029] Figure 13 This is a schematic diagram of the vehicle structure in an embodiment of the present invention. Detailed Implementation

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0031] To enable those skilled in the art to better understand the present invention, some technical terms involved in the embodiments of the present invention are explained below:

[0032] Point cloud: In reverse engineering, the collection of point data on the surface of an object obtained by measuring instruments is called a point cloud.

[0033] ICP (Iterative Closest Point) is a algorithm primarily used for precise stitching of depth images in computer vision. It achieves accurate stitching by iteratively minimizing the corresponding points between the source and target data. Many variations exist, with the main focus being on achieving efficient and robust stitching results.

[0034] SVD: Singular Value Decomposition is a reliable method for solving translation vectors and rotation matrices.

[0035] like Figure 2 As shown, this embodiment of the invention provides a method for measuring the trailer angle, applicable to applications such as... Figure 3 ( Figure 3 The image shows a semi-trailer 20 (bottom view). The semi-trailer 20 includes a tractor unit 201 and a trailer 202, connected by a pivot 205, allowing the trailer 202 to rotate relative to the tractor unit 201. At least one multi-line lidar 203 is provided on each side of the tractor unit 201 (e.g., the left and right sides of the front of the tractor unit 201, i.e., the left and right sides of the vehicle's front). (For example, there could be one, two, or more multi-line lidars on each side.) Figure 3 Due to limitations, only the case where one multi-line lidar is set on each of the left and right sides is shown (this is only shown in the case where one multi-line lidar is set on each of the left and right sides).

[0036] The method for measuring the trailer's included angle includes:

[0037] Step 301: Under the pre-set vehicle coordinate system, obtain the initial model of the trailer when the trailer angle is the initial value, and obtain the initial point cloud data on the initial model of the trailer.

[0038] Step 302: Control the multi-line lidars installed on both sides of the tractor to emit lasers, so that the surface of the trailer reflects the lasers emitted by the multi-line lidars.

[0039] Step 303: Control each multi-line lidar to receive the corresponding laser point cloud reflected from the surface of the trailer.

[0040] Step 304: Based on the corresponding laser point cloud and initial point cloud data received by each multi-line lidar, the trailer angle is calculated using a point cloud matching algorithm.

[0041] Here, as Figure 4As shown, a reflector 204 with a reflective surface can be fixedly installed at the front of the trailer 202, and a lidar 206 (usually located in the middle of the rear of the tractor 201, typically a single-line lidar) can be installed at the rear of the tractor 201. The reflective surface faces the lidar 206. Considering that even with only one lidar 206 at the rear of the tractor 201, lasers can be emitted towards the reflective surface of the reflector 204, the trailer angle can generally be measured using this single lidar 206. However, for scenarios with a large trailer angle, such as... Figure 4 As shown, the reflector 204 may have moved to the side of the tractor 201, entering the blind zone of the lidar 206. The laser emitted by the lidar 206 alone can no longer reach the reflective surface of the reflector 204, causing the measurement of the trailer angle to fail. Therefore, in this embodiment of the invention, the following method can also be used... Figure 4 The method shown is used to measure the trailer angle in scenarios with a small trailer angle (e.g., less than 40°), while steps 301 to 304 are used to measure the trailer angle in scenarios with a large trailer angle (e.g., greater than or equal to 40°), but the method is not limited to this. Steps 301 to 304 in this embodiment can also be used to measure the trailer angle in scenarios with a small trailer angle.

[0042] And such Figure 5 As shown, the present invention employs at least one multi-line lidar 203 on each side of the tractor 201 (e.g., the left and right sides of the front of the tractor 201, i.e., the left and right sides of the front face). (For example, one, two, or more multi-line lidars can be set on each side.) Figure 5 (Due to limitations, only the case where one multi-line lidar is set on each of the left and right sides is shown.) In this way, when the reflector 204 moves to the side of the tractor 201, the laser emitted by at least one of the multi-line lidars can hit the surface of the trailer, thus enabling it to be used to measure the trailer angle. Furthermore, this invention calculates the trailer angle using initial point cloud data based on the laser point clouds received by each multi-line lidar and the trailer angle as the initial value, rather than using the laser point cloud of a single lidar, significantly improving the accuracy of the result.

[0043] Here, to indicate that at least one multi-line lidar 203 is installed on each side of the tractor 201, such as Figure 6 and Figure 7 As shown, the multi-line lidar 203 can be distributed at the front end of the tractor 201 in such a way that there is one multi-line lidar 203 on each of the left and right sides. Figure 6 ), or each has two multi-line lidars 203 ( Figure 7However, it is not limited to this. Without considering the cost, even more multi-line lidars can be set up on the left and right sides.

[0044] To enable those skilled in the art to better understand the present invention, a more detailed embodiment is described below, such as... Figure 8 As shown, this embodiment of the invention provides a method for measuring the trailer angle, applied to the above-mentioned... Figure 3 The semi-trailer 20 shown has had its structure described above and will not be repeated here. The method includes:

[0045] Step 401: In the pre-set vehicle coordinate system, a pre-set external multi-line lidar is used to emit lasers to both sides of the trailer when the trailer angle is 0°, so that the surfaces on both sides of the trailer reflect the lasers emitted by the external multi-line lidar.

[0046] Step 402: Control the external multi-line lidar to receive the laser point cloud reflected from the surfaces on both sides of the trailer.

[0047] Step 403: Use the iterative nearest point algorithm to obtain the initial model of the trailer when the included angle of the trailer is 0° by using the laser point cloud reflected from the surfaces on both sides of the trailer, and obtain the initial point cloud data on the initial model of the trailer.

[0048] Generally, steps 401 to 403 above can be performed in the following manner: Figure 9 As shown, a bracket 501 can be installed on one side of the vehicle's driving lane, and an external multi-line lidar 502 can be mounted on this bracket 501 (e.g., at a height of 2m or more). This allows the vehicle to maintain a trailer angle of 0°, entering the laser emission range of the external multi-line lidar 502 from one side and then from the other side. This ensures that both sides of the trailer are illuminated by the laser, and the external multi-line lidar 502 can collect laser point clouds from both sides of the trailer. After iterative nearest-point algorithm, an initial trailer model with a 0° trailer angle can be obtained, leading to initial point cloud data on the initial trailer model, denoted as {Pt}.

[0049] Step 404: Control the multi-line lidars installed on both sides of the tractor to emit lasers, so that the surface of the trailer reflects the lasers emitted by the multi-line lidars.

[0050] It is worth noting that the multi-line lidar and external multi-line lidar used in the embodiments of the present invention can be, for example, 16-line, 32-line, or 64-line lidars, but are not limited to these.

[0051] Step 405: Control each multi-line lidar to receive the corresponding laser point cloud reflected from the surface of the trailer.

[0052] Generally, the sampling frequency of each multi-line lidar can be 10Hz, but it is not limited to this. Furthermore, each multi-line lidar carries its own corresponding identifier when emitting laser light, ensuring that when receiving the laser point cloud reflected from the trailer's surface, it only receives its own corresponding laser point cloud and not the laser point clouds corresponding to other multi-line lidars. Additionally, to ensure that the initial trailer angles corresponding to each multi-line lidar are arranged according to the acquisition time in the current cycle in subsequent step 408, the acquisition times of each multi-line lidar are preferably different to avoid two or more initial trailer angles being together at the same acquisition time, making them difficult to distinguish. Furthermore, due to the structural characteristics of the semi-trailer 20, when a certain trailer angle exists, generally only one side of the multi-line lidar can receive the laser point cloud reflected from the trailer's surface.

[0053] Step 406: Preprocess the corresponding laser point clouds received by each multi-line lidar, and use the iterative nearest point algorithm to obtain the initial trailer angle corresponding to each multi-line lidar based on the initial point cloud data and the preprocessed laser point cloud.

[0054] Step 406 here can be implemented using the iterative nearest neighbor algorithm:

[0055] Step 1: Perform region of interest filtering on the laser point clouds received by each multi-line lidar to obtain the laser point cloud within a preset area.

[0056] The preset area range here can be determined in the following way: based on the trailer angle of the previous cycle and the known trailer size, a preset distance range outside the trailer of the previous cycle is determined as the preset area range.

[0057] For example, the following method can be used:

[0058] like Figure 10 As shown, given the trailer angle from the previous cycle and the known trailer dimensions, the trailer's current posture can be determined. This allows us to define a preset distance range outside the trailer from the previous cycle (the shaded area in the diagram only describes the planar range; similar ranges also exist above and below the trailer). This three-dimensional range can then be used as the preset range. This is because the time interval between adjacent cycles is short (typically 0.1 seconds), resulting in minimal changes to the trailer angle. Therefore, the trailer's change between the current and previous cycles is small, and it should remain within this preset range.

[0059] Step 2: Perform noise filtering on the laser point cloud within the preset area to obtain the noise-filtered laser point cloud corresponding to each multi-line lidar, thus forming the trailer model corresponding to each multi-line lidar for the current time.

[0060] Here, noise filtering can be used to remove outlier points, thus obtaining a more accurate laser point cloud. Here, the point set consisting of all points of the current trailer model is denoted as {Pn}, where n is a positive integer. For example, {P1} represents the point set consisting of all points of the first trailer model.

[0061] Step 3: For each point in the trailer model of each current iteration, determine the point in the initial point cloud dataset that is closest to each point in a straight line as the target point.

[0062] Step 4: Move each point to its corresponding target point using the singular value decomposition algorithm to obtain the trailer model for the next iteration and generate the model matrix for the current iteration.

[0063] Here, the model matrix for the current iteration includes the rotation matrix and the translation matrix for the current iteration; the rotation matrix for the current iteration includes the trigonometric function relationship of the deflection angles of the three coordinate axes in the vehicle coordinate system for the current iteration.

[0064] After step 4, return to step 3 until the distance between each point in the current trailer model and the target point is less than the preset distance threshold, then continue to step 5.

[0065] In this embodiment of the invention, after installing the multi-line lidar, a lidar coordinate system is established. The position information of the laser point cloud of the multi-line lidar is based on this lidar coordinate system. For example, a coordinate system can be established as follows: Figure 11 The coordinate system shown is for a lidar, but it is not limited to this. In establishing the coordinate system of a lidar, other directions can be selected as the x-axis, a direction perpendicular to the x-axis on the horizontal plane as the y-axis, and a direction perpendicular to both the x-axis and y-axis as the z-axis (not shown in the figure, but generally the vertical upward direction). These will not be listed one by one here.

[0066] Thus, after each iteration, the model matrix An can be represented as: Where Rn represents the rotation matrix of the nth iteration, which is a 3x3 matrix; Tn represents the translation matrix of the current iteration, which is a 3x1 matrix. The rotation matrix Rn of the nth iteration is generally composed of three rotations, i.e., Rn = Rxn·Ryn·Rzn; Rxn is the rotation matrix along the x-axis in the vehicle coordinate system for the nth iteration, Ryn is the rotation matrix along the y-axis in the vehicle coordinate system for the nth iteration, and Rzn is the rotation matrix along the z-axis in the vehicle coordinate system for the nth iteration; for example, in one embodiment…

[0067]

[0068] Where θxn is the x-axis deflection angle in the vehicle coordinate system for the nth iteration; θyn is the y-axis deflection angle in the vehicle coordinate system for the nth iteration; and θzn is the z-axis deflection angle in the vehicle coordinate system for the nth iteration.

[0069] The translation matrix of the current iteration can be expressed as an, bn, and cn are the translation amounts in the nth iteration.

[0070] Step 5: Multiply the model matrices from each iteration to obtain the result matrix after multiplication.

[0071] Here, for example, if n iterations are performed, the model matrices from each iteration are multiplied to obtain a result matrix A = An·A(n-1)·......·A2·A1. This result matrix includes a result rotation matrix and a result translation matrix; the result rotation matrix includes the trigonometric function relationship of the deflection angles of the three coordinate axes in the vehicle coordinate system. For example, the result rotation matrix R in the result matrix A can be represented as... m 00 to m 22 The trigonometric function relationship represents the deflection angle at the corresponding position in the resulting rotation matrix R. Since the trigonometric function relationship here is quite complex, the specific trigonometric function relationship will not be listed here.

[0072] Step 6: Based on the rotation matrix of the results, determine the initial trailer angle corresponding to each multi-line lidar.

[0073] For example, the resulting rotation matrix R is represented as In this case, the following relationship exists:

[0074] θx=atan2(m 12 ,m 22 )

[0075]

[0076] θy=atan2(-m 02 ,cosθy)

[0077] θz=atan2(sinθx·m 20 -cosθx·m 10 ,cosθx·m 11 -sinθx·m 21 )

[0078] Where θx, θy, and θz are the deflection angles around the x-axis, y-axis, and z-axis in the current cycle, respectively. And θz is equivalent to the initial trailer angle.

[0079] Step 407: Filter the initial trailer angle corresponding to each multi-line lidar according to the pre-set judgment conditions.

[0080] Here, step 407 can be implemented in the following two ways, or in combination:

[0081] Method 1:

[0082] Determine whether the number of points in the laser point cloud after noise filtering for each multi-line lidar is less than a preset point count threshold.

[0083] The initial trailer angle corresponding to multi-line lidar with a number of points in the noise-filtered laser point cloud that is less than a preset point number threshold is discarded, while the initial trailer angle corresponding to multi-line lidar with a number of points in the noise-filtered laser point cloud that is greater than or equal to the preset point number threshold is retained.

[0084] Here, if the number of points in the laser point cloud after noise filtering corresponding to the multi-line lidar is less than the preset point number threshold, it means that the trailer model corresponding to the current time of the multi-line lidar is fitted by a small number of laser point clouds. If the trailer model of the current time is obtained by fitting only a few laser point clouds, the initial trailer angle obtained is very inaccurate and should be discarded.

[0085] Method 2:

[0086] When the current cycle is not the first cycle, determine whether the deviation angle value between the initial trailer angle corresponding to each multi-line lidar in the current cycle and the trailer angle of the previous cycle obtained by Kalman filtering is greater than the preset deviation angle threshold.

[0087] If the deviation angle between the initial trailer angle corresponding to the multi-line lidar in the current cycle and the trailer angle in the previous cycle obtained by Kalman filtering is greater than a preset deviation angle threshold, then the initial trailer angle corresponding to the multi-line lidar in the current cycle will be discarded.

[0088] If the deviation angle between the initial trailer angle corresponding to the multi-line lidar in the current cycle and the trailer angle in the previous cycle obtained by Kalman filtering is less than or equal to a preset deviation angle threshold, then the initial trailer angle corresponding to the multi-line lidar in the current cycle will be retained.

[0089] Here, since the time difference between two adjacent cycles (generally only 0.1 seconds apart) is short, the change in trailer angle will not be too large. Therefore, if the deviation angle between the initial trailer angle corresponding to the multi-line lidar in the current cycle and the trailer angle of the previous cycle obtained by Kalman filtering is greater than the preset deviation angle threshold, the initial trailer angle corresponding to the multi-line lidar in the current cycle is determined to be invalid data and should be discarded.

[0090] Step 408: Arrange the initial trailer angles corresponding to each of the filtered multi-line lidars according to the acquisition time in the current cycle to form angle data to be processed.

[0091] For example, taking two multi-line lidars on each side of the front of the tractor as an example (for instance, only the two multi-line lidars on the left side have measured the initial trailer angle), the measurement cycle of the multi-line lidars is 0.1s, and the measurement times of the two multi-line lidars differ by 0.05s, then as follows... Figure 12 As shown, the horizontal axis represents the time corresponding to the initial trailer angle, and the vertical axis represents the angle of the initial trailer angle. The entire vertical axis data constitutes the angle data to be processed.

[0092] Step 409: Perform Kalman filtering on the angle data to be processed to obtain the trailer angle for the current cycle.

[0093] The reason for using Kalman filtering here is that the trailer surface itself is not flat, and the multi-line lidar itself has observation errors, resulting in a certain error in the calculated initial trailer angle. This manifests as a jump of ±1° to ±2° in the angle even when the vehicle is stationary. To solve this problem, Kalman filtering can reduce the noise of the initial trailer angle arranged with the acquisition time in the angle data to be processed. It integrates the initial trailer angle and the simplified kinematic model of the angle change to obtain a smooth output result. This not only ensures that the error of the trailer angle measurement data in a stationary state is within ±0.5°, but also ensures that the measurement data can be updated in real time when the trailer angle changes rapidly, avoiding significant delays.

[0094] After step 409 above, you can return to step 404 to perform the trailer angle measurement for the next cycle.

[0095] As can be seen, a simple, fast and accurate method for measuring trailer angle can be achieved through steps 401 to 409 above.

[0096] In addition, embodiments of the present invention also provide a device for measuring the trailer angle, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned... Figure 2 or Figure 8 The corresponding method.

[0097] In addition, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described... Figure 2 or Figure 8 The corresponding method.

[0098] In addition, such as Figure 13 As shown, this embodiment of the invention also provides a vehicle 50, including the aforementioned trailer angle measuring device 601, as well as a tractor 201 and a trailer 202 (the trailer 202 involved in this invention may be equipped with a trailer box); at least one multi-line lidar 203 is respectively provided on both sides of the tractor 201 (such as on both sides of the front end of the tractor 201, i.e., on both sides of the front of the vehicle); the trailer angle measuring device 601 is communicatively connected to the multi-line lidar 203.

[0099] This invention provides a method, device, and vehicle for measuring trailer angle. It employs at least one multi-line lidar on each side of the tractor unit, which illuminates the trailer surface. The trailer angle is calculated using a point cloud matching algorithm based on the laser point clouds received by each multi-line lidar and an initial point cloud. Furthermore, this invention calculates the trailer angle using the initial point cloud data (based on the laser point clouds received by each multi-line lidar and the trailer angle itself) instead of relying on the laser point cloud data from a single lidar, significantly improving accuracy.

[0100] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0101] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0102] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0103] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0104] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for measuring the included angle of a trailer, characterized in that, Applied to a semi-trailer, the semi-trailer including a tractor and a trailer; at least one multi-line lidar is provided on each side of the tractor; The method for measuring the trailer angle includes: Under a pre-set vehicle coordinate system, the initial model of the trailer with the trailer angle as the initial value is obtained, and the initial point cloud data on the initial model of the trailer is obtained. The multi-line lidars installed on both sides of the tractor emit lasers, causing the surface of the trailer to reflect the lasers emitted by the multi-line lidars. Control each multi-line lidar to receive the corresponding laser point cloud reflected from the surface of the trailer; Based on the corresponding laser point cloud received by each multi-line lidar and the initial point cloud data, the trailer angle is calculated using a point cloud matching algorithm. The step of calculating the trailer angle using a point cloud matching algorithm based on the corresponding laser point clouds received by each multi-line lidar and the initial point cloud data includes: The initial trailer angle corresponding to each multi-line lidar is selected based on the pre-set judgment conditions. The step of filtering the initial trailer angle corresponding to each multi-line lidar according to pre-set judgment conditions includes: When the current cycle is not the first cycle, determine whether the deviation angle between the initial trailer angle corresponding to each multi-line lidar in the current cycle and the trailer angle of the previous cycle obtained by Kalman filtering is greater than a preset deviation angle threshold; and Determine whether the number of points in the noise-filtered laser point cloud corresponding to each multi-line lidar is less than a preset point number threshold, and discard the initial trailer angle corresponding to the multi-line lidar whose number of points in the noise-filtered laser point cloud is less than the preset point number threshold.

2. The method according to claim 1, characterized in that, The process of obtaining the initial trailer model with the trailer angle set to an initial value in a pre-set vehicle coordinate system, and obtaining the initial point cloud data on the initial trailer model, includes: In a pre-set vehicle coordinate system, a pre-set external multi-line lidar is used to emit lasers to both sides of the trailer when the trailer angle is 0°, so that the surfaces on both sides of the trailer reflect the lasers emitted by the external multi-line lidar respectively. The external multi-line lidar is controlled to receive laser point clouds reflected from the surfaces on both sides of the trailer. The initial point cloud data of the trailer is obtained by using the laser point cloud reflected from the surfaces on both sides of the trailer with the iterative nearest point algorithm to obtain the initial model of the trailer when the included angle is 0°.

3. The method according to claim 1, characterized in that, The step of calculating the trailer angle using a point cloud matching algorithm based on the corresponding laser point clouds received by each multi-line lidar and the initial point cloud data includes: The laser point clouds received by each multi-line lidar are preprocessed, and the initial trailer angle corresponding to each multi-line lidar is obtained by using the iterative nearest point algorithm based on the initial point cloud data and the preprocessed laser point cloud. The initial trailer angles corresponding to each of the filtered multi-line lidars are arranged according to the acquisition time in the current cycle to form angle data to be processed. The trailer angle for the current period is obtained by performing Kalman filtering on the angle data to be processed.

4. The method according to claim 3, characterized in that, The process of preprocessing the laser point clouds received by each multi-line lidar and obtaining the initial trailer angle for each multi-line lidar using an iterative nearest-point algorithm based on the initial point cloud data and the preprocessed laser point clouds includes: Step 1: Perform region of interest filtering on the laser point clouds received by each multi-line lidar to obtain the laser point cloud within a preset area. Step 2: Perform noise filtering on the laser point cloud within the preset area to obtain the noise-filtered laser point cloud corresponding to each multi-line lidar, thus forming the trailer model corresponding to each multi-line lidar for the current time. Step 3: For each point in the current trailer model, determine the point with the closest straight-line distance to each point in the initial point cloud dataset as the target point; Step 4: Move each point to its corresponding target point using the singular value decomposition algorithm to obtain the trailer model for the next iteration, and generate the model matrix for the current iteration; the model matrix for the current iteration includes the rotation matrix and the translation matrix for the current iteration; the rotation matrix for the current iteration includes the trigonometric function relationship of the deflection angles of the three coordinate axes in the vehicle coordinate system for the current iteration. After step 4, return to step 3 until the distance between each point in the current trailer model and the target point is less than a preset distance threshold, then continue to step 5; Step 5: Multiply the model matrices from each iteration to obtain the result matrix after multiplication; the result matrix includes the result rotation matrix and the result translation matrix; the result rotation matrix includes the trigonometric function relationship of the deflection angles of the three coordinate axes in the vehicle coordinate system; Step 6: Based on the rotation matrix obtained from the results, determine the initial trailer angle corresponding to each multi-line lidar.

5. The method according to claim 4, characterized in that, Also includes: Based on the trailer angle of the previous cycle and the known trailer dimensions, a preset distance range outside the trailer of the previous cycle is determined as the preset area range.

6. The method according to claim 1, characterized in that, The step of filtering the initial trailer angle corresponding to each multi-line lidar according to pre-set judgment conditions also includes: The initial trailer angle corresponding to the multi-line lidar whose number of points in the noise-filtered laser point cloud is greater than or equal to the preset point number threshold.

7. The method according to claim 1, characterized in that, The step of filtering the initial trailer angle corresponding to each multi-line lidar according to pre-set judgment conditions also includes: If the deviation angle between the initial trailer angle corresponding to the multi-line lidar in the current cycle and the trailer angle in the previous cycle obtained by Kalman filtering is greater than the preset deviation angle threshold, then the initial trailer angle corresponding to the multi-line lidar in the current cycle will be discarded. If the deviation angle between the initial trailer angle corresponding to the multi-line lidar in the current cycle and the trailer angle in the previous cycle obtained by Kalman filtering is less than or equal to a preset deviation angle threshold, then the initial trailer angle corresponding to the multi-line lidar in the current cycle will be retained.

8. A device for measuring the trailer angle, 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 computer program, it implements the method according to any one of claims 1 to 7.

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

10. A vehicle, characterized in that, The device includes the trailer angle measuring device as described in claim 8, as well as a tractor and a trailer; at least one multi-line lidar is provided on each side of the tractor; the trailer angle measuring device is communicatively connected to the multi-line lidar.

11. The vehicle according to claim 10, characterized in that, At least one multi-line lidar is installed on each of the front sides of the tractor.

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