Vehicle parameter detection method, system and storage medium

Abstract

The embodiment of the present invention discloses a vehicle parameter detection method, system and storage medium. The method includes: determining the position coordinates of the radar data in a target coordinate system based on radar data scanned by at least two laser radars on a vehicle during driving; the at least two laser radars are staggered along both sides of the road on which the vehicle is traveling; extracting wheel point clouds based on the position coordinates of the radar data in the target coordinate system; determining the current vehicle parameters of the vehicle based on the position coordinates of the wheel point clouds in the target coordinate system. The technical solution of the present invention can realize automatic and accurate vehicle parameter detection, reduce detection costs, improve detection efficiency, and provide a new idea for vehicle parameter detection.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of laser radar technology, and in particular to a vehicle parameter detection method, system and storage medium. Background Art

[0002] Motor vehicles are an indispensable means of transportation in the rapid development of social economy, and they undertake functions such as cargo transportation and passenger transfer. In order to reduce transportation costs, some motor vehicle users privately modify the size of the vehicle to increase the vehicle's single transportation volume. Privately modified vehicles seriously violate the safety standards for vehicle use. In order to ensure the safety of the vehicle, it is necessary to regularly test the vehicle parameters (such as wheelbase, wheel diameter, etc.). At present, vehicle parameter detection is mainly based on manual measurement, which is inefficient, costly, and inaccurate, and needs to be improved urgently. Summary of the invention

[0003] The embodiments of the present invention provide a vehicle parameter detection method, system and storage medium, which can realize automatic and accurate vehicle parameter detection, reduce detection costs, improve detection efficiency, and provide a new idea for vehicle parameter detection.

[0004] In a first aspect, an embodiment of the present invention provides a vehicle parameter detection method, comprising:

[0005] Determine the position coordinates of the radar data in a target coordinate system based on radar data scanned by at least two laser radars on a vehicle during driving; wherein the at least two laser radars are staggeredly arranged along both sides of a road on which the vehicle is traveling;

[0006] Extracting a wheel point cloud according to the position coordinates of the radar data in a target coordinate system;

[0007] The current vehicle parameters of the vehicle are determined according to the position coordinates of the wheel point cloud in the target coordinate system.

[0008] In a second aspect, an embodiment of the present invention further provides a vehicle parameter detection device, the device comprising:

[0009] A position coordinate determination module, used to determine the position coordinates of the radar data in a target coordinate system based on radar data scanned by at least two laser radars on a vehicle during driving; wherein the at least two laser radars are staggeredly arranged on both sides of the road on which the vehicle is traveling;

[0010] A wheel point cloud extraction module, used to extract a wheel point cloud according to the position coordinates of the radar data in a target coordinate system;

[0011] The vehicle parameter determination module is used to determine the current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system.

[0012] In a third aspect, an embodiment of the present invention further provides a vehicle parameter detection system, the system comprising at least two laser radars and a processing device; the processing device is connected to the at least two laser radars, and the at least two laser radars are staggered along both sides of the vehicle driving road; the processing device comprises:

[0013] one or more processors;

[0014] A storage device for storing one or more programs;

[0015] When the one or more programs are executed by the one or more processors, the one or more processors implement any vehicle parameter detection method described in the first aspect for each laser radar.

[0016] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any vehicle parameter detection method described in the first aspect.

[0017] The embodiment of the present invention provides a vehicle parameter detection method, system and storage medium. At least two laser radars are staggered on both sides of the road where the vehicle is traveling. The radar data is scanned for the vehicle during driving, and the position coordinates of the radar data in the target coordinate system are determined. According to the position coordinates of the radar data in the target coordinate system, the wheel point cloud scanned by the laser radar is extracted, and then the current vehicle parameters of the vehicle are determined according to the position coordinates of the wheel point cloud in the target coordinate system. The technical solution of the embodiment of the present invention does not require manual measurement. At least two laser radars can be used to automatically and accurately detect vehicle parameters, which reduces the detection cost, improves the detection efficiency, and provides a new idea for vehicle parameter detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0019] Figure 1A is a flow chart of a vehicle parameter detection method in Embodiment 1 of the present invention;

[0020] Figure 1B-1C is a simplified schematic diagram of the installation position of the laser radar according to an embodiment of the present invention;

[0021] Figure 2is a flow chart of a vehicle parameter detection method in Embodiment 2 of the present invention;

[0022] Figure 3A is a flow chart of a vehicle parameter detection method in Embodiment 3 of the present invention;

[0023] Figure 3B is a schematic diagram of the effect of the vehicle point cloud extracted in the third embodiment of the present invention;

[0024] Figure 3C is a schematic diagram of the effect of the wheel point cloud extracted in the third embodiment of the present invention;

[0025] Figure 4A is a flow chart of a vehicle parameter detection method in Embodiment 4 of the present invention;

[0026] Figure 4B is a principle block diagram of the vehicle parameter verification process in the fourth embodiment of the present invention;

[0027] Figure 5 It is a structural schematic diagram of a vehicle parameter detection device in Embodiment 5 of the present invention;

[0028] Fig. 6A is a structural schematic diagram of a vehicle parameter detection system in Embodiment 6 of the present invention;

[0029] Figure 6B It is a structural schematic diagram of a processing device of a vehicle parameter detection system in Embodiment 6 of the present invention. DETAILED DESCRIPTION

[0030] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0031] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0032] Embodiment 1

[0033] Figure 1A is a flow chart of a vehicle parameter detection method in Embodiment 1 of the present invention; Figure 1B-1CThis is a simplified schematic diagram of the laser radar installation position of an embodiment of the present invention. This embodiment is applicable to the case where at least two laser radars are used to automatically detect vehicle parameters of a moving vehicle. The method can be executed by a vehicle parameter detection device of an embodiment of the present invention, which can be implemented in software and / or hardware. Figures 1A-1C As shown, the method specifically comprises the following steps:

[0034] S101, determining position coordinates of the radar data in a target coordinate system based on radar data obtained by at least two laser radars scanning a vehicle during driving.

[0035] Among them, the at least two laser radars used in the embodiment of the present invention can be high-speed laser radars for ranging. And the at least two laser radars are staggered along the two sides of the road where the vehicle is traveling. Specifically, the at least two laser radars can be respectively installed on pillars staggered along the two sides of the road where the vehicle is traveling. It should be noted that if there is a laser radar on each side of the road in this embodiment, the horizontal line connecting the two laser radars is not perpendicular to the direction of vehicle travel. For example, Figure 1B As shown, the laser radars 10A and 10B are installed on the pillars 12 arranged staggered on both sides of the vehicle driving road 11. Figure 1C It can be seen that the laser radars 10A and 10B installed on both sides of the vehicle's driving road are horizontally asymmetric, and the distance between the two in the horizontal direction is D. The purpose of staggered arrangement of at least two laser radars along both sides of the vehicle's driving road in the embodiment of the present invention is to subsequently determine the vehicle's driving speed. Optionally, the at least two laser radars in this embodiment can be single-line laser radars or multi-line laser radars. If the laser radar is a single-line laser radar, then when the single-line laser radar is installed, its rotation axis needs to be parallel to the horizontal plane, that is, the scanning surface of the single-line laser radar is a vertical plane; if the laser radar is a multi-line laser radar, then when the multi-line laser radar is installed, its rotation axis can be parallel to the horizontal plane or perpendicular to the horizontal plane, that is, the scanning surface of the multi-line laser radar is a two-dimensional plane, and the scanning of the three-dimensional space is achieved by rotation. In this embodiment, the laser radar is mainly taken as an example of a single-line laser radar.

[0036] When the laser radar in this embodiment is a single-line laser radar, the radar data obtained by scanning can be the distance information and angle information between the space point cloud and the center of the laser radar. Specifically, the distance information is the distance between the line connecting the space point cloud and the center of the laser radar, and the angle information is the angle between the line connecting the space point cloud and the center of the laser radar and the horizontal or vertical direction. When the laser radar in this embodiment is a multi-line laser radar, the radar data obtained by scanning can be the three-dimensional coordinate value of the space point cloud relative to the center of the laser radar, that is, (x, y, z).

[0037] Optionally, in an embodiment of the present invention, when a vehicle to be detected passes through a road where a laser radar is arranged, the laser radars arranged on both sides of the road where the vehicle is traveling will emit laser beams to scan the radar data of the spatial point cloud during the vehicle's driving process. The processing device of the vehicle parameter detection system obtains radar data scanned by at least two laser radars, and then determines the three-dimensional position coordinates of the spatial point cloud corresponding to the radar data in the target coordinate system based on the radar data.

[0038] In an embodiment of the present invention, the radar data acquired by the processing device is collected by multiple laser radars, and the initial coordinate system corresponding to the radar data collected by each laser radar is the coordinate system where the laser radar is located. The target coordinate system in this embodiment can be the coordinate system where any laser radar among the multiple laser radars is located; it can also be other spatial coordinate systems, such as the geocentric coordinate system. In this step, when determining the position coordinates of the radar data in the target coordinate system according to the radar data scanned by at least two laser radars on the vehicle during driving, it can be: first determine the position coordinates of the radar data in the initial coordinate system according to the radar data scanned by at least two laser radars on the vehicle during driving; then convert the position coordinates of the radar data in the initial coordinate system to the target coordinate system to obtain the position coordinates of the radar data in the target coordinate system. Specifically, it can be first determined according to the radar data scanned by at least two laser radars on the driving vehicle, the position coordinates corresponding to each radar data in its initial coordinate system, and then based on the conversion relationship between each initial coordinate system and the target coordinate system, the position coordinates in each initial coordinate system are converted to a unified target coordinate system to obtain the position coordinates of the spatial point cloud corresponding to each radar data in the target coordinate system.

[0039] Optionally, in this embodiment, since the scanning surface of the multi-line laser radar is a two-dimensional plane, scanning and detection of the three-dimensional space can be achieved by rotation, so that as long as the vehicle enters the scanning field of view of the multi-line laser radar, its point cloud data can be obtained through a single frame scan. Of course, in order to ensure the accuracy of the judgment, the multi-frame scanning results can also be used for data processing. Therefore, if the at least two laser radars are multi-line laser radars, when determining the position coordinates of the radar data in its initial coordinate system, the position coordinates of the radar data in the initial coordinate system can be extracted from the radar data scanned by at least two laser radars on the vehicle during driving. Specifically, the three-dimensional position coordinates (x, y, z) can be extracted from the radar data scanned by the multi-line laser radar as the x coordinate value, y coordinate value and z coordinate value of the spatial point cloud corresponding to the radar data in the multi-line laser radar coordinate system. Since the scanning surface of a single-line laser radar is a vertical surface, if the at least two laser radars are single-line laser radars, when determining the position coordinates of the radar data in its initial coordinate system, only the distance information and angle information in the radar data can be used to solve the position coordinates of the radar data in two dimensions in the three-dimensional space. Therefore, this step also requires determining the driving speed of the vehicle to be detected, and then determining the position coordinates in the third dimension based on the vehicle driving speed. The specific determination method will be described in detail in the subsequent embodiments.

[0040] S102, extracting a wheel point cloud according to the position coordinates of the radar data in the target coordinate system.

[0041] Optionally, this step can analyze the position of each spatial point cloud corresponding to the radar data according to the position coordinates of the radar data in the target coordinate system, and extract the point cloud corresponding to the wheel, that is, the wheel point cloud. Specifically, when extracting the vehicle point cloud according to the position coordinates of the radar data in the target coordinate system, this step can be combined with the special spatial position relationship of the wheel point cloud to directly extract the vehicle point cloud from the spatial point cloud. For example, since the laser radar scans the radar data on both sides of the vehicle's driving direction, the special spatial position relationship of the wheel point cloud scanned by it can be that the wheel point cloud is distributed in a circle, and the lower part of the circle is in contact with the ground, and there is a certain distance between the upper part and the vehicle body. This step can be based on the special position relationship to directly extract the wheel point cloud from the spatial point cloud. However, since there may be non-vehicle noise point clouds in the radar data scanned by the laser radar, in order to improve the accuracy of the wheel point cloud extraction in this step, this step can also be to first extract the vehicle point cloud from the spatial point cloud, and then further extract the wheel point cloud from the vehicle point cloud based on the special spatial position relationship of the wheel point cloud. Optionally, the specific implementation process of how to extract the vehicle point cloud from the spatial point cloud in this step, and how to extract the wheel point cloud based on the special spatial position relationship of the wheel point cloud will be described in detail in subsequent embodiments.

[0042] S103, determining the current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system.

[0043] Among them, the current vehicle parameters at least include the current wheelbase parameter and the current wheel diameter parameter of the vehicle. Specifically, the wheelbase parameter can be the distance from the center of the front axle to the center of the rear axle of the vehicle. That is, it is the distance between the centers of two adjacent wheels on the same side of the vehicle and the two vertical lines perpendicular to the longitudinal symmetry plane of the vehicle. The wheel diameter parameter can be the wheel diameter parameter of the vehicle. In order to determine the current wheelbase parameter and the current wheel diameter parameter of the vehicle, when S102 extracts the wheel point cloud from the spatial point cloud, it is necessary to extract the wheel point cloud of at least one side of the left and right side of the vehicle.

[0044] Optionally, when determining the current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system, the current vehicle parameters of the vehicle can be detected as long as the center and diameter of each wheel on at least one side are determined. The specific execution process may be: performing circle fitting on the position coordinates of the wheel point cloud on at least one side in the target coordinate system to determine the center and diameter of the fitting circle on at least one side; determining the current wheelbase parameter and current wheel diameter parameter of the vehicle according to the center and diameter of the fitting circle on at least one side. Specifically, it may be that for the position coordinates of the wheel point cloud on at least one side extracted in S102 in the target coordinate system, a circle fitting is performed on the contours of each wheel on at least one side to obtain the fitting circles corresponding to each wheel; and then the center and diameter of each fitting circle are calculated. When the center and diameter of the fitting circle on one side are obtained, the horizontal distance between the centers of the two fitting circles on the side may be used as the current wheelbase parameter of the vehicle. The average diameter of the two fitting circles on the side is taken as the current wheel diameter parameter of the vehicle, or the diameter with the highest accuracy is selected from the two fitting circles based on the preset screening rules as the current wheel diameter parameter of the vehicle.

[0045] When the centers and diameters of the fitting circles on both sides are obtained, the candidate wheelbase parameters and candidate wheel diameter parameters on both sides can be determined according to the centers and diameters of the fitting circles on both sides; the mean of the candidate wheelbase parameters and the mean of the candidate wheel diameter parameters on both sides are taken as the current wheelbase parameters and the current wheel diameter parameters of the vehicle; or, based on the preset screening rules, the current wheelbase parameters and the current wheel diameter parameters of the vehicle are selected from the candidate wheelbase parameters and the candidate wheel diameter parameters on both sides. Among them, for each side, the horizontal distance between the centers of the two fitting circles on the side is calculated as a candidate wheelbase parameter; the diameters of the four fitting circles on both sides are taken as four candidate wheel diameter parameters; then the mean of each candidate wheelbase parameter and each candidate wheel diameter parameter is calculated as the current wheelbase parameter and the current wheel diameter parameter; or, according to the preset screening rules, the candidate wheelbase parameter with the highest accuracy is selected from the two candidate wheelbases as the current wheelbase parameter, and the candidate wheel diameter parameter with the highest accuracy is selected from the four candidate wheel diameters as the current wheelbase parameter.

[0046] It should be noted that, in the embodiment of the present invention, the number of laser radars collecting radar data is at least two, and the greater the number of laser radars, the more comprehensive the extracted wheel point cloud is, and thus the more accurate the current vehicle parameters of the vehicle are determined.

[0047] The vehicle parameter detection method provided by the embodiment of the present invention has at least two laser radars arranged in a staggered manner on both sides of the road on which the vehicle is traveling, and the radar data is scanned for the vehicle during driving, and the position coordinates of the radar data in the target coordinate system are determined. According to the position coordinates of the radar data in the target coordinate system, the wheel point cloud scanned by the laser radar is extracted, and then the current vehicle parameters of the vehicle are determined according to the position coordinates of the wheel point cloud in the target coordinate system. The technical solution of the embodiment of the present invention does not require manual measurement, and at least two laser radars can be used to automatically and accurately detect vehicle parameters, which reduces the detection cost, improves the detection efficiency, and provides a new idea for vehicle parameter detection.

[0048] Embodiment 2

[0049] Figure 2 This is a flow chart of a vehicle parameter detection method in Embodiment 2 of the present invention. This embodiment is based on the above embodiment and is further optimized. It specifically describes how to determine the position coordinates of the radar data in the target coordinate system based on the radar data of at least two laser radars scanning the vehicle during driving when the laser radar is a single-line laser radar. Specifically, Figure 2 As shown, the operation process includes the following steps:

[0050] S201, determining the vehicle's driving speed based on multiple frames of radar data scanned by at least two laser radars on the vehicle during driving and the offset distance between at least two laser radars.

[0051] Specifically, a vehicle position point that can be collected by laser radars on both sides of the vehicle's driving road can be selected as a reference point, such as the front position of the vehicle as the reference point, and at least a set of laser radar pairs scanning the reference point are obtained. A set of laser radar pairs is composed of two laser radars distributed on both sides of the vehicle's driving road, and the horizontal line connecting them is not perpendicular to the vehicle's driving direction. For example, Figure 1B and 1C The laser radar 10A and laser radar 10B in the figure are a pair of laser radars. Then, based on the distance between the two laser radars in each pair of laser radars in the horizontal plane in the direction of vehicle travel and the timestamps when the two laser radars scan the reference point, the vehicle's travel speed can be calculated. For example, assuming Figure 1B and Figure 1C The time stamp of the laser radar 10A scanning the front position of the vehicle is t1, the time stamp of the laser radar 10B scanning the front position of the vehicle is t2, and the distance between the laser radar 10A and the laser radar 10B in the horizontal plane in the direction of vehicle travel is D (that is, the offset distance between the two laser radars). At this time, the vehicle's travel speed V can be calculated by the formula D=|t1-t2|×V.

[0052] Optionally, when two laser radars have the same specifications and are started strictly at the same time, when this embodiment calculates the vehicle's driving speed, it can also be based on the distance D between the two laser radars in each group of laser radar pairs in the horizontal plane in the direction of vehicle travel, the number of scanning frames when the two laser radars scan the reference point (i.e., S1 and S2), and the scanning frequency H of the laser radar, according to the formula D=|S1-S2|×1 / H×V to calculate the vehicle's driving speed V.

[0053] It should be noted that when this step determines the vehicle speed based on at least two groups of laser radar pairs, a vehicle speed can be calculated based on each group of laser radar pairs according to the method introduced above, and then the calculated multiple vehicle speeds are integrated, such as averaging, or according to preset screening rules, the most accurate vehicle speed is screened out as the final vehicle speed.

[0054] S202, determining the position coordinates of the radar data in the initial coordinate system according to the vehicle speed, distance information and angle information in the radar data.

[0055] Specifically, this step can be to calculate the coordinate value of the radar data on the coordinate axis of the vehicle driving direction in the initial coordinate system according to the vehicle driving speed and the timestamp (or scanning frame number and scanning frequency) corresponding to the laser radar scanning the radar data for the space point cloud corresponding to each radar data; and calculate the coordinate value of the radar data on the other two coordinate axes except the vehicle driving direction in the initial coordinate system according to the geometric position relationship between the space point cloud corresponding to the radar data and the center point of the laser radar scanning the radar data. Exemplarily, assuming that the coordinate axis of the vehicle driving direction is the X axis, the vehicle driving speed is V, the distance information in a certain radar data scanned by the laser radar is d, the angle information (i.e., the angle between the line connecting the space point cloud and the center of the laser radar and the horizontal direction) is α, the timestamp when the laser radar scans the radar data is t, the scanning frame number is S, and the scanning frame rate of the laser radar is H, then the X-axis coordinate of the space point cloud corresponding to the radar data in its initial coordinate system is: X=t×V, or X=S×1 / H×V; the Y-axis coordinate is Y=d×cosα; and the Z-axis coordinate is Z=d×sinα.

[0056] S203, converting the position coordinates of the radar data in the initial coordinate system into the target coordinate system to obtain the position coordinates of the radar data in the target coordinate system.

[0057] Among them, since the radar data in this embodiment is scanned by at least two laser radars, and the coordinate system of each laser radar is a radar coordinate system constructed with its center point as the origin, the position coordinates determined by the point cloud data scanned by different laser radars in S202 are located in different radar coordinate systems. For example, the initial coordinate system where the position coordinates corresponding to the position of the vehicle head determined by the point cloud data collected by the laser radar 10A are located is a radar coordinate system constructed with the center of the laser radar 10A as the origin; the initial coordinate system where the position coordinates corresponding to the position of the vehicle head determined by the point cloud data collected by the laser radar 10B are located is a radar coordinate system constructed with the center of the laser radar 10B as the origin. Therefore, this step needs to convert the position coordinates in different coordinate systems to the same target coordinate system, so that the position coordinates of each spatial point cloud can be analyzed in the same target coordinate system later to detect vehicle parameters.

[0058] Specifically, in this step, the position coordinates of the radar data in the initial coordinate system are converted to the target coordinate system. The position coordinates of the radar data in the initial coordinate system can be uniformly converted to the geocentric coordinate system; or the position coordinates of the radar data in the initial coordinate system can be uniformly converted to the radar coordinate system of any one of the at least two laser radars (i.e., any initial coordinate system). This embodiment is not limited to this. When performing the position coordinate conversion, the position coordinates in each initial coordinate system can be converted to the target coordinate system based on the coordinate conversion relationship (such as a coordinate conversion matrix) between each initial coordinate system and the target coordinate system to be converted to, so as to obtain the position coordinates of each radar data in the target coordinate system.

[0059] S204, extracting the wheel point cloud according to the position coordinates of the radar data in the target coordinate system.

[0060] S205, determining current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system.

[0061] The vehicle parameter detection method provided by the embodiment of the present invention is that if at least two single-line laser radars are staggered on both sides of the road where the vehicle is traveling, the radar data is scanned for the vehicle during driving, and the vehicle speed is determined based on the scanned multi-frame radar data and the staggered distance of at least two laser radars. Based on the vehicle speed, the distance information and angle information in the radar data, the position coordinates of the radar data in the initial coordinate system are determined, and then converted to the target coordinate system. According to the position coordinates of the radar data in the target coordinate system, the wheel point cloud scanned by the laser radar is extracted, and then the current vehicle parameters of the vehicle are determined according to the position coordinates of the wheel point cloud in the target coordinate system. The technical solution of the embodiment of the present invention can accurately determine the position coordinates of the radar data, provide a guarantee for the subsequent accurate extraction of the wheel point cloud for vehicle parameter detection, and provide a new idea for vehicle parameter detection.

[0062] Embodiment 3

[0063] Figure 3A is a flow chart of a vehicle parameter detection method in Embodiment 3 of the present invention, Figure 3B is a schematic diagram of the effect of the vehicle point cloud extracted in the third embodiment of the present invention; Figure 3C This is a schematic diagram of the effect of the wheel point cloud extracted in the third embodiment of the present invention; this embodiment is based on the above embodiment and is further optimized, and specifically provides a specific introduction on how to extract the wheel point cloud according to the position coordinates of the radar data in the target coordinate system. Specifically, Figures 3A-3C As shown, the operation process includes the following steps:

[0064] S301, determining the position coordinates of the radar data in a target coordinate system based on radar data obtained by at least two laser radars scanning a vehicle during driving.

[0065] Wherein, the at least two laser radars are arranged in a staggered manner along both sides of the road on which the vehicle is traveling.

[0066] S302, extracting a vehicle point cloud according to the position coordinates of the radar data in the target coordinate system.

[0067] Optionally, since the ground point cloud contained in the spatial point cloud corresponding to the radar data will seriously interfere with the accuracy of the vehicle point cloud extraction, this step may first remove the ground point cloud in the spatial point cloud before extracting the vehicle point cloud, and then extract the vehicle point cloud from the remaining spatial point cloud.

[0068] Optionally, when this step removes the ground point cloud from the spatial point cloud, it may be by using a random sampling consensus algorithm (RANSAC algorithm) based on the position coordinates of all spatial point clouds in the target coordinate system to remove the ground point cloud from the spatial point cloud; it may also be by using a ground fitting algorithm based on the position coordinates of all spatial point clouds in the target coordinate system to remove the ground point cloud from the spatial point cloud, etc. This embodiment is not limited to this. When this step extracts the vehicle point cloud from the remaining spatial point cloud, it may be by extracting the vehicle point cloud from the remaining spatial point cloud after removing the ground point cloud based on a clustering algorithm; it may also be by inputting the remaining spatial point cloud into a pre-trained vehicle point cloud extraction model to obtain the vehicle point cloud output by the vehicle point cloud extraction model, etc. This embodiment is not limited to this. Exemplarily, Figure 3B A schematic diagram showing the effect of the vehicle point cloud extracted in this step.

[0069] S303, extracting the wheel point cloud according to the position coordinates of the vehicle point cloud in the target coordinate system.

[0070] Optionally, this step may be to extract the wheel point cloud contained in the vehicle point cloud by combining the position coordinates of the vehicle point cloud in the target coordinate system with the special spatial position relationship of the wheel point cloud. The specific execution process may be: projecting the position coordinates of the vehicle point cloud in the target coordinate system into the vertical plane where the vehicle is traveling; determining the vehicle point cloud scanned by each laser radar in each frame based on the projection data of the vehicle point cloud; for each frame of the vehicle point cloud, if the vertical distance between two adjacent data points is within a preset distance range, the data points in the vehicle point cloud of that frame that are below the distance are taken as wheel point clouds.

[0071] Specifically, assuming that the vehicle's driving direction is the X-axis direction, this step is to project the position coordinates of the vehicle point cloud in the target coordinate system into the X0Z plane where the X-axis is located, sort the projection data of the vehicle point cloud (i.e., the vehicle point cloud corresponding to the x-coordinate value and the z-coordinate value) according to the coordinate value in the X-axis direction, determine the X-axis position of each laser radar in each frame scan according to the scanning frequency of each laser radar, and divide each vehicle point cloud within a preset distance range from the X-axis position of each frame scan into the vehicle point cloud obtained by the frame scan. Since there is a certain gap between the wheels of the vehicle and the body in the vertical direction, based on this special spatial position relationship, for each frame of the vehicle point cloud, it is determined whether the vertical distance between any two adjacent data points thereon is within a preset range (such as greater than the first threshold and less than the second threshold). If so, all data points in the frame point cloud data that are located below the distance are used as wheel point clouds. Among them, the preset range can be the gap distance range between the wheel edge of the vehicle and the lower edge of the body. And in this embodiment, the angular resolution of the laser radar is less than the preset distance range. Exemplarily, Figure 3C The schematic diagram shows the effect of the wheel point cloud extracted in this step. Figure 3C Each box in represents an extracted wheel point cloud.

[0072] S304, determining the current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system.

[0073] The vehicle parameter detection method provided by the embodiment of the present invention determines the position coordinates of the radar data in the target coordinate system based on the radar data of the traveling vehicle scanned by the laser radars arranged staggered along both sides of the vehicle's traveling road, first removes the noise point cloud from the spatial point cloud corresponding to the radar data, and then extracts the vehicle point cloud, and then extracts the wheel point cloud from the vehicle point cloud based on the spatial position relationship between the wheel point cloud and the body point cloud, and then determines the current vehicle parameters of the vehicle based on the position coordinates of the wheel point cloud in the target coordinate system. The technical solution of the embodiment of the present invention greatly improves the accuracy of wheel point cloud extraction, and provides a guarantee for the subsequent accurate and efficient determination of the current vehicle parameters.

[0074] Embodiment 4

[0075] Figure 4A is a flow chart of a vehicle parameter detection method in Embodiment 4 of the present invention; Figure 4B This is a principle block diagram of the vehicle parameter verification process in the fourth embodiment of the present invention. This embodiment is based on the above embodiment and is further optimized. Specifically, a preferred example of implementing the vehicle parameter verification process based on vehicle parameter detection is given. Specifically, Figure 4A-4B As shown, the method of this embodiment specifically includes the following steps:

[0076] S401, determining position coordinates of the radar data in a target coordinate system based on radar data obtained by at least two laser radars scanning a vehicle during driving.

[0077] Among them, at least two laser radars are staggeredly arranged along both sides of the vehicle's driving road.

[0078] For example, Figure 4B During the driving process of the vehicle to be detected, the laser radar of the vehicle parameter detection part scans the radar data of the current space and sends it to the processing device. The position coordinate determination module, the wheel point cloud extraction module and the vehicle parameter determination module in the processing device determine the current vehicle parameters of the vehicle to be detected by executing S401-S404 operations.

[0079] S402, extracting a vehicle point cloud according to the position coordinates of the radar data in the target coordinate system.

[0080] S403, extracting the wheel point cloud according to the position coordinates of the vehicle point cloud in the target coordinate system.

[0081] S404, determining current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system.

[0082] S405 , determining a two-dimensional plane view of the vehicle according to the position coordinates of the vehicle point cloud in the target coordinate system.

[0083] The two-dimensional plane view may be an orthographic projection view of the vehicle on the two-dimensional plane, for example, may include at least one of a front view and a top view of the vehicle.

[0084] Optionally, this step can determine the two-dimensional plane view of the vehicle based on the position coordinates of the vehicle point cloud in the target coordinate system by: projecting the position coordinates of the vehicle point cloud extracted in S402 in the target coordinate system into a horizontal plane to obtain a top view of the vehicle; projecting the position coordinates of the vehicle point cloud extracted in S402 in the target coordinate system into a vertical plane in the direction of vehicle travel to obtain a front view of the vehicle.

[0085] Optionally, in the embodiment of the present invention, the size of the current vehicle (ie, the length, width, and height of the vehicle) may be determined based on the top view and the front view of the vehicle, and the size of the current vehicle may also be used as the current vehicle parameter.

[0086] S406, displaying a two-dimensional plane view of the vehicle and current vehicle parameters of the vehicle.

[0087] Optional, to improve the visualization of vehicle parameter detection, Figure 4BAfter determining the current vehicle parameters, the vehicle parameter detection part in the processing device can perform S405 and S406 to determine the two-dimensional plane view of the vehicle, and display the two-dimensional plane view and the current vehicle parameters of the vehicle; in order to better manage the current vehicle parameters, such as Figure 4B As shown, this embodiment can also send the displayed two-dimensional plan view of the vehicle and the current vehicle parameters of the vehicle to the background management module, and the background management module stores the original radar data collected by the laser radar, the two-dimensional plan view of the vehicle and the current vehicle parameters for use in the subsequent S407 parameter verification of the vehicle.

[0088] S407, performing parameter verification on the vehicle based on preset evaluation criteria and current vehicle parameters of the vehicle.

[0089] The preset evaluation standard may be a standard for evaluating whether a vehicle meets the requirements for safe driving of a vehicle. For example, it may be used to determine whether a vehicle violates the requirements for safe driving of a vehicle due to changes in vehicle parameters. Optionally, the preset evaluation standard may be the factory standard vehicle parameters of the corresponding vehicle model of the vehicle to be tested; or it may be the historical vehicle parameters of the vehicle to be tested that have been detected in the past.

[0090] This optional step is based on the preset evaluation criteria and the current vehicle parameters of the vehicle. The process of parameter verification of the vehicle can be performed by Figure 4B The vehicle parameter verification part in the process is executed. Specifically, the data verification module in the processing device may obtain the preset evaluation standards and the current vehicle parameters of the vehicle from the background management module through the data interface, and compare the current vehicle parameters with the vehicle parameters recorded in the preset evaluation standards (i.e., the factory standard vehicle parameters and / or the historical vehicle parameters) to determine whether the current vehicle parameters of the vehicle are consistent with the preset evaluation standards. If they are consistent, the verification passes, otherwise, the verification fails. Then, a verification report is generated based on the verification results. For example, the inspection report may display a two-dimensional plan view of the vehicle, the current vehicle parameters of the vehicle, the preliminary evaluation standards, and whether the verification passes.

[0091] Optionally, this step is based on the preset evaluation criteria and the current vehicle parameters of the vehicle. The process of checking the parameters of the vehicle can be the process of annual inspection of motor vehicles by the vehicle management office, that is, Figure 4B The vehicle verification part is the part controlled by vehicle management.

[0092] It should be noted that the purpose of the above-mentioned S405-S406 operations is to facilitate the visual display of the verification results. This process can be omitted during actual vehicle parameter detection. For example, after executing S404 to determine the current vehicle parameters of the vehicle, the original radar data collected by the lidar and the detected current vehicle parameters are stored in the background management module. When S407 is subsequently executed, the current vehicle parameters of the vehicle are directly obtained from the background management module, and based on the preset evaluation criteria and the current vehicle parameters of the vehicle, the vehicle can be parameter checked.

[0093] The vehicle parameter detection method provided by the embodiment of the present invention determines the position coordinates of the radar data in the target coordinate system based on the radar data of the traveling vehicle scanned by the laser radars arranged staggered along both sides of the vehicle's driving road, extracts the wheel point cloud scanned by the laser radar based on each position coordinate, and then determines the current vehicle parameters of the wheel based on the position coordinates of the wheel point cloud in the target coordinate system; determines the two-dimensional plane view of the vehicle based on the vehicle point cloud, and visually displays the two-dimensional plane view of the vehicle and the current vehicle parameters, so that users can view the detection results more intuitively. Based on the preset evaluation criteria and the current vehicle parameters of the vehicle, the vehicle parameters are checked. After the embodiment of the present invention automatically detects the current vehicle parameters, the vehicle parameters are automatically checked based on the detected vehicle parameters and the preset evaluation criteria. The entire process does not require manual intervention, is efficient, low-cost, and highly accurate, and ensures the fairness and objectivity of the vehicle parameter verification process, avoiding the occurrence of artificial data falsification.

[0094] Embodiment 5

[0095] Figure 5 This is a schematic diagram of the structure of a vehicle parameter detection device provided in Embodiment 5 of the present invention. The device can execute the vehicle parameter detection method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. Figure 5 As shown, the device specifically includes:

[0096] The position coordinate determination module 501 is used to determine the position coordinates of the radar data in the target coordinate system according to the radar data scanned by at least two laser radars on the vehicle during driving; wherein the at least two laser radars are staggeredly arranged on both sides of the vehicle driving road;

[0097] A wheel point cloud extraction module 502 is used to extract a wheel point cloud according to the position coordinates of the radar data in the target coordinate system;

[0098] The vehicle parameter determination module 503 is used to determine the current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system.

[0099] The vehicle parameter detection device provided by the embodiment of the present invention has at least two laser radars arranged in a staggered manner on both sides of the road where the vehicle is traveling, which scans the radar data of the vehicle during driving, and determines the position coordinates of the radar data in the target coordinate system. According to the position coordinates of the radar data in the target coordinate system, the wheel point cloud scanned by the laser radar is extracted, and then the current vehicle parameters of the vehicle are determined according to the position coordinates of the wheel point cloud in the target coordinate system. The technical solution of the embodiment of the present invention does not require manual measurement, and can automatically and accurately perform vehicle parameter detection by using at least two laser radars, which reduces the detection cost, improves the detection efficiency, and provides a new idea for vehicle parameter detection.

[0100] Furthermore, the position coordinate determination module 501 includes:

[0101] A position coordinate determination unit, used to determine the position coordinates of the radar data in an initial coordinate system based on radar data scanned by at least two laser radars on a vehicle during driving; wherein the initial coordinate system of each radar data is the coordinate system of the laser radar that collects each radar data;

[0102] The position coordinate conversion unit is used to convert the position coordinates of the radar data in the initial coordinate system to the target coordinate system to obtain the position coordinates of the radar data in the target coordinate system.

[0103] Furthermore, the above-mentioned position coordinate determination unit is specifically used for:

[0104] If the at least two laser radars are multi-line laser radars, extracting the position coordinates of the radar data in the initial coordinate system from the radar data scanned by the at least two laser radars on the vehicle during driving;

[0105] If the at least two laser radars are single-line laser radars, the vehicle speed is determined based on multi-frame radar data scanned by at least two laser radars on the vehicle during driving and the offset distance of at least two laser radars; the position coordinates of the radar data in the initial coordinate system are determined based on the vehicle speed and the distance information and angle information in the radar data.

[0106] Furthermore, the wheel point cloud extraction module 502 includes:

[0107] A vehicle point cloud extraction unit, used to extract a vehicle point cloud according to the position coordinates of the radar data in a target coordinate system;

[0108] The wheel point cloud extraction unit is used to extract the wheel point cloud according to the position coordinates of the vehicle point cloud in the target coordinate system.

[0109] Furthermore, the wheel point cloud extraction unit is specifically used for:

[0110] Projecting the position coordinates of the vehicle point cloud in the target coordinate system into the vertical plane where the vehicle travels;

[0111] Determine the vehicle point cloud scanned by each laser radar in each frame according to the projection data of the vehicle point cloud;

[0112] For each frame of the vehicle point cloud, if the distance between two adjacent data points in the vertical direction is within a preset distance range, the data points in the frame of the vehicle point cloud that are below the distance are used as wheel point clouds.

[0113] Furthermore, the vehicle parameter determination module 503 includes:

[0114] A circle fitting unit, used to perform circle fitting on the position coordinates of the wheel point cloud on at least one side in the target coordinate system, and determine the center and diameter of the fitting circle on at least one side;

[0115] The vehicle parameter determination unit is used to determine the current wheelbase parameter and the current wheel diameter parameter of the vehicle according to the center and the diameter of the fitting circle on at least one side.

[0116] Furthermore, the vehicle parameter determination unit is specifically used to:

[0117] Determine candidate wheelbase parameters and candidate wheel diameter parameters on both sides according to the center and diameter of the fitting circles on both sides;

[0118] The mean of the candidate wheelbase parameters and the mean of the candidate wheel diameter parameters on both sides are taken as the current wheelbase parameters and the current wheel diameter parameters of the vehicle; or, based on preset screening rules, the current wheelbase parameters and the current wheel diameter parameters of the vehicle are selected from the candidate wheelbase parameters and the candidate wheel diameter parameters on both sides.

[0119] Furthermore, the above device also includes:

[0120] A view parameter display module, used to: determine the two-dimensional plane view of the vehicle according to the position coordinates of the vehicle point cloud in the target coordinate system, and display the two-dimensional plane view of the vehicle and the current vehicle parameters of the vehicle; and / or,

[0121] The vehicle verification module is used to perform parameter verification on the vehicle based on preset evaluation criteria and current vehicle parameters of the vehicle.

[0122] Embodiment 6

[0123] Fig. 6A A structural diagram of a vehicle parameter detection system provided in Embodiment 6 of the present invention is shown in FIG. Figure 6BA schematic diagram of the structure of a processing device of a vehicle parameter detection system provided in Embodiment 5 of the present invention. Fig. 6A The vehicle parameter detection system 6 shown includes at least two laser radars 61 and a processing device 60. The at least two laser radars 61 are staggered along both sides of the vehicle driving road; and the processing device 60 is connected to each laser radar 61. The installation positions of the at least two laser radars 61 have been described in detail in the above embodiment 1. Figure 6B A block diagram of an exemplary processing device 60 suitable for use in implementing embodiments of the present invention is shown. Figure 6B The processing device 60 shown is only an example and should not limit the functionality and scope of use of the embodiments of the present invention. Figure 6B As shown, the processing device 60 is in the form of a general-purpose computing device. The components of the processing device 60 may include, but are not limited to: one or more processors or processing units 601, a system memory 602, and a bus 603 connecting different system components (including the system memory 602 and the processing unit 601).

[0124] Bus 603 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus structures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0125] The processing device 60 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the processing device 60, including volatile and non-volatile media, removable and non-removable media.

[0126] System memory 602 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 604 and / or cache memory 605. Processing device 60 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 606 may be used to read and write non-removable, non-volatile magnetic media ( Figure 6B not shown, usually called a "hard drive"). Although Figure 6BNot shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 603 via one or more data medium interfaces. The system memory 602 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the embodiments of the present invention.

[0127] A program / utility 608 having a set (at least one) of program modules 607 may be stored, for example, in system memory 602, such program modules 607 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 607 generally perform the functions and / or methods of the embodiments described herein.

[0128] The processing device 60 may also communicate with one or more external devices 609 (e.g., a keyboard, a pointing device, a display 610, etc.), one or more devices that enable a user to interact with the device, and / or any device that enables the processing device 60 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed through an input / output (I / O) interface 611. Furthermore, the processing device 60 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 612. Figure 6B As shown, the network adapter 612 communicates with other modules of the processing device 60 via the bus 603. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the processing device 60, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0129] The processing unit 601 executes various functional applications and data processing by running the programs stored in the system memory 602, such as implementing the vehicle parameter detection method provided by any embodiment of the present invention for each laser radar.

[0130] Embodiment 7

[0131] Embodiment 7 of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the vehicle parameter detection method described in the above embodiment can be implemented.

[0132] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0133] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0134] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0135] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0136] The serial numbers of the above embodiments are only for description and do not represent the advantages or disadvantages of the embodiments.

[0137] It should be understood by those skilled in the art that each module or operation of the above-mentioned embodiment of the present invention can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or operations therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0138] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0139] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A vehicle parameter detection method, characterized in that: include: Determine the position coordinates of the radar data in a target coordinate system based on radar data scanned by at least two laser radars on a vehicle during driving; wherein the at least two laser radars are staggeredly arranged along both sides of a road on which the vehicle is traveling; Extracting a wheel point cloud according to the position coordinates of the radar data in a target coordinate system; Determining current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system; Determining the position coordinates of the radar data in a target coordinate system according to radar data scanned by at least two laser radars on a vehicle during driving, including: Determine the position coordinates of the radar data in an initial coordinate system based on radar data scanned by at least two laser radars on the vehicle during driving; wherein the initial coordinate system of each radar data is the coordinate system where the laser radar that collects each radar data is located; Converting the position coordinates of the radar data in the initial coordinate system to the target coordinate system to obtain the position coordinates of the radar data in the target coordinate system; Determining the position coordinates of the radar data in an initial coordinate system according to radar data scanned by at least two laser radars on a vehicle during driving includes: If the at least two laser radars are multi-line laser radars, extracting the position coordinates of the radar data in the initial coordinate system from the radar data scanned by the at least two laser radars on the vehicle during driving; If the at least two laser radars are single-line laser radars, the vehicle speed is determined based on multi-frame radar data scanned by at least two laser radars on the vehicle during driving and the offset distance of at least two laser radars; the position coordinates of the radar data in the initial coordinate system are determined based on the vehicle speed and the distance information and angle information in the radar data.

2. The method according to claim 1, characterized in that: Extracting a wheel point cloud according to the position coordinates of the radar data in the target coordinate system includes: Extracting a vehicle point cloud according to the position coordinates of the radar data in a target coordinate system; The wheel point cloud is extracted according to the position coordinates of the vehicle point cloud in the target coordinate system.

3. The method according to claim 2, characterized in that Extracting wheel point clouds according to the position coordinates of the vehicle point clouds in the target coordinate system includes: Projecting the position coordinates of the vehicle point cloud in the target coordinate system into the vertical plane where the vehicle travels; Determine the vehicle point cloud scanned by each laser radar in each frame according to the projection data of the vehicle point cloud; For each frame of the vehicle point cloud, if the distance between two adjacent data points in the vertical direction is within a preset distance range, the data points in the frame of the vehicle point cloud that are below the distance are used as wheel point clouds.

4. The method according to claim 1, characterized in that: Determining the current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system includes: Performing circle fitting on the position coordinates of the wheel point cloud on at least one side in the target coordinate system, and determining the center and diameter of the fitting circle on at least one side; According to the center and diameter of the fitting circle on at least one side, a current wheelbase parameter and a current wheel diameter parameter of the vehicle are determined.

5. The method according to claim 4, characterized in that According to the center and diameter of the fitting circles on both sides, the current wheelbase parameter and the current wheel diameter parameter of the vehicle are determined, including: Determine candidate wheelbase parameters and candidate wheel diameter parameters on both sides according to the center and diameter of the fitting circles on both sides; The mean of the candidate wheelbase parameters and the mean of the candidate wheel diameter parameters on both sides are taken as the current wheelbase parameters and the current wheel diameter parameters of the vehicle; or, based on preset screening rules, the current wheelbase parameters and the current wheel diameter parameters of the vehicle are selected from the candidate wheelbase parameters and the candidate wheel diameter parameters on both sides.

6. The method according to claim 1, characterized in that After determining the current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system, the method further includes: Determine a two-dimensional plane view of the vehicle according to the position coordinates of the vehicle point cloud in the target coordinate system, and display the two-dimensional plane view of the vehicle and current vehicle parameters of the vehicle; and / or Based on preset evaluation criteria and current vehicle parameters of the vehicle, parameter verification is performed on the vehicle.

7. A vehicle parameter detection system, characterized in that: The invention comprises at least two laser radars and a processing device; the processing device is connected to the at least two laser radars, and the at least two laser radars are staggered along both sides of the road where the vehicle is traveling; the processing device comprises: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle parameter detection method as described in any one of claims 1-6 for each laser radar.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the vehicle parameter detection method as described in any one of claims 1-6 is implemented.

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