Vehicle parameter measurement method and apparatus, terminal device, and medium

Abstract

A vehicle parameter measurement method and apparatus, a terminal device, and a medium. The method comprises the following steps: acquiring point cloud data corresponding to wheels of a vehicle (S101); on the basis of the point cloud data corresponding to the wheels, determining target point cloud planes corresponding to the fronts of the wheels, and determining circle center coordinates corresponding to the wheels (S102); calculating target plane normal vectors of the target point cloud planes respectively corresponding to the wheels (S103); and on the basis of the target plane normal vectors and the circle center coordinates, calculating four-wheel positioning parameters of the vehicle (S104). In the method, the plane normal vectors of the point cloud planes and the circle center coordinates of the wheels can be accurately determined by means of the acquired point cloud data of the wheels, and then the four-wheel positioning parameters of the vehicle can be conveniently and accurately measured and calculated, without contact measurement, so that the measurement accuracy of the four-wheel positioning parameters of the vehicle is improved, and the measurement efficiency of the four-wheel positioning parameters of the vehicle is improved.

Description

Vehicle parameter detection method, device, terminal equipment and medium

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on December 6, 2023, with application number 202311665475.8 and invention name “A vehicle parameter detection method, device, terminal equipment and medium”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application belongs to the field of automotive technology, and in particular relates to a vehicle parameter detection method, apparatus, terminal equipment, and medium. Background Art

[0003] Currently, four-wheel alignment parameters are a set of relative positional relationships between the vehicle's wheels and axles, including camber, toe, castor, and kingpin inclination. Proper selection and maintenance of these parameters are crucial for improving driving comfort, reducing fuel consumption, extending tire life, and enhancing driving safety.

[0004] However, existing technologies typically use contact measurement to determine vehicle wheel alignment parameters. This not only results in slow measurement speeds, but also in the contact force of the probe in the measuring tool, which can cause local deformation between the probe tip and the tire being measured, affecting the actual reading. Consequently, existing technologies suffer from low measurement accuracy and efficiency. Technical issues

[0005] The embodiments of the present application provide a vehicle parameter detection method, apparatus, terminal device, and medium, which improve the measurement accuracy and efficiency of the four-wheel alignment parameters of a vehicle. Technical Solutions

[0006] In a first aspect, an embodiment of the present application provides a vehicle parameter detection method, comprising:

[0007] Obtain the point cloud data corresponding to each wheel of the vehicle;

[0008] Determining the target point cloud plane corresponding to the front of each wheel and the center coordinates of each wheel according to the point cloud data corresponding to each wheel;

[0009] Calculating a target plane normal vector of a target point cloud plane corresponding to each wheel;

[0010] The four-wheel alignment parameters of the vehicle are calculated based on the normal vectors of the target planes and the coordinates of the center of the circles.

[0011] Optionally, the point cloud data includes tire line laser point cloud data corresponding to a plurality of tire line lasers, and determining the target point cloud plane corresponding to the front of each wheel based on the point cloud data corresponding to each wheel includes:

[0012] For each wheel, least squares fitting is performed based on tire line laser point cloud data corresponding to multiple tire line lasers of the wheel to obtain a first point cloud plane corresponding to the front of each wheel;

[0013] For each wheel, traverse and calculate the distance between each point on the plurality of tire line lasers and the first point cloud plane;

[0014] For each wheel, a target point cloud plane corresponding to the wheel is determined based on the distance between each point on the plurality of tire line lasers and the first point cloud plane.

[0015] Optionally, determining the target point cloud plane corresponding to the wheel based on the distance between each point on the plurality of tire line lasers and the first point cloud plane includes:

[0016] For each of the plurality of tire line lasers, determining a point having a maximum forward distance from the first point cloud plane among all points of the tire line laser as a target point of the tire line laser;

[0017] Performing least squares fitting based on the target points of the plurality of tire line lasers to obtain a second point cloud plane;

[0018] If the angle between the second point cloud plane and the first point cloud plane is greater than or equal to a set threshold, then continue to determine, for each of the multiple tire line lasers, the point position of the tire line laser with the largest forward distance to the second point cloud plane as the new target point position of the tire line laser, and perform least squares fitting based on the multiple new target points of the tire line lasers to generate a new second point cloud plane, until the angle between the generated new second point cloud plane and the previous second point cloud plane before the new second point cloud plane is less than the set threshold, and the generated new second point cloud plane is determined as the target point cloud plane corresponding to the wheel.

[0019] Optionally, determining the center coordinates corresponding to each wheel according to the point cloud data corresponding to each wheel includes:

[0020] For each wheel, performing circle fitting on the new target point position corresponding to the wheel and generating the new second point cloud plane, to obtain a fitting circle corresponding to the wheel;

[0021] For each wheel, the center coordinates of the fitting circle corresponding to the wheel are determined, and the center coordinates of the fitting circle are determined as the center coordinates of the wheel.

[0022] Optionally, the calculating of the four-wheel alignment parameters of the vehicle according to each of the target plane normal vectors and each of the circle center coordinates includes:

[0023] Performing least square fitting based on the coordinates of the center of each circle to obtain the body plane of the vehicle;

[0024] Adjusting each target plane normal vector according to the vehicle body plane to obtain each adjusted target plane normal vector;

[0025] The four-wheel alignment parameters of the vehicle are calculated based on the adjusted target plane normal vectors.

[0026] Optionally, adjusting each target plane normal vector according to the vehicle body plane to obtain each adjusted target plane normal vector includes:

[0027] Calculating a rotation matrix between the vehicle body plane and the horizontal ground;

[0028] Each of the target plane normal vectors is adjusted according to the rotation matrix to obtain each adjusted target plane normal vector.

[0029] Optionally, the four-wheel alignment parameters of each vehicle include a wheel camber angle and a wheel toe angle; and the four-wheel alignment parameters of the vehicle are calculated based on each adjusted target plane normal vector, including:

[0030] Calculating each of the wheel camber angles according to the vertical coordinate and the horizontal coordinate of each of the adjusted target plane normal vectors;

[0031] The toe angles of the wheels are calculated based on the adjusted ordinates and abscissas of the target plane normal vectors.

[0032] In a second aspect, an embodiment of the present application provides a vehicle parameter detection device, comprising:

[0033] An acquisition unit, used to acquire point cloud data corresponding to each wheel of the vehicle;

[0034] a first plane determining unit, configured to determine, based on the point cloud data corresponding to each wheel, a target point cloud plane corresponding to the front face of each wheel, and determine the coordinates of the center of a circle corresponding to each wheel;

[0035] A first calculation unit is used to calculate a target plane normal vector of a target point cloud plane corresponding to each wheel;

[0036] The second calculation unit is used to calculate the four-wheel alignment parameters of the vehicle according to each of the target plane normal vectors and each circle center coordinate.

[0037] In a third aspect, an embodiment of the present application provides a terminal device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the vehicle parameter detection method as described in any one of the first aspects above is implemented.

[0038] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the vehicle parameter detection method as described in any one of the above-mentioned first aspects is implemented.

[0039] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed on a terminal device, enables the terminal device to execute the vehicle parameter detection method described in any one of the above-mentioned first aspects. Beneficial effects

[0040] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0041] The embodiment of the present application provides a vehicle parameter detection method, which obtains point cloud data corresponding to each wheel of the vehicle; determines the target point cloud plane corresponding to the front of each wheel and the center coordinates of each wheel based on the point cloud data corresponding to each wheel; calculates the target plane normal vector of the target point cloud plane corresponding to each wheel; and calculates the four-wheel alignment parameters of the vehicle based on each target plane normal vector and each center coordinate. Compared with the prior art that requires contact measurement, and the contact measuring instrument and the measured tire will directly produce local deformation that affects the accuracy of the measurement value, the present application can accurately determine the plane normal vector and center coordinates of the point cloud plane of the wheel through the obtained point cloud data of the wheel, thereby facilitating the accurate detection and calculation of the four-wheel alignment parameters of the vehicle without the need for contact measurement, which not only improves the measurement accuracy of the four-wheel alignment parameters of the vehicle, but also improves the measurement efficiency of the four-wheel alignment parameters of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0043] FIG1 is a flow chart of a vehicle parameter detection method according to an embodiment of the present application;

[0044] FIG2 is a flowchart of a vehicle parameter detection method according to another embodiment of the present application;

[0045] FIG3 is a schematic diagram of a first point cloud plane provided by an embodiment of the present application;

[0046] FIG4 is a schematic diagram of forward distance provided by an embodiment of the present application;

[0047] FIG5 is a flow chart of a vehicle parameter detection method according to another embodiment of the present application;

[0048] FIG6 is a schematic diagram of a fitting circle provided in an embodiment of the present application;

[0049] FIG7 is a flowchart of a vehicle parameter detection method according to another embodiment of the present application;

[0050] FIG8 is a schematic diagram of a target plane normal vector provided by an embodiment of the present application;

[0051] FIG9 is a schematic structural diagram of a vehicle parameter detection device provided in one embodiment of the present application;

[0052] FIG10 is a schematic structural diagram of a terminal device provided in an embodiment of the present application. Modes for Carrying Out the Invention

[0053] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0054] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0055] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0056] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0057] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0058] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0059] Please refer to Figure 1, which is a flowchart illustrating an implementation of a vehicle parameter detection method provided in one embodiment of the present application. In this embodiment, the vehicle parameter detection method is performed by a terminal device. The terminal device includes, but is not limited to, electronic devices such as laptops, desktop computers, and computers.

[0060] As shown in FIG1 , a vehicle parameter detection method provided in an embodiment of the present application may include S101 to S104, which are described in detail as follows:

[0061] In S101 , point cloud data corresponding to each wheel of the vehicle is obtained.

[0062] In actual application, in order to obtain accurate four-wheel alignment parameters of each wheel of the vehicle, the user can send a request to determine the four-wheel alignment parameters of the vehicle to the terminal device. The four-wheel alignment parameters of the vehicle include but are not limited to the wheel toe angle and the wheel camber angle.

[0063] It should be noted that the wheel toe angle refers to the angle between the horizontal diameter of the wheel and the longitudinal vertical plane of the vehicle. The vertical plane is the vertical plane perpendicular to the other plane in two mutually perpendicular planes.

[0064] Camber refers to the outward tilt of the wheel's end surface after installation, specifically the angle between the wheel's plane and the longitudinal vertical plane. A figure-eight (eight) shape is considered negative camber, while a figure-V shape is considered positive camber.

[0065] In an embodiment of the present application, the terminal device detecting the request to determine the wheel alignment parameters of the vehicle may be: detecting a preset operation for the terminal device. The preset operation can be set according to actual needs and is not limited here. For example, the preset operation may be clicking a preset control on the terminal device. Based on this, when the terminal device detects that its preset control has been clicked, it indicates that the preset operation for the terminal device has been detected, that is, the request to determine the wheel alignment parameters of the vehicle has been detected.

[0066] After detecting the vehicle's four-wheel alignment parameter determination request, the terminal device can obtain the point cloud data corresponding to each wheel of the vehicle.

[0067] In one implementation of the embodiment of the present application, the terminal device can obtain point cloud data corresponding to each wheel in real time through a laser radar wirelessly connected to it.

[0068] In S102, based on the point cloud data corresponding to each wheel, the target point cloud plane corresponding to the front of each wheel is determined, and the center coordinates of the circle corresponding to each wheel are determined.

[0069] In this embodiment of the present application, for any wheel, the terminal device can perform a least squares fit on the acquired point cloud data corresponding to the wheel and directly determine the point cloud plane obtained by the fit, which represents the front face of the wheel, as the target point cloud plane. Simultaneously, the terminal device can also determine the coordinates of the center of the circle corresponding to the wheel based on the point cloud data corresponding to the wheel.

[0070] Based on this, the terminal device can obtain the target point cloud plane corresponding to each wheel and the center coordinates of each wheel.

[0071] It should be noted that the front face of the wheel specifically refers to the circular plane of the wheel edge. The center coordinates corresponding to the wheel specifically refer to the three-dimensional coordinates of the center of the wheel.

[0072] In one embodiment of the present application, the point cloud data of each wheel includes tire line laser point cloud data corresponding to multiple tire line lasers. Therefore, in order to improve the accuracy of determining the target point cloud plane and thereby improve the accuracy of subsequently determining the four-wheel alignment parameters of the vehicle, the terminal device can specifically obtain the target point cloud plane through steps S201 to S203 as shown in FIG. 2 , as detailed below:

[0073] In S201 , for each wheel, least squares fitting is performed based on tire line laser point cloud data corresponding to multiple tire line lasers of the wheel to obtain a first point cloud plane corresponding to the front of each wheel.

[0074] In S202 , for each wheel, the distance between each point on the plurality of tire line lasers and the first point cloud plane is traversed and calculated.

[0075] In S203 , for each wheel, a target point cloud plane corresponding to the wheel is determined based on the distance between each point on the plurality of tire line lasers and the first point cloud plane.

[0076] In this embodiment, for each wheel, the terminal device can perform least squares fitting on the tire line laser point cloud data corresponding to the multiple tire line lasers corresponding to the wheel to obtain the first point cloud plane of the wheel front formed by the initial fitting.

[0077] Based on this, the terminal device can obtain the first point cloud plane corresponding to each wheel.

[0078] For example, please refer to FIG3 , which is a schematic diagram of a first point cloud plane provided in an embodiment of the present application.

[0079] In practice, when testing the parameters of each wheel alignment, the vehicle is typically placed on the base of the wheel alignment equipment, with a measuring unit placed at each wheel. Each measuring unit is equipped with a laser that emits a laser beam toward the corresponding wheel. When the laser beam contacts the wheel, multiple tire line lasers are formed, and each tire line laser consists of multiple points.

[0080] For example, please continue to refer to FIG3 , where the arcs are all tire line lasers.

[0081] Based on this, in order to accurately determine the point cloud plane on the front of each wheel, after obtaining the first point cloud plane of each wheel, the terminal device can traverse and calculate the distance between each point on the multiple tire line lasers corresponding to the wheel and the first point cloud plane corresponding to the wheel.

[0082] In this embodiment, for each wheel, after the terminal device obtains multiple distances corresponding to multiple tire line lasers of the wheel, the terminal device can select a target distance from the multiple distances corresponding to multiple tire line lasers according to set conditions, and determine the target point corresponding to the target distance.

[0083] Based on this, for each wheel, the terminal device can obtain the target points corresponding to the multiple tire line lasers of the wheel, and perform least squares fitting on each target point to obtain the target point cloud plane corresponding to the wheel.

[0084] The setting conditions can be set according to actual needs and are not limited here.

[0085] In some possible embodiments, the setting condition may be: selecting a point corresponding to the maximum distance.

[0086] In other possible embodiments, the distance includes, but is not limited to, a positive distance and a negative distance. The positive direction refers to a direction along a first direction toward the first point cloud plane, and the negative direction refers to a direction opposite to the first direction toward the first point cloud plane. The first direction can be determined based on actual needs and is not limited here.

[0087] For example, please refer to Figure 4, which is a schematic diagram of the forward distance provided by an embodiment of the present application, wherein A is the first point cloud plane and L1 is the tire line.

[0088] Based on this, in one embodiment of the present application, in order to improve the accuracy of determining the target point cloud plane, the terminal device can specifically determine the target point cloud plane corresponding to each wheel through steps S301 to S303 as shown in FIG5 , as detailed below:

[0089] In S301 , for each of the plurality of tire line lasers, a point having the largest forward distance from the first point cloud plane among all the points of the tire line laser is determined as a target point of the tire line laser.

[0090] In S302, least square fitting is performed based on the target points of the plurality of tire line lasers to obtain a second point cloud plane.

[0091] In this embodiment, for each tire line laser among the multiple tire line lasers, the terminal device can compare all the forward distances corresponding to the tire line laser one by one, determine the maximum forward distance, and determine the point corresponding to the maximum forward distance as the target point of the tire line laser.

[0092] Based on this, the terminal device can obtain the target points corresponding to multiple tire line lasers.

[0093] Afterwards, the terminal device may perform least square fitting based on the target points of the multiple tire line lasers to obtain a second point cloud plane of the wheel corresponding to the multiple tire line lasers.

[0094] In this embodiment, after obtaining the second point cloud plane, the terminal device can calculate the angle between the first point cloud plane and the second point cloud plane, and compare the angle with a set threshold. The set threshold can be determined according to actual needs and is not limited here. For example, the set threshold can be 0.01 degrees.

[0095] In one embodiment of the present application, when the terminal device detects that the angle between the second point cloud plane and the first point cloud plane is greater than or equal to a set threshold, step S303 may be executed.

[0096] In another embodiment of the present application, when the terminal device detects that the angle between the second point cloud plane and the first point cloud plane is less than a set threshold, it indicates that the difference between the second point cloud plane and the first point cloud plane is small. Therefore, the terminal device can directly determine the second point cloud plane as the target point cloud plane.

[0097] In S303, if the angle between the second point cloud plane and the first point cloud plane is greater than or equal to a set threshold, then, for each of the multiple tire line lasers, a point position of the tire line laser having the largest forward distance to the second point cloud plane is determined as a new target point position of the tire line laser, and least squares fitting is performed based on the multiple new target points of the tire line lasers to generate a new second point cloud plane, until the angle between the generated new second point cloud plane and the previous second point cloud plane before the new second point cloud plane is less than the set threshold, and the generated new second point cloud plane is determined as the target point cloud plane corresponding to the wheel.

[0098] In this embodiment, for each wheel, when the terminal device detects that the angle between the second point cloud plane corresponding to that wheel and the first point cloud plane corresponding to that wheel is greater than or equal to a set threshold, it indicates that the second point cloud plane differs significantly from the first point cloud plane. Therefore, to obtain an accurate target point cloud plane, the terminal device may continue to determine, for each of the multiple tire line lasers corresponding to that wheel, the point with the largest forward distance from the second point cloud plane as the new target point of the tire line laser. The terminal device then performs a least squares fit based on the multiple new target points of the tire line lasers to generate a new second point cloud plane, until the angle between the generated new second point cloud plane and the previous second point cloud plane preceding the new second point cloud plane is less than the set threshold. At this point, the terminal device may determine the generated new second point cloud plane as the target point cloud plane corresponding to the wheel.

[0099] Based on this, the terminal device can obtain the target point cloud plane corresponding to each wheel.

[0100] In one embodiment of the present application, in combination with S301 to S303, in order to improve the accuracy of obtaining the center coordinates corresponding to each wheel, the terminal device can specifically determine the center coordinates corresponding to each wheel according to the following steps, which are detailed as follows:

[0101] For each wheel, performing circle fitting on the new target point position corresponding to the wheel and generating the new second point cloud plane, to obtain a fitting circle corresponding to the wheel;

[0102] For each wheel, the center coordinates of the fitting circle corresponding to the wheel are determined, and the center coordinates of the fitting circle are determined as the center coordinates of the wheel.

[0103] In this embodiment, for each wheel, the terminal device can perform circle fitting on the new target point position of the new second point cloud plane corresponding to the wheel to obtain a fitted circle corresponding to the wheel. The terminal device can then determine the center coordinates of the fitted circle and determine the center coordinates of the fitted circle as the center coordinates of the circle corresponding to the wheel.

[0104] Based on this, the terminal device can obtain the center coordinates corresponding to each wheel.

[0105] For example, please refer to Figure 6, which is a schematic diagram of a fitting circle provided by an embodiment of the present application. As shown in Figure 6, point S is the center of the fitting circle.

[0106] In S103 , the target plane normal vector of the target point cloud plane corresponding to each wheel is calculated.

[0107] In this embodiment, after obtaining the target point cloud plane, the terminal device can randomly select three points on the target point cloud plane that are not on a straight line, and calculate the target plane normal vector based on the vector formed by any two of the three points.

[0108] In S104, four-wheel alignment parameters of the vehicle are calculated based on the normal vectors of the target planes and the coordinates of the center of the circles.

[0109] In an embodiment of the present application, since when the vehicle is on an inclined ground or uneven ground, the target point cloud plane obtained by the terminal device according to the above steps is not perpendicular to the horizontal ground, thereby affecting the subsequent calculation accuracy of the vehicle's four-wheel alignment parameters. Therefore, in order to improve the calculation accuracy of the vehicle's four-wheel alignment parameters, the terminal device can adjust each target plane normal vector according to the center coordinates corresponding to each wheel so that each target plane normal vector is parallel to the horizontal ground. Afterwards, the terminal device can calculate the corresponding vehicle four-wheel alignment parameters based on each adjusted target plane normal vector.

[0110] In one embodiment of the present application, the terminal device may obtain the target point cloud plane through steps S401 to S403 as shown in FIG7 , as detailed below:

[0111] In S401 , least square fitting is performed based on the coordinates of the center of each circle to obtain the body plane of the vehicle.

[0112] In S402 , each target plane normal vector is adjusted according to the vehicle body plane to obtain each adjusted target plane normal vector.

[0113] In S403, four-wheel alignment parameters of the vehicle are calculated based on the adjusted target plane normal vectors.

[0114] In this embodiment, the terminal device may perform least square fitting on the circle centers corresponding to the coordinates of the circle centers, and determine the plane obtained by fitting as the body plane of the vehicle.

[0115] It should be noted that the vehicle body plane refers to a plane parallel to the contact plane formed by the contact points between each tire of the vehicle and the ground.

[0116] In actual applications, when the vehicle is on horizontal ground, the vehicle body plane is parallel to the horizontal ground. Therefore, in this embodiment, the terminal device can adjust each target plane normal vector according to the vehicle body plane so that the adjusted target plane normal vector is parallel to the horizontal ground, thereby obtaining each adjusted target plane normal vector.

[0117] In one embodiment of the present application, in order to improve the accuracy of adjusting the normal vectors of each target plane, the terminal device may specifically perform step S402 according to the following, as detailed below:

[0118] Calculating a rotation matrix between the vehicle body plane and the horizontal ground;

[0119] Each of the target plane normal vectors is adjusted according to the rotation matrix to obtain each adjusted target plane normal vector.

[0120] In this embodiment, the terminal device can obtain the vehicle body plane normal vector corresponding to the vehicle body plane and the horizontal ground normal vector corresponding to the horizontal ground. Then, the terminal device can calculate the rotation matrix of the vehicle body plane to the horizontal ground based on the vehicle body plane normal vector and the horizontal ground normal vector.

[0121] Afterwards, the terminal device can adjust the normal vectors of each target plane based on the calculated rotation matrix to obtain each adjusted target plane normal vector, so that each adjusted target plane normal vector is parallel to the horizontal ground, and then the target point cloud plane corresponding to each wheel is perpendicular to the horizontal ground, so that the accurate four-wheel alignment parameters of the vehicle can be calculated based on each adjusted target plane normal vector.

[0122] In the embodiment of the present application, the four-wheel alignment parameters of the vehicle include the wheel camber angle and the wheel toe angle. Therefore, the terminal device can calculate the respective wheel camber angle and wheel toe angle based on the three-dimensional coordinates of each adjusted target plane normal vector.

[0123] In one embodiment of the present application, the terminal device may specifically determine the camber angle and toe angle of each wheel according to the following steps, which are detailed as follows:

[0124] Calculating each of the wheel camber angles according to the vertical coordinate and the horizontal coordinate of each of the adjusted target plane normal vectors;

[0125] The toe angles of the wheels are calculated based on the adjusted ordinates and abscissas of the target plane normal vectors.

[0126] It should be noted that the vertical coordinate specifically refers to the coordinate at the vertical axis in the three-dimensional coordinate.

[0127] For example, please refer to Figure 8, which is a schematic diagram of the target plane normal vector provided in one embodiment of the present application. As shown in Figure 8, B is the target point cloud plane, nz is the vertical coordinate of the target plane normal vector corresponding to the target point cloud plane on the vertical axis, ny is the vertical coordinate of the target plane normal vector corresponding to the target point cloud plane on the vertical axis, and nx is the horizontal coordinate of the target plane normal vector corresponding to the target point cloud plane on the horizontal axis.

[0128] In this embodiment, the terminal device can specifically calculate the camber angle of each wheel according to the following formula: 1i =arctan(nz i / nx i );

[0129] Among them, A 1i represents the camber angle of the i-th wheel, nz i Indicates the vertical coordinate of the adjusted target plane normal vector corresponding to the i-th wheel, nx i represents the horizontal coordinate of the adjusted target plane normal vector corresponding to the i-th wheel, and arctan(·) represents the inverse tangent function.

[0130] In this embodiment, the terminal device can specifically calculate the toe angle of each wheel according to the following formula:2i =arctan(ny i / nx i );

[0131] Among them, A 2i represents the toe angle of the i-th wheel, ny i Indicates the ordinate of the adjusted target plane normal vector corresponding to the i-th wheel, nx i represents the horizontal coordinate of the adjusted target plane normal vector corresponding to the i-th wheel, and arctan(·) represents the inverse tangent function.

[0132] From the above, it can be seen that the embodiment of the present application provides a vehicle parameter detection method, which obtains point cloud data corresponding to each wheel of the vehicle; determines the target point cloud plane corresponding to the front of each wheel and the center coordinates of each wheel according to the point cloud data corresponding to each wheel; calculates the target plane normal vector of the target point cloud plane corresponding to each wheel; and calculates the four-wheel alignment parameters of the vehicle according to each target plane normal vector and each center coordinate. Compared with the prior art that requires contact measurement, and the contact measuring instrument and the measured tire will directly produce local deformation affecting the accuracy of the measurement value, the present application can accurately determine the plane normal vector and center coordinates of the point cloud plane of the wheel through the acquired point cloud data of the wheel, thereby facilitating the accurate detection and calculation of the four-wheel alignment parameters of the vehicle without the need for contact measurement, which not only improves the measurement accuracy of the four-wheel alignment parameters of the vehicle, but also improves the measurement efficiency of the four-wheel alignment parameters of the vehicle.

[0133] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0134] Corresponding to the vehicle parameter detection method described in the above embodiment, FIG9 shows a schematic diagram of the structure of a vehicle parameter detection device provided by an embodiment of the present application. For ease of explanation, only the parts related to the embodiment of the present application are shown. Referring to FIG9, the vehicle parameter detection device 800 includes: an acquisition unit 81, a first plane determination unit 82, a first calculation unit 83, and a second calculation unit 84. Among them:

[0135] The acquisition unit 81 is used to acquire point cloud data corresponding to each wheel of the vehicle.

[0136] The first plane determining unit 82 is used to determine the target point cloud plane corresponding to the front of each wheel and the center coordinates of each wheel according to the point cloud data corresponding to each wheel.

[0137] The first calculation unit 83 is used to calculate the target plane normal vector of the target point cloud plane corresponding to each wheel.

[0138] The second calculation unit 84 is used to calculate the four-wheel alignment parameters of the vehicle according to each target plane normal vector and each circle center coordinate.

[0139] In one embodiment of the present application, the point cloud data includes tire line laser point cloud data corresponding to multiple tire line lasers, and the first plane determination unit 82 specifically includes: a first fitting unit, a third calculation unit, and a second plane determination unit.

[0140] The first fitting unit is used to perform least square fitting on each wheel based on tire line laser point cloud data corresponding to multiple tire line lasers of the wheel, to obtain a first point cloud plane corresponding to the front of each wheel.

[0141] The third calculation unit is used to traverse and calculate the distance between each point on the plurality of tire line lasers and the first point cloud plane for each wheel.

[0142] The second plane determining unit is used to determine, for each wheel, a target point cloud plane corresponding to the wheel according to the distance between each point on the plurality of tire line lasers and the first point cloud plane.

[0143] In one embodiment of the present application, the second plane determination unit specifically includes: a selection unit, a second fitting unit, and a third plane determination unit.

[0144] The selection unit is used to determine, for each of the multiple tire line lasers, a point position having a maximum forward distance from the first point cloud plane among all the point positions of the tire line laser as a target point position of the tire line laser.

[0145] The second fitting unit is used to perform least square fitting according to the target point positions of the plurality of tire line lasers to obtain a second point cloud plane.

[0146] The third plane determining unit is configured to, if the angle between the second point cloud plane and the first point cloud plane is greater than or equal to a set threshold, continue to determine, for each of the multiple tire line lasers, a point position of the tire line laser having the largest forward distance from the second point cloud plane as a new target point position of the tire line laser, and perform least squares fitting based on the multiple new target points of the tire line lasers to generate a new second point cloud plane, until the angle between the generated new second point cloud plane and a previous second point cloud plane before the new second point cloud plane is less than the set threshold, and determine the generated new second point cloud plane as the target point cloud plane corresponding to the wheel.

[0147] In one embodiment of the present application, the first plane determining unit 82 specifically includes: a third fitting unit and a coordinate determining unit.

[0148] The third fitting unit is used to perform circle fitting on the new target point position for generating the new second point cloud plane corresponding to each wheel, so as to obtain a fitting circle corresponding to the wheel.

[0149] The coordinate determination unit is used to determine the center coordinates of the fitting circle corresponding to each wheel, and determine the center coordinates of the fitting circle as the center coordinates of the wheel.

[0150] In one embodiment of the present application, the second calculation unit 84 specifically includes: a fourth fitting unit, a first adjustment unit, and a third calculation unit.

[0151] The fourth fitting unit is used to perform least square fitting according to the coordinates of the center of each circle to obtain the body plane of the vehicle.

[0152] The first adjustment unit is used to adjust each of the target plane normal vectors according to the vehicle body plane to obtain each adjusted target plane normal vector.

[0153] The third calculation unit is used to calculate the four-wheel alignment parameters of the vehicle according to the adjusted target plane normal vectors.

[0154] In one embodiment of the present application, the third calculation unit specifically includes: a fourth calculation unit and a second adjustment unit.

[0155] The fourth calculation unit is used to calculate a rotation matrix between the vehicle body plane and the horizontal ground.

[0156] The second adjustment unit is used to adjust each of the target plane normal vectors according to the rotation matrix to obtain each adjusted target plane normal vector.

[0157] In one embodiment of the present application, the four-wheel alignment parameters of each vehicle include the wheel camber angle and the wheel toe angle; the third calculation unit specifically includes: a fifth calculation unit and a sixth calculation unit.

[0158] The fifth calculation unit is used to calculate each of the wheel camber angles according to the vertical coordinate and the horizontal coordinate of each adjusted target plane normal vector.

[0159] The sixth calculation unit is used to calculate each of the wheel toe angles according to the adjusted ordinate and abscissa of each of the target plane normal vectors.

[0160] As can be seen from the above, the vehicle parameter detection device provided in the embodiment of the present application obtains the point cloud data corresponding to each wheel of the vehicle; determines the target point cloud plane corresponding to the front of each wheel and the center coordinates of each wheel according to the point cloud data corresponding to each wheel; calculates the target plane normal vector of the target point cloud plane corresponding to each wheel; and calculates the four-wheel alignment parameters of the vehicle according to each target plane normal vector and each center coordinate. The present application can accurately determine the plane normal vector and center coordinates of the point cloud plane of the wheel through the acquired point cloud data of the wheel, thereby facilitating the accurate detection and calculation of the four-wheel alignment parameters of the vehicle without the need for contact measurement, thereby improving not only the measurement accuracy of the four-wheel alignment parameters of the vehicle, but also the measurement efficiency of the four-wheel alignment parameters of the vehicle.

[0161] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0162] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0163] FIG10 is a schematic diagram of the structure of a terminal device provided in one embodiment of the present application. As shown in FIG10 , the terminal device 9 of this embodiment includes: at least one processor 90 (only one is shown in FIG10 ), a memory 91, and a computer program 92 stored in the memory 91 and executable on the at least one processor 90. When the processor 90 executes the computer program 92, it implements the steps of any of the above-mentioned vehicle parameter detection method embodiments.

[0164] The terminal device may include, but is not limited to, a processor 90 and a memory 91. Those skilled in the art will appreciate that FIG10 is merely an example of the terminal device 9 and does not limit the terminal device 9. The terminal device 9 may include more or fewer components than shown, or a combination of certain components, or different components. For example, the terminal device may also include input / output devices, network access devices, etc.

[0165] The processor 90 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor.

[0166] In some embodiments, the memory 91 may be an internal storage unit of the terminal device 9, such as the memory of the terminal device 9. In other embodiments, the memory 91 may also be an external storage device of the terminal device 9, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device 9. Furthermore, the memory 91 may include both an internal storage unit of the terminal device 9 and an external storage device. The memory 91 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program. The memory 91 may also be used to temporarily store data that has been output or is about to be output.

[0167] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned various method embodiments can be implemented.

[0168] An embodiment of the present application provides a computer program product. When the computer program product is run on a terminal device, the terminal device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0169] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to a terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electric carrier signal, a telecommunication signal and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, a computer-readable medium cannot be an electric carrier signal or a telecommunication signal.

[0170] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0171] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A vehicle parameter detection method, characterized in that: include: Obtain point cloud data corresponding to each wheel of the vehicle; Determine the target point cloud plane corresponding to the front of each wheel according to the point cloud data corresponding to each wheel, and determine the center coordinates corresponding to each wheel; Calculate the target plane normal vector of the target point cloud plane corresponding to each wheel; The four-wheel alignment parameters of the vehicle are calculated based on each of the target plane normal vectors and each of the circle center coordinates.

2. The vehicle parameter detection method according to claim 1, characterized in that: The point cloud data includes tire line laser point cloud data corresponding to a plurality of tire line lasers, and determining the target point cloud plane corresponding to the front of each wheel according to the point cloud data corresponding to each wheel includes: For each wheel, least square fitting is performed based on tire line laser point cloud data corresponding to multiple tire line lasers of the wheel to obtain a first point cloud plane corresponding to the front of each wheel; For each wheel, traverse and calculate the distance between each point on the plurality of tire line lasers and the first point cloud plane; For each wheel, a target point cloud plane corresponding to the wheel is determined according to the distance between each point on the plurality of tire line lasers and the first point cloud plane.

3. The vehicle parameter detection method according to claim 2, characterized in that: Determining the target point cloud plane corresponding to the wheel according to the distance between each point on the plurality of tire line lasers and the first point cloud plane comprises: For each of the plurality of tire line lasers, determining a point position having the largest forward distance from the first point cloud plane among all the points of the tire line laser as a target point position of the tire line laser; Performing least square fitting according to the target points of the plurality of tire line lasers to obtain a second point cloud plane; If the angle between the second point cloud plane and the first point cloud plane is greater than or equal to a set threshold, then continue to determine, for each of the multiple tire line lasers, the point position of the tire line laser with the largest forward distance from the second point cloud plane as the new target point position of the tire line laser, and perform least squares fitting based on the new target points of the multiple tire line lasers to generate a new second point cloud plane, until the angle between the generated new second point cloud plane and the previous second point cloud plane before the new second point cloud plane is less than the set threshold, and the generated new second point cloud plane is determined as the target point cloud plane corresponding to the wheel.

4. The vehicle parameter detection method according to claim 3, characterized in that: Determining the center coordinates of each wheel according to the point cloud data corresponding to each wheel includes: For each wheel, the new target point position of the new second point cloud plane corresponding to the wheel is generated. Performing circle fitting to obtain a fitting circle corresponding to the wheel; For each wheel, the center coordinates of the fitting circle corresponding to the wheel are determined, and the center coordinates of the fitting circle are determined as the center coordinates of the wheel.

5. The vehicle parameter detection method according to any one of claims 1 to 4, characterized in that: The four-wheel alignment parameters of the vehicle are calculated based on each of the target plane normal vectors and each of the circle center coordinates, including: Performing least square fitting according to the coordinates of the center of each circle to obtain the body plane of the vehicle; Adjusting each of the target plane normal vectors according to the vehicle body plane to obtain each adjusted target plane normal vector; The four-wheel alignment parameters of the vehicle are calculated based on the adjusted target plane normal vectors.

6. The vehicle parameter detection method according to claim 5, characterized in that: The step of adjusting each of the target plane normal vectors according to the vehicle body plane to obtain each of the adjusted target plane normal vectors includes: Calculating a rotation matrix between the vehicle body plane and the horizontal ground; Each of the target plane normal vectors is adjusted according to the rotation matrix to obtain each adjusted target plane normal vector.

7. The vehicle parameter detection method according to claim 5, characterized in that: The four-wheel alignment parameters of the vehicle include the wheel camber angle and the wheel toe angle; The step of calculating the four-wheel alignment parameters of the vehicle according to each adjusted target plane normal vector comprises: Calculating each of the wheel camber angles according to the vertical coordinate and the horizontal coordinate of each of the adjusted target plane normal vectors; Each wheel toe angle is calculated based on the adjusted ordinate and abscissa of each target plane normal vector.

8. A vehicle parameter detection device, characterized in that: include: An acquisition unit, used to acquire point cloud data corresponding to each wheel of the vehicle; A first plane determination unit, configured to determine a target point cloud plane corresponding to the front of each wheel and determine the center coordinates of each wheel according to the point cloud data corresponding to each wheel; A first calculation unit, used to calculate a target plane normal vector of a target point cloud plane corresponding to each wheel; The second calculation unit is used to calculate the four-wheel alignment parameters of the vehicle according to each of the target plane normal vectors and each of the circle center coordinates.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the vehicle parameter detection method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the vehicle parameter detection method according to any one of claims 1 to 7 is implemented.

Images