High-precision pavement texture rapid measurement method and device

Abstract

The invention relates to the technical field of pavement detection, and provides a high-precision pavement texture rapid measurement method and device. The method comprises the following steps: acquiring object space elevation data and object space abscissa data based on image space elevation data and image space abscissa data of a pavement to be measured; splicing the object space elevation data and the object space abscissa data according to a time sequence to obtain object space elevation spliced data and object space abscissa spliced data; converting the object space elevation splicing data according to a preset transverse interval to obtain preset interval object space elevation data; and fusing the preset spacer elevation data to obtain texture data of the to-be-measured pavement. The high-precision pavement texture data is not influenced by various factors, can be applied to scenes when outdoor actual pavement normally moves, can effectively reduce measurement errors and meet road network level detection requirements based on the high-precision pavement texture to measure pavement friction force or pavement skid resistance, and can be popularized and applied in actual engineering.

Description

Technical Field

[0001] The present application relates to the technical field of road surface detection, and in particular to a high-precision road surface texture rapid measurement method and device. Background Art

[0002] The friction between tires and the road is a crucial factor affecting road driving safety. Road friction is the resistance generated by the relative movement between tires and the road surface, which is caused by the combination of adhesion and hysteresis. The traditional method of measuring road friction or anti-skid performance is still mainly to drag tires or rubber pads on the road or sample to measure road friction. The measurement results of this type of measurement method are usually affected by factors such as road water film thickness, road temperature, tire or rubber pad movement speed, rubber aging, rubber wear and even road surface flatness, making the measurement results difficult to control and poor in reproducibility.

[0003] In order to overcome the defects of traditional methods for measuring road friction or anti-skid performance, there are currently methods for measuring road friction or anti-skid performance based on road surface texture. However, the road surface texture in these methods is usually obtained during low-speed movement on simulated road samples indoors. These methods cannot meet the road network-level detection of road friction or anti-skid performance and cannot be promoted and applied in actual engineering projects. Summary of the invention

[0004] The embodiments of the present application provide a high-precision road surface texture rapid measurement method and device to solve the problem that in the existing methods for measuring road surface friction or anti-skid performance based on road surface texture, the road surface texture is usually obtained when moving at a low speed on a simulated road sample indoors. These methods cannot meet the road network-level detection of road surface friction or anti-skid performance and cannot be promoted and applied in actual engineering projects.

[0005] In a first aspect, an embodiment of the present application provides a high-precision road surface texture rapid measurement method, comprising: Based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured, obtaining the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured; Respectively splicing the object space elevation data and the object space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be measured; Converting the object space elevation splicing data according to a preset lateral interval to obtain preset interval object space elevation data of the road surface to be tested; The preset spacer elevation data are fused to obtain the texture data of the road surface to be tested.

[0006] In one embodiment, the image-space elevation data and image-space horizontal coordinate data of the road surface to be tested are obtained based on the following method: Using multiple line scanning three-dimensional measurement sensors to collaboratively collect image-space elevation data and image-space horizontal coordinate data of the road surface position to be measured corresponding to the same laser line projected by the same laser at multiple positions; The collaborative collection at multiple positions includes cross collection at multiple positions along the driving direction of the road surface to be tested and synchronous collection at multiple positions along the width direction of the road surface to be tested; The image-space elevation data and the image-space horizontal coordinate data of the road surface to be tested are mapped one by one.

[0007] In one embodiment, the step of acquiring the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured comprises: Acquire a first mapping relationship between image-space elevation data and object-space elevation data, and a second mapping relationship between image-space horizontal coordinate data and object-space horizontal coordinate data of the plurality of line-scanning three-dimensional measurement sensors in their own object-space coordinate systems; Based on the image-space elevation data of the road surface to be measured and the first mapping relationship, acquiring object-space elevation data of the road surface to be measured; Based on the image-space horizontal coordinate data of the road surface to be measured and the second mapping relationship, acquiring object-space horizontal coordinate data of the road surface to be measured; The object-space elevation data of the road surface to be measured is mapped one-to-one with the object-space horizontal coordinate data of the road surface to be measured.

[0008] In one embodiment, the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured are spliced ​​in time sequence to obtain the object-space elevation splicing data and the object-space horizontal coordinate splicing data of the road surface to be measured, including: Performing posture correction on the object space elevation data and the object space horizontal coordinate data of the road surface to be measured by using the measurement posture information of the multiple line scanning three-dimensional measurement sensors to obtain corrected object space elevation data and corrected object space horizontal coordinate data; The corrected object space elevation data and the corrected object space horizontal coordinate data are spliced ​​respectively according to the data acquisition time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be tested.

[0009] In one embodiment, converting the object-space elevation stitching data according to a preset lateral interval to obtain the preset interval object-space elevation data of the road surface to be tested includes: Based on the relative positional relationship between the plurality of line scanning three-dimensional measurement sensors, the object space elevation stitching data and the object space horizontal coordinate stitching data are converted into a reference coordinate system to obtain reference object space elevation data and reference object space horizontal coordinate data; The reference object space elevation data is converted according to the preset interval of the reference object space horizontal coordinate data to obtain the preset interval object space elevation data of the road surface to be measured.

[0010] In one embodiment, based on the relative position relationship between the plurality of line scanning three-dimensional measurement sensors, the object space elevation stitching data and the object space horizontal coordinate stitching data are converted into a reference coordinate system to obtain reference object space elevation data and reference object space horizontal coordinate data, including: Taking the object space coordinate system of the target line scanning 3D measurement sensor as the reference coordinate system, based on the relative position relationship between other line scanning 3D measurement sensors in the plurality of line scanning 3D measurement sensors and the target line scanning 3D measurement sensor, converting the object space elevation stitching data and the object space horizontal coordinate stitching data into the reference coordinate system to obtain reference object space elevation data and reference object space horizontal coordinate data; The reference object space elevation data and the reference object space horizontal coordinate data are mapped one by one; The target line scanning 3D measurement sensor is any one of the plurality of line scanning 3D measurement sensors, and the relative position relationship includes an installation angle difference and an object coordinate system origin offset.

[0011] In one embodiment, converting the reference object space elevation data according to the preset interval of the reference object space horizontal coordinate data to obtain the preset interval object space elevation data of the road surface to be measured includes: Among the reference object space horizontal coordinate data corresponding to the reference object space elevation data, respectively obtain the reference object space horizontal coordinate data closest to the multiple target horizontal positions at the preset interval, and obtain multiple target reference object space horizontal coordinate data matching the multiple target horizontal positions; By using the one-to-one mapping relationship between the reference object space elevation data and the reference object space horizontal coordinate data, the reference object space elevation data corresponding to the plurality of target reference object space horizontal coordinate data are determined as the preset interval object space elevation data of the road surface to be measured.

[0012] In one embodiment, the step of fusing the elevation data of the spacer to obtain the texture data of the road surface to be tested includes: The preset spacer elevation data are sequentially fused according to the corresponding measurement mileage positions and target lateral positions to obtain the texture data of the road surface to be measured.

[0013] In a second aspect, an embodiment of the present application provides a high-precision road surface texture rapid measurement device, comprising: a data processing unit; The data processing unit is used for: Based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured, obtaining the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured; Respectively splicing the object space elevation data and the object space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be measured; Converting the object space elevation splicing data according to a preset lateral interval to obtain preset interval object space elevation data of the road surface to be tested; The preset spacer elevation data are fused to obtain the texture data of the road surface to be tested.

[0014] In one embodiment, it further includes: a mobile measurement vehicle, a measurement unit, a control unit and a power supply unit; The measuring unit, the control unit and the power supply unit are arranged on the mobile measuring vehicle; The measuring unit is used to obtain image-space elevation data and image-space horizontal coordinate data of the road surface to be measured; The control unit is used to control the multiple sensors in the measuring unit to work in coordination; The power supply unit is used to provide energy for multiple devices in the measuring unit; The measurement unit includes a laser, an inertial attitude measurement sensor and a plurality of line scanning three-dimensional measurement sensors; The multiple line scanning three-dimensional measurement sensors are used to collaboratively collect image-space elevation data of the road surface position to be measured corresponding to the same laser line projected by the laser at multiple positions; The inertial attitude measurement sensor is used to obtain measurement attitude information of the multiple line scanning three-dimensional measurement sensors.

[0015] The high-precision road surface texture rapid measurement method and device provided in the present application obtain object space elevation data and object space horizontal coordinate data of the road surface to be measured based on the image space elevation data and image space horizontal coordinate data of the road surface to be measured, splice the object space elevation data and object space horizontal coordinate data of the road surface to be measured in time sequence to obtain object space elevation splicing data and object space horizontal coordinate splicing data of the road surface to be measured, convert the object space elevation splicing data according to a preset horizontal interval to obtain object space elevation data of the road surface to be measured at a preset interval, and fuse the object space elevation data at the preset interval to obtain texture data of the road surface to be measured. The present application obtains the final texture data of the road surface to be tested by performing image-to-object conversion, time series splicing, interval conversion and data fusion on the image-side elevation data and image-side horizontal coordinate data of the road surface to be tested. The high-precision road surface texture data is not affected by factors such as road surface water film thickness, road surface temperature, tire or rubber pad movement speed, rubber aging, rubber wear and even road surface flatness, and can be applied to scenes of normal movement on actual outdoor roads. Therefore, measuring road surface friction or road surface anti-skid performance based on the high-precision road surface texture can effectively reduce measurement errors, meet road network-level detection of road surface friction or road surface anti-skid performance, and can be promoted and applied in actual engineering projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 This is one of the flow charts of the high-precision road surface texture rapid measurement method provided in the embodiment of the present application; Figure 2 This is the second flow chart of the high-precision road surface texture rapid measurement method provided in the embodiment of the present application; Figure 3 This is the third flow chart of the high-precision road surface texture rapid measurement method provided in the embodiment of the present application; Figure 4 This is the fourth flow chart of the high-precision road surface texture rapid measurement method provided in the embodiment of the present application; Figure 5 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0019] It should be noted that in the description of the embodiments of the present application, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements. The orientation or position relationship indicated by the terms "upper", "lower" and the like is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. Unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be a connection between the two elements. For those skilled in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0020] The terms "first", "second", etc. in this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0021] Figure 1 This is one of the flow charts of the high-precision road surface texture rapid measurement method provided in the embodiment of the present application. Figure 1 , the present application embodiment provides a high-precision road surface texture rapid measurement method, which may include: 101. Based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured, obtain the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured; 102. splicing the object space elevation data and the object space horizontal coordinate data of the road surface to be measured respectively in time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be measured; 103. Convert the object space elevation splicing data according to a preset lateral interval to obtain preset interval object space elevation data of the road surface to be measured; 104. The preset spacer elevation data are integrated to obtain the texture data of the road surface to be tested.

[0022] In step 101, the image-space elevation data and image-space horizontal coordinate data of the road surface to be measured are the elevation data and horizontal coordinate data of the road surface to be measured in the image space, and the object-space elevation data and object-space horizontal coordinate data of the road surface to be measured are the elevation data and horizontal coordinate data of the road surface to be measured in the object space. For each point on the road surface to be measured, there is a one-to-one mapping relationship between its data in the image space and its data in the object space. Therefore, according to the one-to-one mapping relationship, the image-space elevation data of the road surface to be measured can be converted into object-space elevation data, and the image-space horizontal coordinate data of the road surface to be measured can be converted into object-space horizontal coordinate data.

[0023] In step 102, since the collection time of each data is synchronously recorded when the image space elevation data and the image space horizontal coordinate data of the road surface to be tested are collected in the early stage, these collection times can also be synchronously corresponding to the converted object space elevation data and image space elevation data. Therefore, in this step, the object space elevation data collected at each moment can be spliced ​​according to the sequence of collection times to obtain the object space elevation splicing data of the road surface to be tested, and the object space horizontal coordinate data collected at each moment can be spliced ​​according to the sequence of collection times to obtain the object space horizontal coordinate splicing data of the road surface to be tested.

[0024] In step 103, a preset lateral interval can be set according to one's own needs, and the coordinate system of the object-side elevation stitching data is first converted to make the coordinate system of each data the same, and then the resolution of the object-side elevation stitching data after the coordinate system is unified is converted according to the preset lateral interval to make the resolution of each data uniform, thereby obtaining the preset interval object-side elevation data of the road surface to be tested.

[0025] In step 104, the preset interval object space elevation data may be fused in sequence according to the horizontal and vertical coordinate positions, so as to obtain fused object space elevation data, that is, texture data of the road surface to be measured.

[0026] The high-precision road surface texture rapid measurement method provided in the present embodiment obtains the object space elevation data and object space horizontal coordinate data of the road surface to be measured based on the image space elevation data and image space horizontal coordinate data of the road surface to be measured, splices the object space elevation data and object space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object space elevation splicing data and object space horizontal coordinate splicing data of the road surface to be measured, converts the object space elevation splicing data according to a preset horizontal interval to obtain the preset interval object space elevation data of the road surface to be measured, and fuses the preset interval object space elevation data to obtain the texture data of the road surface to be measured. This embodiment obtains the final road surface texture data to be tested by performing image-to-object conversion, time series splicing, interval conversion and data fusion on the image-side elevation data and image-side horizontal coordinate data of the road surface to be tested. The high-precision road surface texture data is not affected by factors such as road surface water film thickness, road surface temperature, tire or rubber pad movement speed, rubber aging, rubber wear and even road surface flatness, and can be applied to scenes of normal movement on actual outdoor roads. Therefore, measuring road surface friction or road surface anti-skid performance based on the high-precision road surface texture can effectively reduce measurement errors, meet road network-level detection of road surface friction or road surface anti-skid performance, and can be promoted and applied in actual engineering projects.

[0027] In one embodiment, the image-space elevation data and image-space horizontal coordinate data of the road surface to be tested can be obtained based on the following method: Using multiple line scanning three-dimensional measurement sensors to collaboratively collect image-space elevation data and image-space horizontal coordinate data of the road surface position to be measured corresponding to the same laser line projected by the same laser at multiple positions; Collaborative collection at multiple locations includes cross collection at multiple locations along the driving direction of the road to be tested and synchronous collection at multiple locations along the width direction of the road to be tested; The image-space elevation data and image-space horizontal coordinate data of the road surface to be tested are mapped one by one.

[0028] In this embodiment, on the one hand, by collaboratively collecting image-side elevation data and image-side horizontal coordinate data through multiple line-scanning three-dimensional measurement sensors, the same data collected by the multiple line-scanning three-dimensional measurement sensors can be compared with each other to eliminate errors and improve the accuracy of collected data. In addition, when some sensors fail, other sensors can work independently without being affected, thereby improving the stability of data collection. On the other hand, the driving direction and width direction of the road surface to be measured are perpendicular to each other. Through the collaborative collection of longitudinal data, the longitudinal data collection density can be improved, and through the collaborative collection of transverse data, the data collection width can be increased, providing a better data foundation for subsequent data splicing, data conversion and data fusion.

[0029] Figure 2 This is the second flow chart of the high-precision road surface texture rapid measurement method provided in the embodiment of the present application. Figure 2In one embodiment, obtaining the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured may include: 201. Acquire a first mapping relationship between image-space elevation data and object-space elevation data, and a second mapping relationship between image-space horizontal coordinate data and object-space horizontal coordinate data of a plurality of line scanning three-dimensional measurement sensors in their own object-space coordinate systems; 202. Acquire object-space elevation data of the road surface to be measured based on the image-space elevation data of the road surface to be measured and the first mapping relationship; 203. Obtain object-space horizontal coordinate data of the road surface to be measured based on the image-space horizontal coordinate data of the road surface to be measured and the second mapping relationship.

[0030] The object space elevation data of the road surface to be measured is mapped one to one with the object space horizontal coordinate data of the road surface to be measured.

[0031] In step 201, for any line scanning three-dimensional measurement sensor, a first mapping relationship and a second mapping relationship in its own object coordinate system can be acquired by calibration.

[0032] In step 202, since each line scanning 3D measurement sensor has collected image space elevation data and has its own first mapping relationship, the object space elevation data acquired based on this corresponds one-to-one to each line scanning 3D measurement sensor.

[0033] In step 203, since each line scanning 3D measurement sensor has collected image-space horizontal coordinate data and has its own second mapping relationship, the object-space horizontal coordinate data acquired based on this corresponds one-to-one to each line scanning 3D measurement sensor.

[0034] This embodiment obtains the first mapping relationship and the second mapping relationship of each line scanning three-dimensional measurement sensor itself through calibration, and then combines the image space elevation data and image space horizontal coordinate data collected by itself to accurately obtain the corresponding object space elevation data and object space horizontal coordinate data.

[0035] Figure 3 This is the third flow chart of the high-precision road surface texture rapid measurement method provided in the embodiment of the present application. Figure 3 In one embodiment, the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured are spliced ​​in time sequence to obtain the object-space elevation splicing data and the object-space horizontal coordinate splicing data of the road surface to be measured, which may include: 301. Performing posture correction on object space elevation data and object space horizontal coordinate data of the road surface to be measured using measurement posture information of multiple line scanning three-dimensional measurement sensors to obtain corrected object space elevation data and corrected object space horizontal coordinate data; 302. The corrected object space elevation data and the corrected object space horizontal coordinate data are spliced ​​according to the data acquisition time sequence to obtain object space elevation splicing data and object space horizontal coordinate splicing data of the road surface to be tested.

[0036] In step 301, an inertial attitude measurement sensor can be used to simultaneously obtain measurement attitude information of multiple line scanning three-dimensional measurement sensors, where the multiple line scanning three-dimensional measurement sensors are installed in the same measurement unit. The measurement attitude information of the line scanning three-dimensional measurement sensors is used to compensate for attitude measurement errors of the corresponding object space elevation data and object space horizontal coordinate data, thereby achieving the purpose of attitude correction.

[0037] This embodiment first performs posture correction on the object space elevation data and the object space horizontal coordinate data, and then performs time-series splicing on the corrected object space elevation data and object space horizontal coordinate data, so that the spliced ​​object space elevation data and object space horizontal coordinate data eliminate posture measurement errors and improve data accuracy.

[0038] Figure 4 This is the fourth flow chart of the high-precision road surface texture rapid measurement method provided in the embodiment of the present application. Figure 4 In one embodiment, converting the object-space elevation splicing data according to a preset lateral interval to obtain the preset interval object-space elevation data of the road surface to be measured may include: 401. Based on the relative position relationship between the multiple line scanning three-dimensional measurement sensors, the object space elevation stitching data and the object space horizontal coordinate stitching data are converted into a reference coordinate system to obtain reference object space elevation data and reference object space horizontal coordinate data; 402. Convert the reference object space elevation data according to the preset interval of the reference object space horizontal coordinate data to obtain the preset interval object space elevation data of the road surface to be measured.

[0039] In step 401, the specific steps may be as follows: The object space coordinate system of the target line scanning 3D measurement sensor is used as the reference coordinate system, and based on the relative position relationship between other line scanning 3D measurement sensors in the plurality of line scanning 3D measurement sensors and the target line scanning 3D measurement sensor, the object space elevation stitching data and the object space horizontal coordinate stitching data are converted into the reference coordinate system to obtain reference object space elevation data and reference object space horizontal coordinate data; The reference object space elevation data and the reference object space horizontal coordinate data are mapped one by one; The target line scanning 3D measurement sensor is any line scanning 3D measurement sensor among the multiple line scanning 3D measurement sensors, and the relative position relationship includes the installation angle difference and the object coordinate system origin offset.

[0040] The installation angle difference between the multiple line scanning 3D measurement sensors and the offset between the coordinate origins in the object coordinate system of the multiple line scanning 3D measurement sensors can be obtained by calibration, and any line scanning 3D measurement sensor among the multiple line scanning 3D measurement sensors is used as the target line scanning 3D measurement sensor, and its object coordinate system is used as the reference coordinate system. Based on the obtained installation angle difference between the other line scanning 3D measurement sensors and the target line scanning 3D measurement sensor, and the offset between the coordinate origin in the object coordinate system of the other line scanning 3D measurement sensors and the coordinate origin in the reference coordinate system, the object elevation stitching data and the object horizontal coordinate stitching data corresponding to the other line scanning 3D measurement sensors are converted to the reference coordinate system, so that the object elevation stitching data and the object horizontal coordinate stitching data corresponding to all the line scanning 3D measurement sensors are unified under the reference coordinate system, thereby obtaining the reference object elevation data and the reference object horizontal coordinate data corresponding to all the line scanning 3D measurement sensors under the same coordinate system.

[0041] In step 402, the specific steps may be as follows: 402a. From the reference object space horizontal coordinate data corresponding to the reference object space elevation data, respectively obtain the reference object space horizontal coordinate data closest to the multiple target horizontal positions at preset intervals, and obtain multiple target reference object space horizontal coordinate data matching the multiple target horizontal positions; 402b. Using the one-to-one mapping relationship between the reference object space elevation data and the reference object space horizontal coordinate data, the reference object space elevation data corresponding to the plurality of target reference object space horizontal coordinate data are determined as the preset interval object space elevation data of the road surface to be measured.

[0042] The preset interval is the preset resolution, and the reference object space horizontal coordinate data closest to the target horizontal position is used as the reference object space horizontal coordinate data of the preset interval, and then the object space elevation data of the preset interval is obtained according to the one-to-one mapping relationship between the reference object space horizontal coordinate data and the reference object space elevation data, that is, the resolution of the reference object space elevation data is unified to the preset resolution. Afterwards, the target horizontal position of the preset interval can be used as the preset object space horizontal coordinate position corresponding to the object space elevation data of the preset interval.

[0043] In this embodiment, any line scanning 3D measurement sensor is used as a target line scanning 3D measurement sensor, and its object space coordinate system is used as a reference coordinate system. Based on the relative position relationship between other line scanning 3D measurement sensors and the target line scanning 3D measurement sensor and the relative position relationship between the object space coordinate systems of other line scanning 3D measurement sensors and the reference coordinate system, data corresponding to other line scanning 3D measurement sensors are converted into the reference coordinate system by using a plurality of relative position relationships, so that data corresponding to a plurality of line scanning 3D measurement sensors can be efficiently and accurately unified into the same coordinate system, thereby avoiding data deviation caused by data corresponding to different coordinate systems. Furthermore, based on the reference object space horizontal coordinate data in the same coordinate system and in combination with the target horizontal position at a preset interval, reference object space elevation data in the same coordinate system is converted into object space elevation data at a preset interval, thereby enabling the reference object space elevation data to be efficiently and accurately unified into the same resolution.

[0044] In one embodiment, the preset spacer elevation data is merged to obtain the texture data of the road surface to be tested, which may include: The preset spacer elevation data are fused in sequence according to the corresponding measurement mileage position and target lateral position to obtain the texture data of the road surface to be measured.

[0045] The preset interval object elevation data are sequentially merged according to the corresponding measurement mileage positions, that is, the object elevation data at the preset resolution are sequentially merged along the driving direction or the road extension direction, that is, the object elevation data at the preset resolution are sequentially spliced ​​along the vertical coordinate position; The preset interval object space elevation data are sequentially fused according to the corresponding target lateral positions, that is, the object space elevation data at the preset resolution are sequentially fused along the road width direction or the cross-section direction, that is, the object space elevation data at the preset resolution are sequentially spliced ​​along the horizontal coordinate position.

[0046] In this embodiment, by sequentially fusing the object space elevation data at a preset resolution along the horizontal and vertical coordinate positions, the overall object space elevation data of the road surface to be measured at the preset resolution can be obtained, thereby achieving rapid measurement of high-precision road surface texture.

[0047] The embodiment of the present application provides a high-precision road surface texture rapid measurement device, which may include: a data processing unit; The data processing unit is used to: Based on the image space elevation data and the image space horizontal coordinate data of the road surface to be measured, obtaining the object space elevation data and the object space horizontal coordinate data of the road surface to be measured; Respectively splicing the object space elevation data and the object space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be measured; The object space elevation splicing data is converted according to the preset lateral interval to obtain the preset interval object space elevation data of the road surface to be tested; The preset spacer elevation data are fused to obtain the texture data of the road surface to be tested.

[0048] Furthermore, the device also includes: a mobile measurement vehicle, a measurement unit, a control unit and a power supply unit; The measuring unit, the control unit and the power supply unit are arranged on the mobile measuring vehicle; The measuring unit is used to obtain image-space elevation data and image-space horizontal coordinate data of the road surface to be measured; The control unit is used to control the multiple sensors in the measuring unit to work in coordination; The power supply unit is used to provide energy for multiple devices in the measuring unit; The measurement unit includes a laser, an inertial attitude measurement sensor, and multiple line scan 3D measurement sensors; A plurality of line scanning three-dimensional measurement sensors are used to collaboratively collect image-space elevation data of the road surface position to be measured corresponding to the same laser line projected by the laser at multiple positions; The inertial attitude measurement sensor is used to obtain the measurement attitude information of multiple line scanning 3D measurement sensors.

[0049] Among them, any line scanning 3D measurement sensor can obtain the elevation data of all measuring points in the cross section under the same measurement posture in a single measurement, and the lateral resolution of the elevation data is better than 0.2 mm; the sampling interval of the line scanning 3D measurement sensor in the moving direction is 0.1 mm to 0.5 mm, and the measurement width accuracy is better than 120 mm.

[0050] The high-precision road surface texture rapid measurement device provided in the present embodiment can utilize a mobile measurement vehicle to integrate a data processing unit, a measurement unit, a control unit, and a power supply unit, and drive these units to move to perform high-precision texture rapid measurement of the road surface to be measured. The final road surface texture data to be measured is obtained by performing image-to-object conversion, time sequence splicing, interval conversion, and data fusion on the image-side elevation data and the image-side horizontal coordinate data of the road surface to be measured. The high-precision road surface texture data is not affected by factors such as road surface water film thickness, road surface temperature, tire or rubber pad movement speed, rubber aging, rubber wear, and even road surface flatness, and can be applied to scenes of normal outdoor road surface movement. Therefore, measuring road surface friction or road surface anti-skid performance based on the high-precision road surface texture can effectively reduce measurement errors, meet road network-level detection of road surface friction or road surface anti-skid performance, and can be promoted and applied in actual engineering projects.

[0051] FIG5 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 5As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call a computer program in the memory 530 to execute the steps of the high-precision road surface texture rapid measurement method, for example including: Based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured, obtaining the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured; Respectively splicing the object space elevation data and the object space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be measured; Converting the object space elevation splicing data according to a preset lateral interval to obtain preset interval object space elevation data of the road surface to be tested; The preset spacer elevation data are fused to obtain the texture data of the road surface to be tested.

[0052] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0053] On the other hand, an embodiment of the present application further provides a computer program product, the computer program product comprising a computer program, the computer program may be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can execute the steps of the high-precision road surface texture rapid measurement method provided in the above embodiments, for example, including: Based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured, obtaining the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured; Respectively splicing the object space elevation data and the object space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be measured; Converting the object space elevation splicing data according to a preset lateral interval to obtain preset interval object space elevation data of the road surface to be tested; The preset spacer elevation data are fused to obtain the texture data of the road surface to be tested.

[0054] On the other hand, an embodiment of the present application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program is used to cause a processor to execute the steps of the high-precision road surface texture rapid measurement method provided in the above embodiments, for example, including: Based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured, obtaining the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured; Respectively splicing the object space elevation data and the object space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be measured; Converting the object space elevation splicing data according to a preset lateral interval to obtain preset interval object space elevation data of the road surface to be tested; The preset spacer elevation data are fused to obtain the texture data of the road surface to be tested.

[0055] The non-transitory computer-readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drives (SSDs)), etc.

[0056] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0057] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. 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. However, 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 embodiments of the present application.

Claims

1. A high-precision road surface texture rapid measurement method, characterized in that: include: Based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured, obtaining the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured; Respectively splicing the object space elevation data and the object space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be measured; Converting the object space elevation splicing data according to a preset lateral interval to obtain preset interval object space elevation data of the road surface to be tested; The preset spacer elevation data are fused to obtain the texture data of the road surface to be tested.

2. The high-precision road surface texture rapid measurement method according to claim 1 is characterized in that: The image-space elevation data and image-space horizontal coordinate data of the road surface to be tested are obtained based on the following method: Using multiple line scanning three-dimensional measurement sensors to collaboratively collect image-space elevation data and image-space horizontal coordinate data of the road surface position to be measured corresponding to the same laser line projected by the same laser at multiple positions; The collaborative collection at multiple positions includes cross collection at multiple positions along the driving direction of the road surface to be tested and synchronous collection at multiple positions along the width direction of the road surface to be tested; The image-space elevation data and the image-space horizontal coordinate data of the road surface to be tested are mapped one by one.

3. The high-precision road surface texture rapid measurement method according to claim 2 is characterized in that: The method of obtaining the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured comprises: Acquire a first mapping relationship between image-space elevation data and object-space elevation data, and a second mapping relationship between image-space horizontal coordinate data and object-space horizontal coordinate data of the plurality of line-scanning three-dimensional measurement sensors in their own object-space coordinate systems; Based on the image-space elevation data of the road surface to be measured and the first mapping relationship, acquiring object-space elevation data of the road surface to be measured; Based on the image-space horizontal coordinate data of the road surface to be measured and the second mapping relationship, acquiring object-space horizontal coordinate data of the road surface to be measured; The object-space elevation data of the road surface to be measured is mapped one-to-one with the object-space horizontal coordinate data of the road surface to be measured.

4. The high-precision road surface texture rapid measurement method according to claim 2 is characterized in that: The method of respectively splicing the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object-space elevation splicing data and the object-space horizontal coordinate splicing data of the road surface to be measured comprises: Performing posture correction on the object space elevation data and the object space horizontal coordinate data of the road surface to be measured by using the measurement posture information of the multiple line scanning three-dimensional measurement sensors to obtain corrected object space elevation data and corrected object space horizontal coordinate data; The corrected object space elevation data and the corrected object space horizontal coordinate data are spliced ​​respectively according to the data acquisition time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be tested.

5. The high-precision road surface texture rapid measurement method according to claim 2 is characterized in that: The step of converting the object space elevation splicing data according to a preset lateral interval to obtain the preset interval object space elevation data of the road surface to be tested includes: Based on the relative positional relationship between the plurality of line scanning three-dimensional measurement sensors, the object space elevation stitching data and the object space horizontal coordinate stitching data are converted into a reference coordinate system to obtain reference object space elevation data and reference object space horizontal coordinate data; The reference object space elevation data is converted according to the preset interval of the reference object space horizontal coordinate data to obtain the preset interval object space elevation data of the road surface to be measured.

6. The high-precision road surface texture rapid measurement method according to claim 5 is characterized in that: The method of converting the object space elevation stitching data and the object space horizontal coordinate stitching data into a reference coordinate system based on the relative position relationship between the plurality of line scanning three-dimensional measurement sensors to obtain reference object space elevation data and reference object space horizontal coordinate data includes: Taking the object space coordinate system of the target line scanning 3D measurement sensor as the reference coordinate system, based on the relative position relationship between other line scanning 3D measurement sensors in the plurality of line scanning 3D measurement sensors and the target line scanning 3D measurement sensor, converting the object space elevation stitching data and the object space horizontal coordinate stitching data into the reference coordinate system to obtain reference object space elevation data and reference object space horizontal coordinate data; The reference object space elevation data and the reference object space horizontal coordinate data are mapped one by one; The target line scanning 3D measurement sensor is any one of the plurality of line scanning 3D measurement sensors, and the relative position relationship includes an installation angle difference and an object coordinate system origin offset.

7. The high-precision road surface texture rapid measurement method according to claim 5 is characterized in that: The step of converting the reference object space elevation data according to the preset interval of the reference object space horizontal coordinate data to obtain the preset interval object space elevation data of the road surface to be measured includes: Among the reference object space horizontal coordinate data corresponding to the reference object space elevation data, respectively obtain the reference object space horizontal coordinate data closest to the multiple target horizontal positions at the preset interval, and obtain multiple target reference object space horizontal coordinate data matching the multiple target horizontal positions; By using the one-to-one mapping relationship between the reference object space elevation data and the reference object space horizontal coordinate data, the reference object space elevation data corresponding to the plurality of target reference object space horizontal coordinate data are determined as the preset interval object space elevation data of the road surface to be measured.

8. The high-precision road surface texture rapid measurement method according to claim 7 is characterized in that: The step of fusing the elevation data of the spacer to obtain the texture data of the road surface to be tested includes: The preset spacer elevation data are sequentially fused according to the corresponding measurement mileage positions and target lateral positions to obtain the texture data of the road surface to be measured.

9. A high-precision road surface texture rapid measurement device, characterized in that: include: Data processing unit; The data processing unit is used for: Based on the image-space elevation data and the image-space horizontal coordinate data of the road surface to be measured, obtaining the object-space elevation data and the object-space horizontal coordinate data of the road surface to be measured; Respectively splicing the object space elevation data and the object space horizontal coordinate data of the road surface to be measured in time sequence to obtain the object space elevation splicing data and the object space horizontal coordinate splicing data of the road surface to be measured; Converting the object space elevation splicing data according to a preset lateral interval to obtain preset interval object space elevation data of the road surface to be tested; The preset spacer elevation data are fused to obtain the texture data of the road surface to be tested.

10. The high-precision road surface texture rapid measurement device according to claim 9, characterized in that: Also includes: Mobile measurement vehicle, measurement unit, control unit and power supply unit; The measuring unit, the control unit and the power supply unit are arranged on the mobile measuring vehicle; The measuring unit is used to obtain image-space elevation data and image-space horizontal coordinate data of the road surface to be measured; The control unit is used to control the multiple sensors in the measuring unit to work in coordination; The power supply unit is used to provide energy for multiple devices in the measuring unit; The measurement unit includes a laser, an inertial attitude measurement sensor and a plurality of line scanning three-dimensional measurement sensors; The multiple line scanning three-dimensional measurement sensors are used to collaboratively collect image-space elevation data of the road surface position to be measured corresponding to the same laser line projected by the laser at multiple positions; The inertial attitude measurement sensor is used to obtain measurement attitude information of the multiple line scanning three-dimensional measurement sensors.

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