Road safety detection method and equipment based on multi-scale three dimensions

Abstract

The invention relates to the technical field of road detection, and provides a multi-scale three-dimensional road safety detection method and equipment. The method comprises the following steps: acquiring vehicle-mounted measurement data of a target road; the vehicle-mounted measurement data comprises lane-level pavement three-dimensional data and pavement micro-texture data; performing attitude compensation on the vehicle-mounted measurement data to obtain reconstructed measurement data; obtaining target information of the target road based on the reconstruction measurement data; the target information comprises road geometric linear information, road surface height difference sudden change information and road surface anti-slide performance information; and obtaining a safety detection result of the target road based on the target information. According to the method, the comprehensiveness and the accuracy of road surface data acquisition can be improved, so that accurate detection of the road safety condition is realized, and the effectiveness of evaluating the road traffic safety risk based on the detection result of the road safety condition is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of road detection, in particular to a road safety detection method and equipment based on multi-scale three-dimensional. BACKGROUND

[0002] Road safety data collection has always been the core content of road safety detection and the most basic content of road traffic safety risk assessment. Therefore, comprehensive and accurate data collection and assessment are needed to accurately detect the road safety situation and effectively assess the road traffic safety risk.

[0003] During the driving of the vehicle on the road, the wheels are in direct contact with the road surface, and the road surface condition directly affects the road traffic safety. Therefore, it is necessary to collect road surface data to detect the road safety situation and assess the road traffic safety risk.

[0004] However, the traditional road safety detection method lacks comprehensiveness and accuracy in collecting road surface data, which greatly affects the subsequent detection of the road safety situation, and thus leads to the lack of effectiveness in assessing the road traffic safety risk based on the detection result of the road safety situation. SUMMARY

[0005] The embodiments of the present application provide a road safety detection method and equipment based on multi-scale three-dimensional to solve the technical problem that the traditional road safety detection method lacks comprehensiveness and accuracy in collecting road surface data, which greatly affects the subsequent detection of the road safety situation, and thus leads to the lack of effectiveness in assessing the road traffic safety risk based on the detection result of the road safety situation.

[0006] In a first aspect, the embodiments of the present application provide a road safety detection method based on multi-scale three-dimensional, comprising: Obtaining vehicle-mounted measurement data of a target road; the vehicle-mounted measurement data includes lane-level road surface three-dimensional data and road surface micro-texture data; Performing attitude compensation on the vehicle-mounted measurement data to obtain reconstructed measurement data; Based on the reconstructed measurement data, obtaining target information of the target road; the target information includes road geometric linear information, road surface height difference mutation information and road surface anti-skid performance information; Based on the target information, obtaining a safety detection result of the target road.

[0007] In one embodiment, the reconstructed measurement data includes lane-level road surface three-dimensional reconstruction data and road surface micro-texture reconstruction data, and the road geometric linear information includes road transverse slope information, road longitudinal slope information and road curvature information. The step of obtaining target information for the target road based on the reconstructed measurement data includes: Based on the cross-sectional data in the lane-level pavement three-dimensional reconstruction data, the road cross slope information is obtained; Based on the longitudinal slope data in the lane-level road surface three-dimensional reconstruction data, the road longitudinal slope information is obtained; Based on the latitude and longitude of the lane-level road surface 3D reconstruction data, the road curvature information is obtained; Based on the elevation difference data in the lane-level road surface three-dimensional reconstruction data, obtain the road surface elevation difference abrupt change information; Based on the reconstruction data of the tire-road contact area in the road surface microtexture reconstruction data, the road surface anti-skid performance information is obtained.

[0008] In one embodiment, obtaining the safety detection result of the target road based on the target information includes: Based on the road cross slope information, the road longitudinal slope information, and the road curvature information, the road geometric hazard parameters of the target road are obtained; Based on the information on abrupt changes in road surface elevation, the road abrupt change hazard parameters of the target road are obtained; Based on the road surface skid resistance information, the road cross slope information, the road longitudinal slope information, and the road curvature information, the road surface skid resistance parameters of the target road are obtained; Based on the road geometric hazard parameters, the road abrupt change hazard parameters, and the pavement anti-skid performance parameters, the safety detection results of the target road are obtained.

[0009] In one embodiment, obtaining the road geometric hazard parameters of the target road based on the road cross slope information, the road longitudinal slope information, and the road curvature information includes: Based on the design speed and road grade of the target road, determine whether the road cross slope information, the road longitudinal slope information, and the road curvature information meet the road design requirements; If all the information is correct, then the road geometric hazard parameter is determined to be 0; If any information is not met, the road geometric hazard parameter is determined to be 1.

[0010] In one embodiment, obtaining the road abrupt change hazard parameters of the target road based on the road surface elevation change information includes: Obtain the mutation type, mutation degree, and mutation location of the elevation change target in the road surface elevation change information; Based on the mutation category, determine the elevation risk threshold of the elevation mutation target; The road mutation hazard parameters are obtained based on the degree of mutation, the location of mutation, and the elevation difference hazard threshold.

[0011] In one embodiment, obtaining the pavement skid resistance parameters of the target road based on the pavement skid resistance performance information, the road cross slope information, the road longitudinal slope information, and the road curvature information includes: Obtain the lateral friction coefficient and longitudinal friction coefficient from the road surface anti-skid performance information; Obtain the cross slope angle from the road cross slope information and the longitudinal slope angle from the road longitudinal slope information; Obtain the curvature value from the road curvature information; Based on the lateral friction coefficient, the longitudinal friction coefficient, the cross slope angle, the longitudinal slope angle, and the curvature value, combined with the design speed of the target road, the anti-skid performance parameters of the road surface are obtained.

[0012] Secondly, embodiments of this application provide a road safety detection equipment based on multi-scale three-dimensional measurement, including: a lane-level three-dimensional measurement sensor, a micro-level three-dimensional measurement sensor, and a main control unit; The main control unit is used for: Acquire vehicle-mounted measurement data of the target road; the vehicle-mounted measurement data includes lane-level three-dimensional road surface data collected by the lane-level three-dimensional measurement sensor and road surface micro-texture data collected by the micro-three-dimensional measurement sensor; The vehicle-mounted measurement data is subjected to attitude compensation to obtain reconstructed measurement data; Based on the reconstructed measurement data, target information of the target road is obtained; the target information includes road geometric linearity information, pavement elevation change information, and pavement skid resistance information. Based on the target information, the safety detection results of the target road are obtained.

[0013] In one embodiment, it further includes: a mobile vehicle and an inertial measurement sensor; The main control unit is also used for: Acquire the attitude information of the mobile vehicle collected by the inertial measurement sensor; Based on the attitude information, attitude compensation is performed on the vehicle-mounted measurement data to obtain reconstructed measurement data; The lane-level three-dimensional measurement sensor, the microscopic three-dimensional measurement sensor, the inertial measurement sensor, and the main control unit are integrated on the mobile vehicle.

[0014] In one embodiment, the lane-level three-dimensional measurement sensor measures at least one complete lane along the width direction of the target road; The sampling interval of the lane-level three-dimensional measurement sensor along the width direction of the target road is less than or equal to 20 mm, and the sampling interval along the extension direction of the target road is less than or equal to 30 mm.

[0015] In one embodiment, the road surface micro-texture data collected by the micro-three-dimensional measurement sensor is the road surface micro-texture data at the wheel tracks of the mobile vehicle; The sampling interval of the microscopic three-dimensional measurement sensor along the width direction of the target road is less than or equal to 0.2 mm, and the sampling interval along the extension direction of the target road is less than or equal to 0.5 mm.

[0016] Thirdly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the multi-scale three-dimensional road safety detection method described in the first aspect.

[0017] Fourthly, embodiments of this application provide a non-transitory computer-readable storage medium, including a computer program, which, when executed by a processor, implements the steps of the multi-scale three-dimensional road safety detection method described in the first aspect.

[0018] The road safety detection method and equipment based on multi-scale three-dimensional measurement provided in this application acquires vehicle-mounted measurement data of the target road, including lane-level three-dimensional road surface data and road surface micro-texture data. The vehicle-mounted measurement data is subjected to attitude compensation to obtain reconstructed measurement data. Based on the reconstructed measurement data, target information of the target road is obtained, including road geometric linear information, road surface elevation change information and road surface anti-skid performance information. Based on the target information, the safety detection result of the target road is obtained. In this application, on the one hand, based on the characteristic of vehicles traveling in fixed lanes, lane-level three-dimensional road surface data is collected. Simultaneously, since lane-level three-dimensional road surface data is relatively granular, finer-grained micro-texture data of the road surface is further collected to achieve comprehensive collection of road surface data at different scales, improving the comprehensiveness of data collection. On the other hand, because the measurement carrier typically has a specific acquisition posture during road surface data collection, leading to certain posture deviations in the collected road surface data, posture compensation is also performed on the collected road surface data to correct these posture deviations, thereby improving the accuracy of road surface data collection. Based on the comprehensive and accurate reconstructed measurement data obtained from the above processing, the target information acquired is also more comprehensive and accurate. Therefore, based on this target information, accurate detection of the target road can be achieved, greatly improving the effectiveness of road traffic safety risk assessment. In summary, this application can improve the comprehensiveness and accuracy of road surface data collection, thereby achieving accurate detection of road safety conditions and improving the effectiveness of assessing road traffic safety risks based on the detection results of road safety conditions. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is one of the flowcharts of the road safety detection method based on multi-scale three-dimensional provided in the embodiments of this application; Figure 2 This is the second flowchart of the road safety detection method based on multi-scale three-dimensional provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the road safety detection equipment based on multi-scale three-dimensional provided in the embodiments of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] It should be noted that in the description of the embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The terms "upper," "lower," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Unless otherwise expressly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly, for example, they can be fixed connections, detachable connections, or integral connections; they can be mechanical connections or electrical connections; they can be direct connections or indirect connections through an intermediate medium; and they can be internal connections between two elements. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0023] The terms "first," "second," etc., used in this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, without limiting the number of objects; for example, a first object can be one or more. Furthermore, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects have an "or" relationship.

[0024] Figure 1 This is one of the flowcharts illustrating the multi-scale three-dimensional road safety detection method provided in this application. (Refer to...) Figure 1 This application provides a road safety detection method based on multi-scale three-dimensional measurement, which may include: Step 101: Obtain vehicle-mounted measurement data for the target road; Onboard measurement data includes lane-level 3D road surface data and road surface microtexture data; Step 102: Perform attitude compensation on the vehicle-mounted measurement data to obtain reconstructed measurement data; Step 103: Based on the reconstructed measurement data, obtain the target information of the target road; The target information includes road geometric linearity information, pavement elevation change information, and pavement skid resistance information; Step 104: Based on the target information, obtain the safety detection results of the target road.

[0025] In step 101, independent acquisition units can be used to acquire lane-level three-dimensional road surface data and road surface micro-texture data separately, or integrated acquisition units can be used to acquire lane-level three-dimensional road surface data and road surface micro-texture data simultaneously; no limitation is made here.

[0026] In step 102, the attitude information of the measurement carrier can be obtained first, and then attitude compensation can be performed on the lane-level road surface three-dimensional data and road surface micro-texture data based on the attitude information.

[0027] In steps 103 to 104, since the reconstructed measurement data is relatively comprehensive and accurate, it is possible to obtain information on dimensions such as geometric features, elevation differences, and anti-skid performance, thereby enabling accurate measurement of road safety from multiple dimensions and effective assessment of road traffic safety risks.

[0028] The multi-scale three-dimensional road safety detection method provided in this embodiment acquires vehicle-mounted measurement data of the target road, including lane-level three-dimensional road surface data and road surface micro-texture data. The vehicle-mounted measurement data is subjected to attitude compensation to obtain reconstructed measurement data. Based on the reconstructed measurement data, the target information of the target road is obtained, including road geometric linear information, road surface elevation change information and road surface anti-skid performance information. Based on the target information, the safety detection result of the target road is obtained. In this embodiment, on the one hand, based on the characteristic of vehicles traveling in fixed lanes, lane-level three-dimensional road surface data is collected. Simultaneously, since lane-level three-dimensional road surface data has a relatively large granularity, finer-grained micro-texture data of the road surface is further collected to achieve comprehensive collection of road surface data at different scales, improving the comprehensiveness of data collection. On the other hand, because the measurement carrier typically has a specific acquisition posture during road surface data collection, which can lead to certain posture deviations in the collected road surface data, posture compensation is also performed on the collected road surface data to correct these posture deviations, thereby improving the accuracy of road surface data collection. Based on the above-processed reconstructed measurement data, which is comprehensive and accurate, the target information obtained is also more comprehensive and accurate. Therefore, based on this target information, accurate detection of the target road can be achieved, greatly improving the effectiveness of road traffic safety risk assessment. In summary, this embodiment can improve the comprehensiveness and accuracy of road surface data collection, thereby achieving accurate detection of road safety conditions and improving the effectiveness of assessing road traffic safety risks based on the detection results of road safety conditions.

[0029] In one embodiment, the reconstructed measurement data includes lane-level pavement 3D reconstruction data and pavement microtexture reconstruction data, and the road geometric linear information includes road cross slope information, road longitudinal slope information, and road curvature information. Step 103 may include: 1. Obtain road cross slope information based on cross section data from lane-level pavement 3D reconstruction data; One can refer to the road cross slope calculation model and obtain road cross slope information based on the cross section data; 2. Obtain road longitudinal slope information based on longitudinal slope data from lane-level 3D road surface reconstruction data; Among them, the road longitudinal slope calculation model can be referenced, and the road longitudinal slope information can be obtained based on the longitudinal slope surface data; 3. Obtain road curvature information based on the latitude and longitude of lane-level road surface 3D reconstruction data; One can refer to the road curvature calculation model and obtain road curvature information based on the latitude and longitude. 4. Obtain information on abrupt changes in road surface elevation based on elevation difference data in lane-level 3D road surface reconstruction data; Among them, elevation difference data can be input into a pre-trained artificial intelligence model to obtain the road surface elevation difference abrupt change information output by the artificial intelligence model; the road surface elevation difference abrupt change information can include information on various abrupt change targets, such as information on road potholes, road bumps, road misalignments, road foreign objects, bridge approach slabs, and road ruts. 5. Based on the reconstruction data of the tire-road contact area in the road surface microtexture reconstruction data, obtain information on the road surface anti-skid performance; One approach is to combine a tire-road contact model to first determine the contact area between the tire and the road surface in the road surface microtexture reconstruction data, then extract the reconstructed road surface data of the contact area, and then refer to the road surface anti-skid performance index calculation model to obtain road surface anti-skid performance information based on the reconstructed road surface data.

[0030] In this embodiment, multiple models are used to adaptively acquire road geometric linear information, pavement elevation change information, and pavement anti-skid performance information, which greatly enriches the types of target information and helps to obtain more accurate road safety detection results.

[0031] Figure 2 This is the second flowchart illustrating the multi-scale three-dimensional road safety detection method provided in this application. (Refer to...) Figure 2 In one embodiment, step 104 may include: Step 201: Based on the road cross slope information, road longitudinal slope information, and road curvature information, obtain the road geometric hazard parameters of the target road; Step 202: Based on the information on abrupt changes in road surface elevation, obtain the road abrupt change hazard parameters for the target road; Step 203: Based on the road surface skid resistance performance information, road cross slope information, road longitudinal slope information, and road curvature information, obtain the road surface skid resistance performance parameters of the target road; Step 204: Based on the road geometric hazard parameters, road abrupt change hazard parameters, and pavement anti-skid performance parameters, obtain the safety inspection results of the target road.

[0032] Step 201 may specifically include: Step 201a: Based on the design speed and road grade of the target road, determine whether the road cross slope information, road longitudinal slope information and road curvature information meet the road design requirements; Step 201b: If all information is met, then the road geometric hazard parameter is determined to be 0; Step 201c: If any information is not met, then the road geometric hazard parameter is determined to be 1.

[0033] In step 201a, for each road, the road design requirements will limit the road cross slope, road longitudinal slope and road curvature based on the road design speed and road grade. Therefore, based on the design speed and road grade of the target road, the corresponding road design requirements can be obtained, and the information such as the road cross slope, road longitudinal slope and road curvature of the target road can be evaluated to see if they meet the requirements of the road design requirements. In steps 201b to 201c, if all information is consistent, it indicates that the overall road geometric linearity information is within the safe range and the road geometric hazard is low. Therefore, the road geometric hazard parameter can be determined to be 0. If any information is inconsistent, it indicates that the road geometric linearity information exceeds the safe range and the road geometric hazard is high. Therefore, the road geometric hazard parameter can be determined to be 1.

[0034] Step 202 may specifically include: Step 202a: Obtain the mutation type, mutation degree, and mutation location of the elevation change target in the road surface elevation change information; Step 202b: Based on the mutation category, determine the elevation risk threshold of the elevation mutation target; Step 202c: Based on the degree of mutation, the location of mutation, and the elevation difference hazard threshold, obtain the road mutation hazard parameters.

[0035] In step 202a, the mutation type, mutation degree, and mutation location of road potholes, road bumps, road misalignments, road foreign objects, bridge approach slabs, and road ruts are obtained.

[0036] In step 202b, the elevation difference hazard threshold is different for each type of mutation target. That is, the elevation difference hazard thresholds for road potholes, road bumps, road misalignments, road debris, bridge approach slabs, and road ruts are all different and need to be determined separately. Furthermore, the elevation difference hazard threshold can be a hazard threshold set for the degree of mutation of a specific type of mutation target.

[0037] In step 202c, for each type of mutation target, the deviation between its mutation degree and the elevation difference hazard threshold, and the deviation between its mutation location and the wheel track location are compared. These two deviations are then combined to assess the mutation hazard posed by each type of mutation target to the target road. Finally, the mutation hazards posed by all types of mutation targets to the target road are combined to assess the overall mutation hazard posed to the target road, thus obtaining the road mutation hazard parameters.

[0038] Step 203 may specifically include: Step 203a: Obtain the transverse friction coefficient and longitudinal friction coefficient from the road surface anti-skid performance information; Step 203b: Obtain the cross slope angle from the road cross slope information and the longitudinal slope angle from the road longitudinal slope information; Step 203c: Obtain the curvature value from the road curvature information; Step 203d: Based on the lateral friction coefficient, longitudinal friction coefficient, cross slope angle, longitudinal slope angle and curvature value, and combined with the design speed of the target road, the anti-skid performance parameters of the road surface are obtained.

[0039] The anti-skid performance parameters of the road surface can be calculated based on the following formula. : ; in, The coefficient of lateral friction is... For the transverse slope angle, The longitudinal friction coefficient is... The longitudinal slope angle, The curvature value, The preset reference curvature value, To design vehicle speed, The preset benchmark design speed.

[0040] in: In calculation At this time, because the larger the cross slope angle, the higher the requirement for the lateral friction coefficient, specifically, the cross slope angle will cause gravity to be decomposed into a component perpendicular to the cross slope road surface and a component parallel to the cross slope road surface. This reduces the normal force of gravity on the road surface and introduces a lateral sliding component, resulting in the need for additional lateral anti-skid compensation. Among these, the normal force influence factor is... Characterization, the lateral anti-skid compensation factor is 1- Therefore, in the calculation of lateral skid resistance, the lateral friction coefficient is used as the basis, and then multiplied by the normal pressure influence factor and the lateral skid resistance compensation factor to obtain the accurate lateral friction coefficient under the influence of the cross slope. Similarly, since the larger the longitudinal slope angle, the higher the requirement for the longitudinal friction coefficient, specifically, the longitudinal slope angle will cause gravity to be decomposed into a component perpendicular to the longitudinal slope road surface and a component parallel to the longitudinal slope road surface. This reduces the normal pressure of gravity on the road surface, and there is a longitudinal sliding component, resulting in the need for additional longitudinal skid resistance compensation. Among these, the normal pressure influence factor... Characterization, the longitudinal anti-skid compensation factor is 1- Therefore, in the calculation of longitudinal skid resistance performance, the longitudinal friction coefficient is used as the basis, and then multiplied by the normal pressure influence factor and the longitudinal skid resistance compensation factor to obtain the accurate longitudinal friction coefficient under the influence of longitudinal slope. Furthermore, the smaller value is selected from the converted transverse friction coefficient and the converted longitudinal friction coefficient as the index value for calculating the road surface skid resistance performance parameters, so that the road surface skid resistance performance parameters can characterize the skid resistance performance state during vehicle sideslip and rear-end collision accidents, and improve the accuracy of subsequent road safety inspection results. In calculation When the actual curvature value exceeds the preset reference curvature value, the ratio of the preset reference curvature value to the actual curvature value is taken as the index value for calculating the road surface anti-skid performance parameter. When the actual curvature value does not exceed the preset reference curvature value, 1 is taken as the index value for calculating the road surface anti-skid performance parameter. That is, when the actual curvature value exceeds the preset reference curvature value, the greater the exceedance, the smaller the road surface anti-skid performance parameter, which is consistent with the practical experience that "the larger the curvature value, the greater the demand for tire adhesion when the vehicle is driving, the higher the risk of sideslip, and the faster the road surface anti-skid performance decays." When the actual curvature value does not exceed the preset reference curvature value, it is considered that the actual curvature value has little impact on the road surface anti-skid performance, and 1 is taken so that it will not affect the calculation of the road surface anti-skid performance parameter. In calculation When the actual design speed exceeds the preset benchmark design speed, the ratio of the preset benchmark design speed to the actual design speed is taken as the index value for calculating the road surface anti-skid performance parameters. When the actual design speed does not exceed the preset benchmark design speed, 1 is taken as the index value for calculating the road surface anti-skid performance parameters. That is, when the actual design speed exceeds the preset benchmark design speed, the greater the exceedance, the higher the requirements for the road surface anti-skid performance parameters. This is consistent with the practical experience that "the higher the design speed, the higher the vehicle speed, the smaller the safety margin of the road surface anti-skid performance, and the faster the road surface anti-skid performance deteriorates." When the actual design speed does not exceed the preset benchmark design speed, it is considered that the actual design speed will not increase the requirements for the road surface anti-skid performance, and 1 is taken so that it will not affect the calculation of the road surface anti-skid performance parameters, that is, it will not affect the evaluation result of whether the road surface anti-skid performance meets the standards.

[0041] In step 204, the safety status parameters of the target road can be calculated based on the following formula. This will be used as the result of the safety inspection. ; in, For road geometric hazard parameters, For road sudden change hazard parameters, and For the corresponding weights, and .

[0042] Since road geometry is the foundation of a road and the basic determinant of road safety, and road abrupt changes and anti-skid performance are both linearly related to road geometry, they are evaluation indicators that extend from road geometry. For example, in areas where the geometry is designed for curves, the requirements for anti-skid performance are also higher. Therefore, the above formula takes the weighted sum of the road geometry hazard parameters with the road abrupt change hazard parameters and the pavement anti-skid performance parameters, and takes the larger value. Based on the linear correlation between road abrupt changes and anti-skid performance and road geometry, it determines whether road abrupt changes or anti-skid performance has a greater impact on road safety based on road geometry. Then, the weighted value of the indicator with the greater impact is selected as the final safety status parameter, i.e., the safety test result.

[0043] This embodiment determines road geometric hazard parameters by comparing whether road cross slope information, road longitudinal slope information, and road curvature information meet road design requirements. It determines elevation difference hazard thresholds for different abrupt change categories and, based on the deviation between the degree of abrupt change and the elevation difference hazard threshold, as well as the deviation between the abrupt change location and the wheel track location, determines road abrupt change hazard parameters. Using the normal pressure influence factor and the transverse and longitudinal anti-skid compensation factors, it obtains the friction coefficient under the influence of transverse and longitudinal slopes. Combining the deviation between the actual curvature value and the preset benchmark curvature value, and the deviation between the actual design speed and the preset benchmark design speed, it determines pavement anti-skid performance parameters. Finally, based on the linear correlation between road geometric design, road abrupt changes, and anti-skid performance, it calculates the weighted values ​​of road geometric hazard parameters and road abrupt change hazard parameters, as well as the weighted values ​​of road geometric hazard parameters and pavement anti-skid performance parameters, selecting the larger value as the final safety detection result, thus achieving comprehensive and accurate detection of road safety.

[0044] Figure 3 This is a schematic diagram of the structure of a multi-scale three-dimensional road safety detection equipment provided in an embodiment of this application. (Refer to...) Figure 3 This application provides a road safety detection equipment based on multi-scale three-dimensional measurement, which may include: lane-level three-dimensional measurement sensor, micro-level three-dimensional measurement sensor and main control unit; The main control unit is used for: Acquire vehicle-mounted measurement data for the target road; the vehicle-mounted measurement data includes lane-level 3D road surface data collected by lane-level 3D measurement sensors and road surface micro-texture data collected by micro-3D measurement sensors; Attitude compensation is performed on the vehicle-mounted measurement data to obtain reconstructed measurement data; Based on the reconstructed measurement data, target information of the target road is obtained; the target information includes road geometric linearity information, pavement elevation change information, and pavement skid resistance information. Based on the target information, the safety detection results of the target road are obtained.

[0045] Furthermore, the road safety detection equipment may also include: a mobile vehicle and an inertial measurement sensor; The main control unit is also used for: Acquire the attitude information of the moving vehicle collected by the inertial measurement sensor; Based on attitude information, attitude compensation is performed on the vehicle-mounted measurement data to obtain reconstructed measurement data; Lane-level 3D measurement sensors, micro-level 3D measurement sensors, inertial measurement sensors, and the main control unit are integrated on the mobile vehicle.

[0046] Furthermore, a mobile vehicle can be used as a measurement carrier to build a mobile measurement platform, integrating lane-level three-dimensional measurement sensors, microscopic three-dimensional measurement sensors, inertial measurement sensors, and a main control unit into the mobile measurement platform; Furthermore, the mobile measurement platform may also include a positioning unit, a synchronization control unit, a power supply unit, and a communication unit, which are integrated on the mobile vehicle. in: The positioning unit includes photoelectric encoders mounted on the wheels of the mobile vehicle and GNSS receivers mounted on the roof of the mobile vehicle. The photoelectric encoders are used to collect the detection mileage information of the mobile vehicle, and the GNSS receivers are used to collect the GNSS signals of the mobile vehicle. The synchronization control unit is used to provide measurement time and space references for lane-level three-dimensional measurement sensors, micro three-dimensional measurement sensors and inertial measurement sensors based on the detected mileage information and GNSS signals, and to control the lane-level three-dimensional measurement sensors, micro three-dimensional measurement sensors and inertial measurement sensors to synchronously collect data at preset time intervals or distance intervals; The power supply unit is used to supply power to the other units. The communication unit is used for communication between the road safety detection equipment and the road safety management platform. For example, the road safety management platform sends detection tasks to the road safety detection equipment, and the road safety detection equipment sends detection result data to the road safety management platform.

[0047] Furthermore, industrial cameras can be added to road safety inspection equipment to collect color images along the road, which can be used for data verification of dangerous areas on the road. Furthermore, road structure safety detection equipment, such as three-dimensional ground-penetrating radar, can be added to road safety detection equipment to detect the safety of underground road structures.

[0048] Furthermore, it is also possible to base it on calculated road safety condition parameters. The safety level of roads is classified to conduct a qualitative analysis of road safety.

[0049] The multi-scale three-dimensional road safety detection equipment provided in this embodiment acquires vehicle-mounted measurement data of the target road. The vehicle-mounted measurement data includes lane-level three-dimensional road surface data and road surface micro-texture data. The vehicle-mounted measurement data is subjected to attitude compensation to obtain reconstructed measurement data. Based on the reconstructed measurement data, the target information of the target road is obtained. The target information includes road geometric linear information, road surface elevation change information, and road surface anti-skid performance information. Based on the target information, the safety detection result of the target road is obtained. In this embodiment, on the one hand, based on the characteristic of vehicles traveling in fixed lanes, lane-level three-dimensional road surface data is collected. Simultaneously, since lane-level three-dimensional road surface data has a relatively large granularity, finer-grained micro-texture data of the road surface is further collected to achieve comprehensive collection of road surface data at different scales, improving the comprehensiveness of data collection. On the other hand, because the measurement carrier typically has a specific acquisition posture during road surface data collection, which can lead to certain posture deviations in the collected road surface data, posture compensation is also performed on the collected road surface data to correct these posture deviations, thereby improving the accuracy of road surface data collection. Based on the above-processed reconstructed measurement data, which is comprehensive and accurate, the target information obtained is also more comprehensive and accurate. Therefore, based on this target information, accurate detection of the target road can be achieved, greatly improving the effectiveness of road traffic safety risk assessment. In summary, this embodiment can improve the comprehensiveness and accuracy of road surface data collection, thereby achieving accurate detection of road safety conditions and improving the effectiveness of assessing road traffic safety risks based on the detection results of road safety conditions.

[0050] Furthermore, various functional units and testing equipment can be integrated into the equipment to achieve integrated testing of road safety and cross-utilization of testing data, which is also conducive to centralized maintenance and reduces maintenance costs.

[0051] Reference Figure 3 In one embodiment, the lane-level three-dimensional measurement sensor includes at least one of LiDAR and line-scan three-dimensional measurement sensor, and the micro-level three-dimensional measurement sensor may include a line-scan three-dimensional measurement sensor. The lane-level 3D measurement sensor covers at least one complete lane in the width direction of the target road. The sampling interval of the lane-level three-dimensional measurement sensor along the width direction of the target road is less than or equal to 20 mm, and the sampling interval along the extension direction of the target road is less than or equal to 30 mm. Furthermore, lane-level three-dimensional road surface data can cover not only the lane in which the measurement vehicle travels, but also the entire road surface.

[0052] The microscopic texture data of the road surface collected by the microscopic three-dimensional measurement sensor is the microscopic texture data of the road surface at the wheel tracks of the moving vehicle; The sampling interval of the microscopic three-dimensional measurement sensor along the width direction of the target road is less than or equal to 0.2 mm, and along the extension direction of the target road is less than or equal to 0.5 mm.

[0053] In this embodiment, the lane-level three-dimensional measurement sensor can uniformly sample data of the entire lane along the width of the target road, and the micro-level three-dimensional measurement sensor can uniformly collect data at the wheel tracks of the moving vehicle along the width of the target road, thereby achieving comprehensive collection of road surface data at different scales, improving the comprehensiveness of data collection, and helping to achieve accurate detection of road safety conditions.

[0054] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of the multi-scale three-dimensional road safety detection method provided in the above embodiments, such as including: Acquire vehicle-mounted measurement data of the target road; the vehicle-mounted measurement data includes lane-level three-dimensional road surface data and road surface micro-texture data; The vehicle-mounted measurement data is subjected to attitude compensation to obtain reconstructed measurement data; Based on the reconstructed measurement data, target information of the target road is obtained; the target information includes road geometric linearity information, pavement elevation change information, and pavement skid resistance information. Based on the target information, the safety detection results of the target road are obtained.

[0055] On the other hand, embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program thereon, the computer program being used to cause a processor to execute the steps of the multi-scale three-dimensional road safety detection method provided in the above embodiments, for example including: Acquire vehicle-mounted measurement data of the target road; the vehicle-mounted measurement data includes lane-level three-dimensional road surface data and road surface micro-texture data; The vehicle-mounted measurement data is subjected to attitude compensation to obtain reconstructed measurement data; Based on the reconstructed measurement data, target information of the target road is obtained; the target information includes road geometric linearity information, pavement elevation change information, and pavement skid resistance information. Based on the target information, the safety detection results of the target road are obtained.

[0056] The non-transitory computer-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0057] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments 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 this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A multi-scale three-dimensional based road safety detection method, characterized in that, The method comprises the following steps: acquiring vehicle-mounted measurement data of a target road; the vehicle-mounted measurement data comprises lane-level road surface three-dimensional data and road surface micro-texture data; performing attitude compensation on the vehicle-mounted measurement data to obtain reconstructed measurement data; acquiring target information of the target road based on the reconstructed measurement data; the target information comprises road geometric linearity information, road surface elevation difference mutation information, and road surface anti-skid performance information; obtaining a safety detection result of the target road based on the target information.

2. The multi-scale three-dimensional based road safety detection method of claim 1, wherein, the reconstructed measurement data comprises lane-level road surface three-dimensional reconstruction data and road surface micro-texture reconstruction data, and the road geometric linearity information comprises road transverse slope information, road longitudinal slope information, and road curvature information; the step of acquiring the target information of the target road based on the reconstructed measurement data comprises: acquiring the road transverse slope information based on cross-section data in the lane-level road surface three-dimensional reconstruction data; acquiring the road longitudinal slope information based on longitudinal slope surface data in the lane-level road surface three-dimensional reconstruction data; acquiring the road curvature information based on latitude and longitude of the lane-level road surface three-dimensional reconstruction data; acquiring the road surface elevation difference mutation information based on elevation difference data in the lane-level road surface three-dimensional reconstruction data; acquiring the road surface anti-skid performance information based on reconstruction data of a tire and road surface contact area in the road surface micro-texture reconstruction data.

3. The multi-scale three-dimensional based road safety detection method of claim 2, wherein, the step of obtaining a safety detection result of the target road based on the target information comprises: obtaining road geometric danger parameters of the target road based on the road transverse slope information, the road longitudinal slope information, and the road curvature information; obtaining road mutation danger parameters of the target road based on the road surface elevation difference mutation information; obtaining road surface anti-skid performance parameters of the target road based on the road surface anti-skid performance information, the road transverse slope information, the road longitudinal slope information, and the road curvature information; obtaining a safety detection result of the target road based on the road geometric danger parameters, the road mutation danger parameters, and the road surface anti-skid performance parameters.

4. The multi-scale three-dimensional based road safety detection method of claim 3, wherein, the step of obtaining road geometric danger parameters of the target road based on the road transverse slope information, the road longitudinal slope information, and the road curvature information comprises: determining whether the road transverse slope information, the road longitudinal slope information, and the road curvature information meet road design requirements based on a design vehicle speed and a road grade of the target road; if all the information meets the requirements, determining that the road geometric danger parameters are 0; if any information does not meet the requirements, determining that the road geometric danger parameters are 1.

5. The multi-scale three-dimensional based road safety detection method of claim 3, wherein, the step of obtaining road mutation danger parameters of the target road based on the road surface elevation difference mutation information comprises: acquiring a mutation category, a mutation degree, and a mutation position of an elevation difference mutation target in the road surface elevation difference mutation information; determining an elevation difference danger threshold of the elevation difference mutation target based on the mutation category; obtaining the road mutation danger parameters based on the mutation degree, the mutation position, and the elevation difference danger threshold.

6. The multi-scale three-dimensional based road safety detection method of claim 3, wherein, The road surface anti-skid performance parameter of the target road is obtained based on the road surface anti-skid performance information, the road cross slope information, the road longitudinal slope information, and the road curvature information, including: Obtaining the lateral friction coefficient and the longitudinal friction coefficient in the road surface anti-skid performance information; Obtaining the cross slope angle in the road cross slope information and the longitudinal slope angle in the road longitudinal slope information; Obtaining the curvature value in the road curvature information; Obtaining the road surface anti-skid performance parameter based on the lateral friction coefficient, the longitudinal friction coefficient, the cross slope angle, the longitudinal slope angle, and the curvature value, in combination with the design speed of the target road.

7. A multi-scale three-dimensional based road safety detection apparatus, characterized by, Including: a lane-level three-dimensional measurement sensor, a micro three-dimensional measurement sensor, and a master control unit; The master control unit is configured to: acquire vehicle-mounted measurement data of a target road; the vehicle-mounted measurement data includes lane-level road surface three-dimensional data collected by the lane-level three-dimensional measurement sensor and road surface micro texture data collected by the micro three-dimensional measurement sensor; perform attitude compensation on the vehicle-mounted measurement data to obtain reconstructed measurement data; acquire target information of the target road based on the reconstructed measurement data; the target information includes road geometric linear information, road surface elevation difference mutation information, and road surface anti-skid performance information; obtain a safety detection result of the target road based on the target information.

8. The multi-scale three-dimensional based road safety detection apparatus of claim 7, wherein, Further including: a mobile vehicle and an inertial measurement sensor; The master control unit is further configured to: acquire attitude information of the mobile vehicle collected by the inertial measurement sensor; perform attitude compensation on the vehicle-mounted measurement data based on the attitude information to obtain reconstructed measurement data; The lane-level three-dimensional measurement sensor, the micro three-dimensional measurement sensor, the inertial measurement sensor, and the master control unit are integrated on the mobile vehicle.

9. The multi-scale three-dimensional based road safety detection equipment according to claim 7, wherein: The measurement width of the lane-level three-dimensional measurement sensor along the width direction of the target road covers at least one complete lane; The sampling interval of the lane-level three-dimensional measurement sensor along the width direction of the target road is less than or equal to 20 mm, and the sampling interval along the extension direction of the target road is less than or equal to 30 mm.

10. The multi-scale three-dimensional based road safety detection equipment according to claim 8, wherein: The road surface micro texture data collected by the micro three-dimensional measurement sensor is road surface micro texture data at the track of the mobile vehicle; The sampling interval of the micro three-dimensional measurement sensor along the width direction of the target road is less than or equal to 0.2 mm, and the sampling interval along the extension direction of the target road is less than or equal to 0.5 mm.

11. A computer program product comprising a computer program, characterized in that, The computer program is executed by a processor to implement the steps of the multi-scale three-dimensional based road safety detection method of any one of claims 1 to 6.

12. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by a processor to implement the steps of the multi-scale three-dimensional based road safety detection method of any one of claims 1 to 6.

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