基于近景摄影测量技术的沥青路面纹理实时识别系统

Real-time identification system of asphalt pavement texture based on close-range photogrammetry

为了实时获取沥青路面纹理信息并准确监测服役道路路面的抗滑性能,基于环形三相机近景摄影测量(CRP)技术提出并创建了一个获取沥青路面纹理信息的自动化近景摄影测量(ACRP)系统,实现了沥青路面表面纹理图像自动化采集及三维重建过程.首先对采集的路表纹理图像进行数值化处理;其次,在基于MATLAB与Python联合编程的三维重建模块中重建具有表面纹理的沥青路面三维模型,并提取沥青路面表面高程数据;最后,在三维重建模块中进行路表纹理指标参数的运算,并采用铺砂法、激光扫描法进行沥青路面纹理现场对比试验.结果表明,以平均构造深度与均方根粗糙度(RMSR)为路表纹理统计指标,ACRP系统获得的纹理信息具有较高的准确性与高效性,识别精度接近于0.02mm.ACRP系统提高了传统近景摄影测量的工作效率和精度,可为后续无人驾驶车辆安全制动提供实时、有效的路表抗滑信息.

To obtain the asphalt pavement texture information in real time and monitor the anti-skid performance of the road pavement accurately, an automatic close-range photogrammetry system (ACRP system) was proposed and built based on the three circle-arranged camera close-range photogrammetry (CRP) technology. The automatic image acquisition and the three-dimensional(3D) reconstruction were completed using the ACRP system. Firstly, the collected pavement texture images were digitized. Secondly, a 3D model of asphalt pavement with surface texture was established in the 3D reconstruction software module based on MATLAB and Python joint programming. The surface elevation data of asphalt pavement were extracted. Finally, index parameters of the pavement surface texture were calculated in 3D reconstruction software. The sand patch and the laser scanning (ZGScan) were chosen to collect the on-site asphalt pavement texture for comparison. The mean texture depth (MTD) and the root-mean-square roughness (RMSR) were chosen as the statistical indicators of the pavement surface texture. The results show that the texture data obtained by ACRP system have relatively high accuracy and efficiency. The recognition accuracy of the ACRP system is close to 0.02 mm, providing real-time and effective anti-skid pavement surface information for subsequent safety braking of autonomous vehicles.