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

Abstract

In order to obtain the asphalt pavement texture information in real time and accurately monitor the anti-skid performance of the road pavement, an automatic close-range photogrammetry system (ACRP System) was proposed and established based on the three cameras close-range photogrammetry (CRP) technology. Automatic image acquisition and 3D reconstruction were achieved by 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, then the surface elevation data of asphalt pavement were extracted. Finally, the calculation of the road surface texture index parameters were performed in 3D reconstruction software module. Sand patch testing method and laser scanning method (ZGScan) were used to collect the on-site data as comparison test of the asphalt pavement texture. The mean texture depth (MTD) and the root mean square roughness (RMSR) were chosen as the statistical indicators of pavement surface texture. The results show that the texture data obtained by the ACRP system has relatively higher accuracy and efficiency, and the recognition accuracy is close to 0.02 mm. The ACRP system improves the efficiency and accuracy of traditional close-range photogrammetry and provides real-time and effective road surface anti-skid information for subsequent safety braking of autonomous vehicle.