Abstract
Laser scanning technology has been increasingly utilised for the detection of pavement three-dimensional (3D) surface texture. This paper aims to develop a 3D laser scanning system and corresponding methods for the precise extraction and evaluation of the mean texture depth (MTD). The contributions are as follows: 1) an improved Steger method is developed to extract the centreline of the laser stripe; 2) 3D point cloud data of the pavement surface are processed using the coordinate transformation and cubic spline interpolation; 3) Monte Carlo expectation method is employed to evaluate pavement MTD, and an appropriate subblock size is obtained based on the optimal reference surface. Based on the sand-patch testing with 35 testing samples, the mean absolute error and Pearson correlation coefficient are 0.017 mm and 0.9864, respectively, indicating the accuracy of the proposed methods for MTD evaluation. Thus, the proposed methods provide a reference for autonomous detection of pavement performance.
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