Differences Evaluation of Pavement Roughness Distribution Based on Light Detection and Ranging Data

Pavement roughness serves as a crucial indicator for evaluating road performance. However, traditional measurement methods, such laser detection vehicles, are limited to providing values single profile, failing capture the overall pavement condition comprehensively. To address this limitation, study utilized high-precision light and ranging technology (LiDAR) acquire three-dimensional point cloud data 25 km section in Shanghai. Road elevations were extracted from different lateral survey lines. Subsequently, variance analysis Kruskal–Wallis non-parametric test conducted evaluate differences distribution longitudinal variability of roughness. The findings revealed significant international index (IRI) among lines within section. Moreover, observed variations influenced by characteristics itself. Roads exhibiting discrete patterns displayed higher likelihood disparities. Additionally, it was discovered that discrepancy between length actual introduced volatility repeated results, necessitating limitation 30 m. Consequently, has been recommended consider regulate performance evaluations enhance reliability facilitate more accurate maintenance decision making. highlights importance incorporating comprehensive assessment approaches management practices.