Assessment of Transverse Pavement Texture Homogeneity Under Service-Stage Tire-Induced Uneven Wear Using 3D Laser Scanning

Pavement texture strongly affects skid resistance, drainage, and tire–pavement contact stability, yet its transverse evolution under wheel-track-concentrated loading remains insufficiently quantified. This study proposes a 3D-laser-scanning-based framework for evaluating the transverse homogeneity of preventive maintenance pavements during service. Ten field sections on the Jiangluo Expressway in Guangdong Province, China, covering five preventive maintenance surface systems at two service stages (six months and one year), were investigated. Reflection intensity histogram features and geometric texture parameters were screened against transverse wheel-track distribution to identify representative indicators of asphalt film peeling and aggregate wear. Weighted average grayscale was selected as the optical indicator, whereas height-distribution kurtosis was selected as the geometric indicator. A section-level homogeneity index based on normalized median absolute deviation was then used to quantify transverse dispersion. The results show that weighted average grayscale and kurtosis are the most sensitive of the tested indicators to transverse wheel-track distribution, with R2=0.973 and R=0.9057, respectively. Wheel-track regions generally exhibited more severe optical and geometric deterioration than non-wheel-track regions, and transverse homogeneity tended to decrease from six months to one year. Within the investigated expressway sections, the framework was sensitive to different degrees of service-stage transverse wear evolution; however, broader multi-site validation is still required before threshold-based general applications can be established.