Analysis of Skid Resistance Performance of Asphalt Pavement Based on the 3D Surface Topography Features
Year: 2026
Type: article
Abstract: Skid resistance is a critical functional property of asphalt pavements and is strongly influenced by surface topography. However, existing studies often rely on limited texture indicators, making it difficult to comprehensively characterize pavement surface morphology and directly relate it to braking performance. In this study, the surface topography of eight asphalt mixtures, including six porous asphalt concrete (PAC-13) mixtures with different air-void contents, one stone mastic asphalt (SMA-13) mixture, and one asphalt concrete (AC-13) mixture, was characterized using a high-precision three-dimensional laser scanner. The acquired point-cloud data were analyzed using one-dimensional, two-dimensional, three-dimensional, and ISO 25178 surface parameters. Correlation analysis was first used to remove redundant indicators, and principal component analysis was then performed to reduce dimensionality. Three principal components explaining 67.45%, 9.94%, and 6.42% of the total variance, respectively, were extracted and combined into a comprehensive surface topography index (F). The results showed that F effectively distinguished different mixture types and PAC surfaces with different air-void levels. Field validation was further conducted on PAC, SMA, and AC pavements in Xi’an, China, and a regression model relating F to the braking distance from 60 km/h to 0 km/h (D60) was established, with an R2 of 0.8864. The proposed index provides a multidimensional and practical approach for asphalt pavement surface characterization and offers a useful basis for skid-resistance evaluation and braking distance prediction.
Source: Applied Sciences
DOI: 10.3390/app16094473
Authors: Zhufa Chu, Guoquan Wang, Chuan He, Wanli Ye, Nianwen Yao
Institutions: Chang'an University, Harbin Institute of Technology
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7160206153
