A Review of Long-Term Skid Resistance of Asphalt Pavement

• Published in: Applied sciences Vol. 15; no. 4; p. 1895
• Main Authors: Chen, Yuanfeng, Li, Zhitang, Wang, Yuankuo, Liang, Guoxi, Yang, Xiaolong
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2025
• Subjects: Accuracy; Algorithms; Analysis; asphalt pavement; Asphalt pavements; Automation; evaluation index; influence factors; Lighting; Methods; Morphology; Photogrammetry; prediction models; Roads & highways; Sensors; skid resistance; Software; Vehicles; Wavelet transforms; China
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app15041895

This study aims to gain an in-depth understanding of the research trends in the field of the long-term skid resistance (L-TSR) of asphalt pavement (AP). In this paper, the detection method, decay model, influence factors, and prediction model of the L-TSR of AP are summarized. This paper quantitatively analyzes the skid resistance mechanism of the pavement and elucidates the existing problems and future development directions of the L-TSR of AP. The research indicates that digital image methods and intelligent sensor detection methods are important methods for the skid resistance detection of AP in the future. The indoor test can provide detailed data of material properties and can effectively evaluate the performance of anti-sliding materials under different environmental conditions by simulating the actual road conditions. A quantitative analysis of the skid mechanism of AP can better reflect the actual contact characteristics of the pavement. The combined prediction model combining multiple single models can not only correct the shortcomings of a single model but also greatly improve the calculation accuracy. At present, the research on the L-TSR of AP is insufficient in the aspects of the tire–pavement interaction mechanism, evaluation index, decay model, and combined prediction model, which needs to be further studied from quantitative, time-varying, unified, and innovative aspects.