A Review of Long-Term Skid Resistance of Asphalt Pavement

被引:0
|
作者
Chen, Yuanfeng [1 ,2 ,3 ]
Li, Zhitang [4 ]
Wang, Yuankuo [4 ]
Liang, Guoxi [4 ]
Yang, Xiaolong [1 ,2 ,3 ]
机构
[1] Guangxi Univ, Coll Civil Engn & Architecture, Nanning 530004, Peoples R China
[2] Guangxi Univ, Key Lab Engn Disaster Prevent & Struct Safety, Minist Educ, Nanning 530004, Peoples R China
[3] Guangxi Engn Technol Res Ctr Special Geol Highway, Nanning 530004, Peoples R China
[4] Poly Changda Engn Co Ltd, Guangzhou 510000, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2025年 / 15卷 / 04期
关键词
asphalt pavement; skid resistance; influence factors; evaluation index; prediction models; POLISHING BEHAVIOR; AGGREGATE; PREDICTION; ALGORITHM; ROUGHNESS; TEXTURE; MODEL; FINE;
D O I
10.3390/app15041895
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页数:35
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