应用数学和力学2024，Vol.45Issue(4)：443-457,15.DOI:10.21656/1000-0887.440244
基于复合分形的路面抗滑随机森林评估模型
A Random Forest Evaluation Model for Pavement Skid Resistance Based on Comprehensive Fractal
摘要
Abstract
The pavement anti-skid performance directly affects road traffic safety,and the evaluation methods based on pavement texture features currently have problems of poor interpretability and low accuracy.Herein,185 sets of pavement texture data were collected by the portable 3D laser surface analyzer with an accuracy of 0.05 mm.The pavement friction data in the speed range of 0～80 km/h of the corresponding road section were obtained with the dynamic friction coefficient tester.The comprehensive fractal dimension index representing the complexity of the pavement texture space,the cross section,and the depth direction was constructed,and the random forest evaluation model for pavement skid resistance performances at speeds of 10 km/h and 70 km/h.The results show that,the comprehensive fractal dimension has the ability to describe the complexity of texture independently,but there is no linear relationship between it and the pavement dynamic friction coeffi-cient;the prediction accuracy of comprehensive fractal dimensions for dynamic friction coefficients at the 70 km/h speed is 0.78,which can be used to evaluate the skid resistance of pavement under the condition of rapid sliding of tire rubber;the spatial,cross-sectional,surface,shallow,and deep profile fractal features in com-prehensive fractal indicators jointly affect the pavement anti-skid performances.In the evaluation of pavement texture morphology,comprehensive analysis of texture features should be conducted from multiple spatial per-spectives.关键词
道路工程/路面纹理/抗滑性能/分形维数/随机森林Key words
road engineering/pavement texture/skid resistance/fractal dimension number/random forest分类
交通运输引用本文复制引用
彭毅,张政奇,李强,杨广伟..基于复合分形的路面抗滑随机森林评估模型[J].应用数学和力学,2024,45(4):443-457,15.基金项目
国家自然科学基金青年科学基金(52208425) （52208425）
重庆市博士后自然科学基金(cstc2021jcyj-bshX0113) （cstc2021jcyj-bshX0113）
中国博士后面上项目地区基金(2021M693918) （2021M693918）
