•  
  •  
 

Abstract

Rutting damage on the road surface seriously affects driving safety, often causes traffic accidents, and results in significant economic losses. In order to explore the texture characteristics of the rutting surface, this paper designed an experiment to simulate the formation process of rutting. It used a depth camera based on a 3D laser to collect point cloud data of rutting and non-rutting and calculated the surface texture feature parameters of rutting. It selected the mean profile depth (MPD), functional parameters, and volume parameters. After the analysis of the calculation results, the MPD values with rutting, the height Svk of the protruding valley, and the void volume Vvv of the valley were all smaller than those of the non-rutting. By using these three parameters to establish the rutting judgment prediction model of SVM, the judgment accuracy rate was 91.7%.

Publication Date

6-18-2022

DOI

10.14048/j.issn.1671-2579.2022.03.009

First Page

48

Last Page

51

Submission Date

May 2025

Reference

[1] 李清泉, 雷波, 毛庆洲, 等. 利用激光三角法进行快速车辙检测[J]. 武汉大学学报(信息科学版), 2010, 35(3): 302-307. LI Qingquan, LEI Bo, MAO Qingzhou, et al. A fast method for pavement ruts measuring with laser triangulation[J]. Geomatics and Information Science of Wuhan University, 2010, 35(3): 302-307. [2] 汪恩军, 陈先桥, 初秀民, 等. 车辙检测中超声测距数据采集方法[J]. 武汉理工大学学报, 2008, 30(1): 138-141. WANG Enjun, CHEN Xianqiao, CHU Xiumin, et al. Data acquisition method by ultrasonic wave distance measurement for rut detection[J]. Journal of Wuhan University of Technology, 2008, 30(1): 138-141. [4] 李甜甜. 基于三维线激光技术的路面车辙检测技术研究[D]. 西安: 长安大学, 2016. LI Tiantian. Research on pavement rutting detection technology based on 3D line laser technology[D]. Xi’an: Changan University, 2016. [5] 司永伟. 集成式多点激光路面车辙检测技术研究[D]. 西安: 长安大学, 2018. SI Yongwei. Research on integrated multi-point laser pavement rutting detection technology[D]. Xi’an: Changan University, 2018. [6] 李莉, 孙立军, 谭生光, 等. 用于路面车辙检测的线结构光图像处理流程[J]. 同济大学学报(自然科学版), 2013, 41(5): 710-715. LI Li, SUN Lijun, TAN Shengguang, et al. Line-structured light image processing procedure for pavement rut detection[J]. Journal of Tongji University (Natural Science), 2013, 41(5): 710-715. [7] 张磊. 基于线激光的道路车辙检测方法研究[D]. 西安: 长安大学, 2015. ZHANG Lei. Research on road rutting detection method based on line laser[D]. Xi’an: Changan University, 2015. [8] 李伟, 孙朝云, 呼延菊, 等. 基于激光3D数据的沥青路面构造深度检测方法[J]. 中外公路, 2016, 36(5): 9-12. LI Wei, SUN Chao Zhaoyun, HUYAN Ju, et al. Detection method of asphalt pavement structure depth based on laser 3D data[J]. Journal of China & Foreign Highway, 2016, 36(5): 9-12. [9] 敬超, 张金喜. 沥青路面性能预测研究综述[J]. 中外公路, 2017, 37(5): 31-35. JING Chao, ZHANG Jinxi. Summary of asphalt pavement performance prediction research[J]. Journal of China & Foreign Highway, 2017, 37(5): 31-35. [10] 陈文, 黄能, 何若夫, 等. 基于寿命周期分析的项目级路面养护决策应用研究[J]. 中外公路, 2019, 39(5): 64-68. CHEN Wen, HUANG Neng, HE Ruofu, et al. Research on pavement maintenance decision in project level based on life cycle analysis[J]. Journal of China & Foreign Highway, 2019, 39(5): 64-68. [11] 钟彪. 沥青混凝土路面预防性养护措施决策与应用[J]. 中外公路, 2018, 38(6): 58-62. ZHONG Biao. Decision and application of preventative maintenance measures for asphalt concrete pavement[J]. Journal of China & Foreign Highway, 2018, 38(6): 58-62.

Download

Share

COinS