Evaluation of 3D Automated Systems for the Measurement of Pavement Surface Cracking

JOURNAL OF TRANSPORTATION ENGINEERING(2016)

引用 12|浏览3
暂无评分
摘要
Pavement management systems rely on accurate distress measurements to support transportation agency officials in making decisions on budget planning and allocation as well as on the design of maintenance and rehabilitation strategies. Errors in distress data measurements lead to inappropriate project prioritization and increased maintenance and rehabilitation costs. This paper presents an independent evaluation of the accuracy and precision of high-speed field measurements of pavement cracking taken by three different automatic three-dimensional (3D) systems that represent the state of the practice. Cracking data were collected from a field experiment designed to represent typical conditions encountered in Texas highway network and comprised twenty 550-ft pavement sections. Three vendors participated in the experiment; two of them used the same hardware (i.e., INO LCMS sensors) but different proprietary algorithms to detect and quantify surface distresses. The third vendor used PaveVision sensors. The high-speed measurements were compared to manual measurements taken statically by experienced certified raters. Further, each service provider was asked to report their results with different levels of manual intervention in order to capture the change in accuracy due to manual postprocessing of the data. The large number of false positives and low overall accuracy and precision showed by the three automated systems highlights the need for improvements on the available high-speed data collection technologies. The accuracy, along with the amount of false positives, significantly improved after applying manual postprocessing. The precision, on the other hand, was similar. In addition, a weak association between cracking measurement accuracy and surface texture was observed for every automated system. (C) 2016 American Society of Civil Engineers.
更多
查看译文
关键词
Automation,Maintenance,Cracking,Systems management,Pavement condition,Rehabilitation,Data collection,Pavement design,Texas,United States
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要