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原文传递 Analysis of In-Service Traffic Sign Visual Condition: Tree-Based Model for Mobile LiDAR and Digital Photolog Data

题名：	Analysis of In-Service Traffic Sign Visual Condition: Tree-Based Model for Mobile LiDAR and Digital Photolog Data
其他题名：	Abdel-Aty,M.,and Haleem,K.(2011)."Analyzing angle crashes at unsignalized intersections using machine learning techniques."Accid.Anal.Prev.,43(1),461-470.
正文语种：	英文
作者：	M. Khalilikhah
关键词：	Traffic sign management;Traffic sign condition;Mobile-based data collection;Geographical information system;Random forests
摘要：	Because the important task of traffic signs is to provide drivers with valuable information, the replacement of ineffective signs leads to a safer and more efficient environment for road users. Previously, many researchers studied traffic signs from the perspective of the road user. However, research regarding the identification of factors contributing to sign degradation is far from complete. To fill this gap, this study examines a large number of possible explanatory variables that may affect a sign's visual condition. A data integration strategy is proposed to combine a large traffic sign data set with location and climate information. The Random Forests model and Odds ratio were applied to analyze the mobile light detection and ranging (LiDAR) and digital photolog data and rank all of the contributing factors based on their importance to the sign visual condition. The results showed that the odds of sign failure for signs with mount height less than or equal to 2 m were between 1.55 and 1.72 times those of signs placed higher than 2 m. These findings may reflect the importance of snow frequency and vandalism factors. The findings also revealed that air pollutants were among the most important contributing factors to traffic sign deterioration. Based on the results, a sign inspection schedule is also proposed. The findings of this study provide transportation agencies with useful information in identifying traffic signs that are more likely to be degraded. This study also provides a basis for employing advanced data collection and integration methods to assess the performance of transportation systems with greater consistency and establish asset tracking and risk analysis plans, and thus improve the efficiency of the surface transportation systems by making informed decisions.
出版年：	2018
论文唯一标识：	P-72Y2018V144N06003
英文栏目名称：	TECHNICAL PAPERS
doi：	10.1061/JTEPBS.0000132
期刊名称：	Journal of Transportation Engineering
拼音刊名(出版物代码)：	P-72
卷：	144
期：	06
页码：	12-24