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Investigating the Differences of Single-Vehicle and Multivehide Accident Probability Using Mixed Logit Model

机译:使用混合Logit模型研究单车和多车事故概率的差异

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摘要

Road traffic accidents are believed to be associated with not only road geometric feature and traffic characteristic, but also weather condition. To address these safety issues, it is of paramount importance to understand how these factors affect the occurrences of the crashes. Existing studies have suggested that the mechanisms of single-vehicle (SV) accidents and multivehicle (MV) accidents can be very different. Few studies were conducted to examine the difference of SV and MV accident probability by addressing unobserved heterogeneity at the same time. To investigate the different contributing factors on SV and MV, a mixed logit model is employed using disaggregated data with the response variable categorized as no accidents, SV accidents, and MV accidents. The results indicate that, in addition to speed gap, length of segment, and wet road surfaces which are significant for both SV and MV accidents, most of other variables are significant only for MV accidents. Traffic, road, and surface characteristics are main influence factors of SV and MV accident possibility. Hourly traffic volume, inside shoulder width, and wet road surface are found to produce statistically significant random parameters. Their effects on the possibility of SV and MV accident vary across different road segments.
机译:人们认为,道路交通事故不仅与道路的几何特征和交通特性有关,而且与天气状况有关。为了解决这些安全问题,了解这些因素如何影响碰撞事故的发生至关重要。现有研究表明,单车(SV)事故和多车(MV)事故的机理可能非常不同。很少有研究通过同时解决未观察到的异质性来检验SV和MV事故概率的差异。为了研究对SV和MV的不同影响因素,采用混合logit模型,使用分类数据,将响应变量分类为无事故,SV事故和MV事故。结果表明,除了速度差距,路段长度和湿路面对SV和MV事故均很重要外,其他大多数变量仅对MV事故才重要。交通,道路和地面特性是SV和MV事故可能性的主要影响因素。发现每小时的交通量,内路肩宽度和潮湿的路面产生统计上显着的随机参数。它们对SV和MV事故可能性的影响在不同的路段上有所不同。

著录项

  • 来源
    《Journal of Advanced Transportation》 |2018年第1期|11.1-11.9|共9页
  • 作者单位

    Tongji Univ, Coll Traff Engn, 4800 Caoan Rd, Shanghai 201804, Peoples R China;

    Tongji Univ, Coll Traff Engn, 4800 Caoan Rd, Shanghai 201804, Peoples R China;

    Tongji Univ, Coll Traff Engn, 4800 Caoan Rd, Shanghai 201804, Peoples R China;

    Colorado State Univ, Dept Civil & Environm Engn, Ft Collins, CO 80523 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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