Investigating the Differences of Single-Vehicle and Multivehicle Accident Probability Using Mixed Logit Model. (17th January 2018)

• Record Type: Journal Article
• Authors: Dong, Bowen; Ma, Xiaoxiang; Chen, Feng; Chen, Suren
• Other Names: Huang Helai Academic Editor.
• Is Part Of: Journal of advanced transportation. Volume 2018(2018)
• Publication Date: 2018-01-17
• Subjects: Transportation -- Periodicals; 388.05
• DOI: 10.1155/2018/2702360
• Languages: English
• ISSNs: 0197-6729

Abstract

Abstract : 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.