Modeling bicyclist injury severity in bicycle–motor vehicle crashes that occurred in urban and rural areas: A mixed logit analysis

12Citations
Citations of this article
20Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The purpose of this paper is to identify and compare the contributing factors to bicyclist injury severity in urban and rural areas. Two mixed logit models are developed for both the urban and rural areas separately to identify factors that significantly contribute to the injury severity outcome of bicyclists resulting from bicycle–motor vehicle crashes. Data collected from 2007 to 2014 in North Carolina are utilized for the model development. The model estimation results show that factors including bicyclist age from 25 to 54, driver age under 25, vehicle speed, and divided road are found to significantly affect the injury severity outcome of bicyclists in bicycle–motor vehicle crashes in rural areas only. In contrast, factors including drivers age over 60, van, single unit truck, head-on crash, motorist overtaking bicyclist, two-way roadway, road condition, and crash time are found to have a significant impact on the injury severity of bicyclists in urban areas only.

Cite

CITATION STYLE

APA

Lin, Z., & David Fan, W. (2019). Modeling bicyclist injury severity in bicycle–motor vehicle crashes that occurred in urban and rural areas: A mixed logit analysis. Canadian Journal of Civil Engineering, 46(10), 924–933. https://doi.org/10.1139/cjce-2018-0781

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free