North Carolina Department of Transportation
Research & Innovation Summit – 2020
Investigating Factors Affecting Injury Severity in Bicycle-Vehicle Crashes: A Day-of-Week Analysis with Partial Proportional Odds Logit Models
Authors: Shaojie Liu and Wei Fan
UNCC
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Introduction
Bicycle is increasingly popular as an environment-friendly transportation mode for short-distance travels. A study that was conducted in 2014 stated that 36 states in the US established their goals to promote either walking or bicycling, representing a remarkable improvement from 2007 when there were only 16 states established such goals (Milne and Melin 2014). Nevertheless, due to inferior protective equipment compared to motorized vehicle users, cyclists are prone to experience more severe injuries if crashes occur. To gain a better understanding of the mechanism of bicycle-vehicle crashes, many efforts have been made in analyzing the contributing factors to injury severities in the crashes involving cyclists (Lin and Fan 2019; Moore et al.. 2011).
Cyclist riding behaviors are likely to present different patterns in different time periods, such as day of week, which could have an impact on injury severities. Since few studies have been conducted on the injury severity analysis of crashes involving cyclists in terms of days of week, this study aims to mitigate this gap by conducting a crash severity analysis for cyclists on weekdays and weekends by using the partial proportional logit model particularly. The results of this study would improve the understanding of different mechanisms of cyclist-vehicle crashes.
For questions about this research, contact Shaojie Liu at sliu29@uncc.edu .