Research Article Comparison of Factors Affecting Crash Severities in Hit-and-Run and Non-Hit-and-Run Crashes Bei Zhou , 1 Zongzhi Li, 2 and Shengrui Zhang 1 1 School of Highway, Chang’an University, Xi’an, 710064, China 2 Department of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, 60616, USA Correspondence should be addressed to Bei Zhou; bzhou3@chd.edu.cn Received 29 June 2018; Revised 6 October 2018; Accepted 25 October 2018; Published 4 November 2018 Academic Editor: Eneko Osaba Copyright © 2018 Bei Zhou et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A hit-and-run (HR) crash occurs when the driver of the ofending vehicle fees the crash scene without reporting it or aiding the victims. Te current study aimed at contributing to existing literatures by comparing factors which might afect the crash severity in HR and non-hit-and-run (NHR) crashes. Te data was extracted from the police-reported crash data from September 2017 to August 2018 within the City of Chicago. Two multinomial logistic regression models were established for the HR and NHR crash data, respectively. Te odds ratio (OR) of each variable was used to quantify the impact of this variable on the crash severity. In both models, the property damage only (PDO) crash was selected as the reference group, and the injury and fatal crash were chosen as the comparison group. When the injury crash was taken as the comparison group, it was found that 12 variables contributed to the crash severities in both HR and NHR model. Te average percentage deviation of OR for these 12 variables was 34%, indicating that compared with property damage, HR crashes were 34% more likely to result in injuries than NHR crashes on average. When fatal crashes were chosen as the comparison group, 2 variables were found to be statistically signifcant in both the HR and the NHR model. Te average percentage deviation of OR for these 2 variables was 127%, indicating that compared with property damage, HR crashes were 127% more likely to result in fatalities than NHR crashes on average. 1. Introduction Injuries and fatalities caused by trafc crashes are serious problems encountered by most countries in the world. According to the World Health Organization (WHO), the global number of road trafc deaths reached 1.25 million in 2013, and an additional 20-50 million were injured or disabled [1]. Among various crash types, hit-and-run (HR) crashes have drawn more and more attention in both general public and academia during past few years. A hit-and-run crash occurs when the driver of the striking vehicle leaves the crash scene without reporting it to the authority or aiding the victim [2]. According to a recent AAA (American Automo- bile Association) report, both HR crashes and fatalities were increasing. It was estimated that more than one HR crash happened in the US every minute in 2015 [3]. Although the penalties of HR crash vary from state to state in the US, most states consider it a felony if the crash leads to injury or fatality. HR crashes may not be completely eliminated in the short term, but it is possible to alleviate the severe damage caused to the public by HR. In order to do so, it is crucial to understand factors afecting the severities of HR crashes. And potential engineering and administrative countermeasures could be scheduled and prioritized. Te current paper aimed at contributing to existing literatures by explicitly analyzing factors afecting the crash severities of HR crashes. Moreover, factors afecting severities of HR crashes and non-hit-and-run (NHR) crashes were quantitatively compared correspondingly. 2. Literature Review Current literatures on HR crashes generally fall into two categories: identifying vehicles involved in HR crashes and identifying factors afecting the decisions of feeing crash scenes. Te identifcation of HR vehicles has been an area of interest in various felds, such as forensic, legal, and insurance [4]. For instances, Teresi´ nski and Madro [5] examined knee Hindawi Journal of Advanced Transportation Volume 2018, Article ID 8537131, 11 pages https://doi.org/10.1155/2018/8537131