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Citation |
Gong L, Fan WD. Accid. Anal. Prev. 2017; 101: 124-134. |
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Affiliation |
Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, NC 28223, USA. Electronic address: wfan7@uncc.edu. |
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Copyright |
(Copyright © 2017, Elsevier Publishing) |
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DOI |
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PMID |
28226253 |
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Abstract |
This study investigates factors that significantly contribute to the severity of driver injuries resulting from single-vehicle run-off-road (SV ROR) crashes. A mixed logit model approach is employed to explore the potential unobserved heterogeneous effects associated with each age group: young (ages 16-24), middle-aged (ages 25-65), and older drivers (ages over 65). Likelihood ratio tests indicated that the development of separate injury severity models for each age group is statistically superior to estimating a single model using all data. Based on the crash data collected from 2009 to 2013 in North Carolina, a series of driver, vehicle, roadway, and environmental characteristics are examined. Both parameter estimates and their elasticities are developed and used to interpret the models. The estimation results show that contributing factors which significantly affect the injury severity of an SV ROR crash differ across three age groups. Use of restraint device and horizontal curves are found to affect crash injuries and fatalities in all age groups. Reckless driving, speeding, distraction, inexperience, drug or alcohol involvement, presence of passengers, and driving an SUV or a van are found to have a more pronounced influence in young and middle-aged drivers than older drivers. Compared to the passenger cars, older drivers are less likely to experience possible injuries in a large-size vehicle (e.g., truck or bus). The average annual daily traffic volume and lighting conditions are also found to influence the resulting injury severity of an SV ROR crash specific to young drivers. Language: en |
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Keywords |
Age differences; Crash-injury severities; Mixed logit model; Roadway safety; Run-off-road crashes |