A comparative injury severity analysis of motorcycle at-fault crashes on rural and urban roadways in Alabama. (November 2017)

• Record Type: Journal Article
• Authors: Islam, Samantha; Brown, Joshua
• Is Part Of: Accident analysis and prevention. Volume 108(2017)
• Page Start: 163
• Page End: 171
• Publication Date: 2017-11
• Subjects: At-fault crashes -- Injury severity -- Random parameter -- Rural -- Urban; Accidents -- Prevention -- Periodicals; Accident Prevention -- Periodicals; Accidents -- Prévention -- Périodiques; 363.106
• DOI: 10.1016/j.aap.2017.08.016
• Languages: English
• ISSNs: 0001-4575

Abstract

Highlights: We analyzed injury severities from motorcycle at-fault accidents in Alabama. We considered motorcycle at-fault accidents in rural and urban locations. Two separate random parameter logit models of injury severity were estimated. Some variables were found significant in one model (rural or urban) but not in the other. Some variables were found significant in both rural and urban model. Abstract: The research described in this paper explored the factors contributing to the injury severity resulting from the motorcycle at-fault accidents in rural and urban areas in Alabama. Given the occurrence of a motorcycle at-fault crash, random parameter logit models of injury severity (with possible outcomes of fatal, major, minor, and possible or no injury) were estimated. The estimated models identified a variety of statistically significant factors influencing the injury severities resulting from motorcycle at-fault crashes. According to these models, some variables were found to be significant only in one model (rural or urban) but not in the other one. For example, variables such as clear weather, young motorcyclists, and roadway without light were found significant only in the rural model. On the other hand, variables such as older female motorcyclists, horizontal curve and at intersection were found significant only in the urban model. In addition, some variables (such as, motorcyclists under influence of alcohol, non-usage of helmet, high speed roadways, etc.) were found significant in both models. Also, estimation findings showed that two parameters (clear weather and roadway without light) in the rural model and one parameter (on weekend) in the urban model could be modeled as random parameters indicating their varying influences on the injury severity due to unobserved effects. Based on the results obtained, this paper discusses the effects of different variables on injury severities resulting from rural and urban motorcycle at-fault crashes and their possible explanations.