Islam Samantha, Brown Joshua
Department of Civil, Coastal, and Environmental Engineering, University of South Alabama, 150 Jaguar Drive Shelby Hall, Suite 3142 Mobile, AL 36688, United States.
Accid Anal Prev. 2017 Nov;108:163-171. doi: 10.1016/j.aap.2017.08.016. Epub 2017 Sep 6.
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.
本文所述研究探讨了导致阿拉巴马州农村和城市地区摩托车肇事事故伤害严重程度的相关因素。考虑到摩托车肇事事故的发生，对伤害严重程度的随机参数logit模型（可能的结果为致命、重伤、轻伤以及可能无伤害或无伤害）进行了估计。估计出的模型确定了多种对摩托车肇事事故导致的伤害严重程度有统计学显著影响的因素。根据这些模型，发现一些变量仅在一个模型（农村或城市）中具有显著性，而在另一个模型中则不然。例如，晴朗天气、年轻摩托车手以及无照明道路等变量仅在农村模型中具有显著性。另一方面，年龄较大的女性摩托车手、水平弯道和十字路口等变量仅在城市模型中具有显著性。此外，一些变量（如受酒精影响的摩托车手、未使用头盔、高速道路等）在两个模型中均具有显著性。而且，估计结果表明，农村模型中的两个参数（晴朗天气和无照明道路）以及城市模型中的一个参数（在周末）可被建模为随机参数，表明它们由于未观察到的效应而对伤害严重程度有不同影响。基于所获得的结果，本文讨论了不同变量对农村和城市摩托车肇事事故导致的伤害严重程度的影响及其可能的解释。
