Abstract

As one of the most frequently occurring crashes, rear-end crashes often result in injuries and property damage, especially when large trucks are involved. To investigate the contributing factors and the unobserved heterogeneity in such factors, a mixed logit model is developed to analyze rear-end crashes involving large trucks. A dataset containing 7,976 rear-end crashes involving large trucks is collected from Highway Safety Information System (HSIS) in North Carolina between 2005 and 2013. Driver, roadway, and environmental related characteristics are considered in the analysis. Speed limit over 50 mph is found to be better modeled as a random-parameter at specific injury severity levels. Results also indicate that driving under the influence of alcohol or drugs, rural roadways, dark light condition, grade roadway configuration, speed limit over 50 mph will significantly increase the injury severity of large truck involved rear-end crashes. Roadway with traffic control will significantly decrease the injury severity of such crashes. The findings in this study can greatly help traffic agencies and truck companies develop better large truck-involved rear-end crash prevention strategies.

摘要

作为最常见的撞车事故之一，追尾事故往往会导致人身伤害和财产损失，尤其是在涉及大型卡车时。为了研究这些因素中的影响因素和未观察到的异质性，开发了一个混合 logit 模型来分析涉及大型卡车的追尾事故。2005 年至 2013 年间，从北卡罗来纳州的公路安全信息系统 (HSIS) 收集了包含 7,976 起涉及大型卡车的追尾事故的数据集。分析中考虑了驾驶员、道路和环境相关特征。发现超过 50 英里/小时的速度限制可以更好地建模为特定伤害严重程度的随机参数。结果还表明，在酒精或药物的影响下驾驶、乡村道路、暗光条件、坡度道路配置、超过 50 英里/小时的限速将显着增加大型卡车追尾事故的伤害严重程度。道路交通管制将显着降低此类事故的伤害严重程度。本研究的发现可以极大地帮助交通机构和卡车公司制定更好的大型卡车追尾事故预防策略。