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A comprehensive analysis of factors influencing the injury severity of large-truck crashes

机译:影响大卡车撞车事故严重程度的因素的综合分析

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Given the importance of trucking to the economic well being of a country and the safety concerns posed by the trucks, a study of large-truck crashes is critical. This paper contributes by undertaking an extensive analysis of the empirical factors affecting injury severity of large-truck crashes. Data from a recent, nationally representative sample of large-truck crashes are examined to determine the factors affecting the overall injury severity of these crashes. The explanatory factors include the characteristics of the crash, vehicle(s), and the driver(s). The injury severity was modeled using two measures. Several similarities and some differences were observed across the two models which underscore the need for improved accuracy in the assessment of injury severity of crashes. The estimated models capture the marginal effects of a variety of explanatory factors simultaneously. In particular, the models indicate the impacts of several driver behavior variables on the severity of the crashes, after controlling for a variety of other factors. For example, driver distraction (truck drivers), alcohol use (car drivers), and emotional factors (car drivers) are found to be associated with higher severity crashes. A further interesting finding is the strong statistical significance of several dummy variables that indicate missing data - these reflect how the nature of the crash itself could affect the completeness of the data. Future efforts should seek to collect such data more comprehensively so that the true effects of these aspects on the crash severity can be determined.
机译:考虑到卡车运输对一个国家经济状况的重要性以及卡车带来的安全问题,对大型卡车撞车事故的研究至关重要。本文通过对影响大卡车撞车事故严重程度的经验因素进行广泛分析来做出贡献。检查了来自最近全国有代表性的大型卡车碰撞事故的数据,以确定影响这些事故总体伤害严重性的因素。解释性因素包括碰撞,车辆和驾驶员的特征。使用两种方法对伤害严重程度进行建模。在两个模型之间观察到了一些相似性和一些差异,这突显了在评估碰撞伤害严重性方面需要提高准确性的需求。估计模型同时捕获了各种解释性因素的边际效应。特别是,这些模型在控制了各种其他因素之后,指出了多个驾驶员行为变量对撞车严重性的影响。例如,发现驾驶员分心(卡车驾驶员),饮酒(汽车驾驶员)和情绪因素(汽车驾驶员)与严重程度更高的事故相关。另一个有趣的发现是,表明数据丢失的几个虚拟变量具有很强的统计意义-这些变量反映了崩溃本身的性质如何影响数据的完整性。未来的工作应寻求更全面地收集此类数据,以便可以确定这些方面对碰撞严重性的真实影响。

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