Abstract：
This exploratory study is a follow-up to a 2014 study that investigated factors associated with large truck at-fault crash outcomes in Alabama. To assess unobserved temporal changes in the effects of the crash factors, this study re-creates the original crash models developed in the 2014 study using crash data from 2017 to 2019. Four mixed logit models were re-created using the same variables used in the previous study to analyze contributing crash factors to injury severity of single-vehicle (SV) and multi-vehicle-involved (MV) large truck at-fault crashes in urban and rural settings. It was found that there have been temporal changes in how many of the factors influenced crash severity with some of them no longer showing any significant association with crash outcomes, while others remained significant. Further, it was observed that some of the variables that remained significant had different relationships with crash injury severity in the newer severity models. For instance, while factors such as fatigued driver (in rural crashes), clear weather (in urban crashes), single-unit truck (in rural SV crashes), truck rollover (in urban SV crashes) maintained consistent significance over time, the effects of variables such as at-fault male drivers (in urban MV crashes), at-fault female drivers (in urban MV crashes), and hitting fixed object (in rural MV crashes) have changed. One such notable difference is the variable for absence of traffic control which increased the probability of major injury in rural SV crashes by 49.50% in the 2014 model but decreased the probability of recording major injuries by 108.90% using the 2017-2019 data. Considering the temporal changes that were observed in the recreated models, newer models were developed, revealing the emergence of new variables such as truck age that are significantly associated with truck crash severity. The findings of this study provide evidence to suggest that some crash severity factors for at-fault large truck collisions vary over time, with newer ones also emerging over time. These findings can also help trucking companies, transportation engineers, and other industry experts in developing measures to reduce large truck crashes.
摘要：
这项探索性研究是2014年一项研究的后续研究，该研究调查了与阿拉巴马州大型卡车故障事故结果相关的因素。为了评估碰撞因素影响的未观察到的时间变化，本研究使用2017年至2019年的碰撞数据重新创建了2014年研究中开发的原始碰撞模型.使用先前研究中使用的相同变量重新创建了四个混合logit模型，以分析造成单车（SV）和多车（MV）大型卡车故障事故严重程度的碰撞因素。城市和农村设置。结果发现，有多少因素影响了碰撞严重程度，其中一些因素不再显示与碰撞结果的任何显着关联。而其他人仍然很重要。Further,据观察,在较新的严重程度模型中,一些仍然显著的变量与碰撞损伤严重程度有不同的关系.例如,而诸如司机疲劳(在农村撞车事故中)等因素，晴朗的天气（在城市交通事故中），单单元卡车(在农村SV事故中)，卡车翻车(在城市SV碰撞中)随着时间的推移保持一致的重要性，诸如有过错的男性司机(在城市MV撞车事故中)等变量的影响，有过错的女司机(在城市MV撞车事故中)，击中固定对象(在农村MV崩溃中)已经改变。其中一个显着差异是缺乏交通管制的变量，在2014年模型中，农村SV撞车事故的重大伤害概率增加了49.50％，但使用2017-2019年的数据，记录重大伤害的概率降低了108.90％。考虑到在重新创建的模型中观察到的时间变化，开发了新的模型，揭示了新变量的出现，如卡车年龄，与卡车碰撞严重程度显著相关。这项研究的结果提供的证据表明，一些碰撞严重因素的故障大型卡车碰撞随时间而变化，随着时间的推移，新的也会出现。这些发现也可以帮助卡车运输公司，交通工程师,和其他行业专家在制定措施，以减少大型卡车碰撞。
