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Exploring driver injury severity patterns and causes in low visibility related single-vehicle crashes using a finite mixture random parameters model
Analytic Methods in Accident Research ( IF 12.9 ) Pub Date : 2018-09-06 , DOI: 10.1016/j.amar.2018.08.001
Zhenning Li , Cong Chen , Qiong Wu , Guohui Zhang , Cathy Liu , Panos D. Prevedouros , David T. Ma

Low visibility is consistently considered as a hazardous factor due to its potential leading to severe fatal crashes. However, unlike the other inclement weather conditions that have attracted extensive research interests, only a few studies have been conducted to investigate the impacts of risk factors on driver injury severity outcomes in low visibility related crashes. A three-year crash dataset including all low visibility related crashes from 2010 to 2012 in four South Central states, i.e., Arkansas, Louisiana, Texas, and Oklahoma, is adopted in this study. A finite mixture random parameters approach is developed to interpret both within-class and between-class unobserved heterogeneity among crash data. After a careful comparison, a two-class finite mixture random parameter model with normal distribution assumptions is selected as the final model. Estimation results show that three variables, including young (specific to injury, I), male (specific to serious injury and fatality, F), and large truck (specific to serious injury and fatality, F), are found to be normally distributed and have significant impacts on driver injury severities. Variables with fixed effects including rural, wet, 60 mph or higher, no statutory limit, dark, Sunday, curve, rollover, light truck, old, and drug/alcohol impaired also have significant influences on driver injury severities. This study provides an insightful understanding of the impacts of these variables on driver injury severity outcomes in low visibility related crashes, and a beneficial reference for developing countermeasures and strategies to mitigate driver injury severities under these conditions.



中文翻译:

使用有限混合随机参数模型探索驾驶员伤害的严重程度模式以及与低能见度相关的单车事故

低能见度一直被认为是一个危险因素,因为它有可能导致严重的致命事故。但是,与引起广泛研究兴趣的其他恶劣天气条件不同,仅进行了少量研究来调查低能见度相关事故中危险因素对驾驶员伤害严重性结果的影响。本研究采用了三年崩溃数据集,其中包括2010年至2012年中南部四个州(阿肯色州,路易斯安那州,德克萨斯州和俄克拉荷马州)与低能见度相关的所有崩溃。开发了一种有限混合随机参数方法来解释碰撞数据之间的类内和类间未观察到的异质性。经过仔细比较 选择具有正态分布假设的两类有限混合随机参数模型作为最终模型。估计结果表明,三个变量包括发现青年人(特定于伤害,I 男性(特定于严重伤害和死亡,F 大型卡车(特定于严重伤害和死亡,F 呈正态分布,并严重影响驾驶员的受伤严重程度。具有固定影响的变量,包括农村潮湿60 mph或更高无法定限制黑暗星期天曲线翻车轻型卡车旧车毒品/酒精饮料受损对驾驶员的伤害严重程度也有重大影响这项研究提供了对这些变量对低能见度相关的碰撞中这些变量对驾驶员伤害严重性结果的影响的深刻理解,并为开发在这些条件下减轻驾驶员伤害严重性的对策和策略提供了有益的参考。

更新日期:2018-09-06
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