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Secondary collisions and injury severity: A joint analysis using structural equation models

机译:二级碰撞和损伤严重程度:使用结构方程模型的联合分析

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Objective: This study aims to investigate the contributing factors to secondary collisions and the effects of secondary collisions on injury severity levels. Manhattan, which is the most densely populated urban area of New York City, is used as a case study. In Manhattan, about 7.5% of crash events become involved with secondary collisions and as high as 9.3% of those secondary collisions lead to incapacitating and fatal injuries.Methods: Structural equation models (SEMs) are proposed to jointly model the presence of secondary collisions and injury severity levels and adjust for the endogeneity effects. The structural relationship among secondary collisions, injury severity, and contributing factors such as speeding, alcohol, fatigue, brake defects, limited view, and rain are fully explored using SEMs. In addition, to assess the temporal effects, we use time as a moderator in the proposed SEM framework.Results: Due to its better performance compared with other models, the SEM with no constraint is used to investigate the contributing factors to secondary collisions. Thirteen explanatory variables are found to contribute to the presence of secondary collisions, including alcohol, drugs, inattention, inexperience, sleep, control disregarded, speeding, fatigue, defective brakes, pedestrian involved, defective pavement, limited view, and rain. Regarding the temporal effects, results indicate that it is more likely to sustain secondary collisions and severe injuries at night.Conclusions: This study fully investigates the contributing factors to secondary collisions and estimates the safety effects of secondary collisions after adjusting for the endogeneity effects and shows the advantage of using SEMs in exploring the structural relationship between risk factors and safety indicators. Understanding the causes and impacts of secondary collisions can help transportation agencies and automobile manufacturers develop effective injury prevention countermeasures.
机译:目的:本研究旨在调查次要碰撞的贡献因素以及二次碰撞对损伤严重程度的影响。曼哈顿是纽约市人口最密集的城市地区,用作案例研究。在曼哈顿,大约7.5%的崩溃事件涉及二次碰撞,高达9.3%的二级碰撞导致丧失态度和致命的伤害。提出了结构方程模型(SEMS)共同模拟了二次碰撞的存在和损伤严重程度,调整内能性效应。使用SEM完全探索二次碰撞,伤害严重程度,伤害严重程度,造成因素,促进损失,疲劳,制动缺损,有限的视图和雨水的结构关系。此外,为了评估时间效应,我们在建议的SEM框架中使用时间作为主持人。结果:由于其与其他模型相比的更好的性能,因此没有约束的SEM用于调查二次冲突的贡献因素。发现十三个解释性变量有助于存在二次碰撞,包括酒精,药物,疏忽,缺乏经验,睡眠,控制被忽视,超速,疲劳,缺陷的制动,行人,有缺陷的路面,有限的观点,有限的观点,有限的观点。关于时间效应,结果表明它更有可能在夜间维持次要碰撞和严重伤害。结论:本研究完全调查次要冲突的贡献因素,并估计在调整内生物性效果后进行二次碰撞的安全效果使用SEM在探索风险因素与安全指标之间结构关系中的优势。了解二次碰撞的原因和影响可以帮助运输机构和汽车制造商开发有效的伤害预防对策。

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