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Use of Bivariate Random-Parameter Probit Model to Analyze the Injury Severity of Highway Traffic Crashes Involving School-Age Children
Transportation Research Record: Journal of the Transportation Research Board ( IF 1.6 ) Pub Date : 2021-05-10 , DOI: 10.1177/03611981211011620
Jaeyoung Lee 1 , Suyi Mao 1 , Mohamed Abdel-Aty 2 , Wen Fu 1
Affiliation  

Traffic safety has been a serious public health issue. According to the World Health Organization, annual traffic fatalities and non-fatal injuries are 1.35 million and 20 to 50 million, respectively, worldwide. Vehicle crashes, in particular, are the leading cause of the death of children in the world. This study aims to analyze the injury severity level of drivers and school-age passengers and to identify contributing factors, focusing on the effects of driver characteristics on the severity of injuries to the driver and child passenger. A bivariate model is adopted to capture unobserved shared factors between the driver’s and child’s injury severity levels. The results indicate that the factors contributing to the injury severity level of drivers and school-age passengers are quite different, and some driver characteristics significantly affect the injury severity of the child passenger. The findings from this study can contribute to an efficient strategic plan to reduce the injury severity of vehicle occupants.



中文翻译:

应用二元随机参数概率模型分析学龄儿童的公路交通事故伤害严重程度

交通安全一直是严重的公共卫生问题。根据世界卫生组织的数据,全世界每年的交通事故死亡人数和非致命伤害分别为135万人和20至5000万人。特别是,车祸是世界上儿童死亡的主要原因。本研究旨在分析驾驶员和学龄乘客的伤害严重程度,并找出影响因素,重点关注驾驶员特征对驾驶员和儿童乘客伤害严重程度的影响。采用双变量模型来捕获驾驶员和孩子的伤害严重性水平之间的未观察到的共享因素。结果表明,造成驾驶员和学龄乘客伤害严重程度的因素差异很大,驾驶员的某些特征会严重影响儿童乘客的伤害严重程度。这项研究的结果可以有助于制定有效的战略计划,以减少车辆乘员的伤害严重程度。

更新日期:2021-05-10
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