A random parameter bivariate probit model for injury severities of riders and pillion passengers in motorcycle crashes

IF 2.4 3区 工程技术 Q3 TRANSPORTATION Journal of Transportation Safety & Security Pub Date : 2021-05-14 DOI:10.1080/19439962.2021.1916666
Shunping Wang, Fengmei Li, Zhengwu Wang, Jie Wang
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引用次数: 9

Abstract

Abstract This study proposes a random parameter bivariate probit model to analyze risk factors on the crash injury severity of both motorcycle riders and passengers in a single modeling framework. The proposed model can not only account for the underlying correlation of common factors affecting the rider and its pillion passenger simultaneously, but also can capture the unobserved heterogeneity across crash samples. The case analysis is based on 3665 motorcycle-carrying-passenger crashes in Hunan province of China. Model comparisons show that the proposed random parameter bivariate probit model outperforms two conventional models in the goodness-of-fit. The results of parameter estimations show that, age and gender differences in passengers pose significant effects on injury severity of the rider in crashes. Specifically, when carrying a vulnerable passenger including women, children and elders, the rider is less likely to sustain severe injuries. But for injury severity of the passenger, these vulnerable passengers are more likely to suffer from severe injuries. Apart form age and gender attributes, factors including collision objects, helmet use, drunk riding, night without lights, peak periods, high-speed roads have significant effects on rider injury and/or passenger injury. Relevant suggestions to alleviate the injury severity for motorcycle-carrying-passengers crashes are recommended.
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摩托车碰撞中乘员及后座乘客损伤严重程度的随机参数二元概率模型
摘要本文提出了一种随机参数双变量概率模型,在单一建模框架下分析摩托车骑手和乘客碰撞损伤严重程度的危险因素。所提出的模型不仅可以同时考虑影响驾驶员和后座乘客的常见因素之间的潜在相关性,还可以捕捉到碰撞样本中未被观察到的异质性。案例分析基于中国湖南省3665起摩托车载客事故。模型比较表明,所提出的随机参数二元概率模型在拟合优度上优于两种传统模型。参数估计结果表明,乘客的年龄和性别差异对事故中乘员的伤害严重程度有显著影响。具体来说,当载着弱势乘客,包括妇女、儿童和老人时,骑手不太可能受到严重伤害。但是对于乘客的伤害程度来说,这些脆弱的乘客更容易受到严重的伤害。除年龄和性别属性外,碰撞物体、头盔使用、酒后骑行、夜间无灯、高峰时段、高速道路等因素对骑行者和/或乘客的伤害有显著影响。提出了减轻摩托车载客事故伤害程度的相关建议。
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来源期刊
CiteScore
6.00
自引率
15.40%
发文量
38
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