A multinomial logit model of motorcycle crash severity at Australian intersections

被引:122
作者
Vajari, Mohammad Abrari [1 ]
Aghabayk, Kayvan [1 ]
Sadeghian, Mohammad [1 ]
Shiwakoti, Nirajan [2 ]
机构
[1] Univ Tehran, Coll Engn, Sch Civil Engn, 16 Azar St, Tehran, Iran
[2] RMIT Univ, Sch Engn, Melbourne, Vic, Australia
关键词
Multinomial logit model; Injury severity; Motorcycle crashes; Intersection; Risk factors; INJURY SEVERITIES; SINGLE-VEHICLE; ACCIDENT SEVERITY; ENGINE SIZE; URBAN; RISK; DRIVERS; EXPERIENCE; JUNCTIONS; AGE;
D O I
10.1016/j.jsr.2020.02.008
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
Introduction: Motorcyclists are exposed to more fatalities and severe injuries per mile of travel as compared to other vehicle drivers. Moreover, crashes that take place at intersections are more likely to result in serious or fatal injuries as compared to those that occur at non-intersections. Therefore, the purpose of this study is to evaluate the contributing factors to motorcycle crash severity at intersections. Method: A data set of 7,714 motorcycle crashes at intersections in the State of Victoria, Australia was analyzed over the period of 2006-2018. The multinomial logit model was used for evaluating the motorcycle crashes. The severity of motorcycle crashes was divided into three categories: minor injury, serious injury and fatal injury. The risk factors consisted of four major categories: motorcyclist characteristics, environmental characteristics, intersection characteristics and crash characteristics. Results: The results of the model demonstrated that certain factors increased the probability of fatal injuries. These factors were: motorcyclists aged over 59 years, weekend crashes, midnight/early morning crashes, morning rush hours crashes, multiple vehicles involved in the crash, t-intersections, crashes in towns, crashes in rural areas, stop or give-way intersections, roundabouts, and uncontrolled intersections. By contrast, factors such as female motorcyclists, snowy or stormy or foggy weather, rainy weather, evening rush hours crashes, and unpaved roads reduced the probability of fatal injuries. (C) 2020 National Safety Council and Elsevier Ltd. All rights reserved.
引用
收藏
页码:17 / 24
页数:8
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