A multinomial logit model of motorcycle crash severity at Australian intersections. (June 2020)

• Record Type: Journal Article
• Authors: Abrari Vajari, Mohammad; Aghabayk, Kayvan; Sadeghian, Mohammad; Shiwakoti, Nirajan
• Is Part Of: Journal of safety research. Volume 73(2020)
• Page Start: 17
• Page End: 24
• Publication Date: 2020-06
• Subjects: Multinomial logit model -- Injury severity -- Motorcycle crashes -- Intersection -- Risk factors; Industrial safety -- Periodicals; Accidents -- Prevention -- Periodicals; Safety -- Periodicals; Accidents, Occupational -- Periodicals; Sécurité du travail -- Périodiques; Accidents -- Prévention -- Périodiques; Accidents -- Prevention; Industrial safety; Periodicals; 363.1
• DOI: 10.1016/j.jsr.2020.02.008
• Languages: English
• ISSNs: 0022-4375

Abstract

Highlights: Motorcycle crashes at intersections are investigated with twelve-year crash data. A MNL is used to determine the contributing factors to motorcycle crash severity. Motorcyclist, crash, environmental and intersection characteristics are considered. Certain factors increased the probability of fatal injuries. The results can be useful to guide actions to reduce motorcycle crashes. Abstract: 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. Practical Applications: The results from our study demonstrated that certain treatment measures for t-intersections may reduce the probability of fatal injuries. An effective way for improving the safety of stop or give-way intersections and uncontrolled intersections could be to convert them to all-way stop controls. Further, it is recommended to educate the older riders that with ageing, there are physiological changes that occur within the body which can increase both crash likelihood and injury severity.