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Despite paying special attention to the motorcycle-involved crashes in thesafety research, little is known about their pattern and impacts in developingcountries. The widespread adoption of motorcycles in such regions in tandemwith the vulnerability of motorcyclists exacerbates the likelihood of severecrashes. The main objective of this paper is to investigate the underlyingfactors contributing to the severity of motorcycle-involved crashes throughemploying crash data from March 2018 to March 2019 from Iran. Considering theordinal nature of three injury classes of property-damage-only (PDO), injury,and fatal crashes in our data, an ordered logistic regression model is employedto address the problem. The data statistics suggest that motorcycle isresponsible for 38% of injury and 15% of all fatal crashes in the dataset. Theresults indicate that significant factors contributing to more severe crashesinclude collision, road, temporal, and motorcycle rider characteristics. Amongall attributes, our model is most sensitive to the motorcycle-pedestrianaccident, which increases the probability of belonging a crash into injury andfatal crashes by 0.289 and 0.019, respectively. Moreover, we discovered asignificant degree of correlation between young riders and riders without alicense. Finally, upon the insights obtained from the results, we proposesafety countermeasures, including 1) strict traffic rule enforcement uponriders and pedestrians, 2) educational programs, and 3) road-specificadjustment policies.

Crash Severity Pattern of Motorcycle Crashes in Developing Country Context