Crash Severity Pattern of Motorcycle Crashes in Developing Country Context

TL;DR

This study analyzes motorcycle crash severity in Iran, identifying key factors like collision type and rider characteristics, and proposes targeted safety measures to reduce injuries and fatalities in developing countries.

Contribution

It employs an ordered logistic regression model to identify significant factors affecting crash severity, providing new insights specific to developing country contexts.

Findings

Motorcycles account for 38% of injuries and 15% of fatalities.

Collision with pedestrians significantly increases crash severity.

Young and unlicensed riders are highly correlated with severe crashes.

Abstract

Despite paying special attention to the motorcycle-involved crashes in the safety research, little is known about their pattern and impacts in developing countries. The widespread adoption of motorcycles in such regions in tandem with the vulnerability of motorcyclists exacerbates the likelihood of severe crashes. The main objective of this paper is to investigate the underlying factors contributing to the severity of motorcycle-involved crashes through employing crash data from March 2018 to March 2019 from Iran. Considering the ordinal nature of three injury classes of property-damage-only (PDO), injury, and fatal crashes in our data, an ordered logistic regression model is employed to address the problem. The data statistics suggest that motorcycle is responsible for 38% of injury and 15% of all fatal crashes in the dataset. The results indicate that significant factors contributing to more severe crashes include collision, road, temporal, and motorcycle rider characteristics. Among all attributes, our model is most sensitive to the motorcycle-pedestrian accident, which increases the probability of belonging a crash into injury and fatal crashes by 0.289 and 0.019, respectively. Moreover, we discovered a significant degree of correlation between young riders and riders without a license. Finally, upon the insights obtained from the results, we propose safety countermeasures, including 1) strict traffic rule enforcement upon riders and pedestrians, 2) educational programs, and 3) road-specific adjustment policies.