Crash risk models for a motorcycle-dominated traffic environment

This paper presents a methodology to estimate the potentials of rear-end and sideswipe crashes for motorcycles moving in a motorcycle-dominated traffic environment on urban roads and examines their integration in the International Road Assessment Programme (iRAP) star rating system. The crash risk models developed are based on discrete choice models and traffic conflict techniques. The proposed methodology was validated using data collected on road segments from the city of Danang in Vietnam. The models’ field validation shows that the proposed methodology produces a good estimate of rear-end and sideswipe crash risk for motorcyclists and the enhanced iRAP star rating methodology produces most satisfactory results. It was found that risk factors such as front distance, longitudinal gap, lateral gap, lateral clearance, speed difference, and operating speed have a significant contribution to motorcycle crash risk and therefore they should be considered in the selection of appropriate countermeasures aimed at improving motorcyclist safety.