An approach of identifying and assessing the factors influencing traffic crashes: a combination of exploratory factor analysis and fuzzy analytical hierarchy process

Preventing traffic accidents is a top priority worldwide, considering its extensive negative impact on people’s physical and mental health, the economy, and government expenditure. This research aims to identify and categorise the potential crash-related factors and evaluate the impact of those factors on the risk of traffic accidents. “Preferred Reporting Items for Systematic Reviews and Meta-Analysis” is used to identify twenty-five potential crash-related factors. In addition, the Exploratory Factor Analysis (EFA) method is used to classify the crash-related factors into five categories, including 1) road, 2) traffic, 3) vehicle, 4) personal, and 5) environment. Finally, the Fuzzy Analytical Hierarchy Process (FAHP) prioritises the factors in each category. For each factor, the factor loadings varied from 0.659 to 0.934, satisfying the factor analysis condition in the EFA. Furthermore, Cronbach’s Alpha values were higher than 0.8 for all factors, which means the collected data had high internal consistency. According to the relative weights identified from FAHP, the road-related factors were ranked in the following order: roadway geometry, non-signalised intersections, number of lanes and lane widths, road surface condition, and road surface type. Similarly, traffic, vehicle, personal, and environmental factors were ranked using FAHP. This study may contribute to the existing literature by scientifically categorising crash-related factors into five main categories and understanding the impacts of the factors on traffic crashes. The results from this study will assist the government and road authorities in reducing the severity of traffic crashes and implementing road safety strategies through informed decisions.