Proportion-Based Analytical Hierarchy Process for Determining Prominent Reasons Causing Severe Crashes

Abstract

Governments and authorities worldwide consider road traffic crashes (RTCs) to be a major concern. These crashes incur losses in terms of productivity, property, and life. For a country to establish its road and action plans, it is crucial to comprehend the reasons for and consequences of traffic collisions. The main objective of this research study was to evaluate and rank the important and supporting factors influencing traffic crashes on the road. To identify the most significant accident causation elements, the proportion-based analytic hierarchy process (PBAHP) was used to order the factors in terms of their relative importance. In this study, the city of Al-Ahsa, located in the eastern province of Saudi Arabia, was used as a case study, since this city is the highest RTC-prone area in the region. PBAHP was used to calculate relative importance/weights for different crash types and reasons in terms of their impact on crash severity. It was found that vehicle-overturned collisions which result in fatal crashes have the most weight, whereas “hit motorcycle” crashes result in serious injury crashes. When vehicles (two or more) collide with one another while they are moving, it appears that the likelihood of a fatality in a collision increases. The highest weights for serious injury crashes came from “driver distraction”, “leaving insufficient safe distance”, and “speeding”, which also generated similar and relatively high weights for fatal crashes. Weights from the PBAHP approach were also used to develop utility functions for predicting the severity of crashes. This approach could assist decision-makers in concentrating on the key elements affecting road traffic crashes and enhancing road safety.