A Combined Index of Proactive and Reactive Data for Rating the Safety of Road Sections

Abstract

There are two main methods for reducing the number of road accident fatalities and damages: proactive statistics and reactive statistics. The segments under consideration do not necessarily have the same level of safety risk and should be prioritized based on safety and budget expertise. Using six proactive and reactive criteria, this study presents a new index for ranking segments of a suburban road in terms of safety, namely accidents, roadside conditions, vertical signs, road markings, pavement conditions, and access density. In this study, a hierarchical analysis, a hybrid indicator of combinative distance-based assessment/evaluation based on distance from average solution, and simple weighted models were applied in addition to safety audit and accident index. The Sanandaj-Kermanshah road was selected as a case study for implementing the model. The road was chosen because of its high traffic, importance, and accident rate. In determining the safety risk of segments, accident severity index and access density were the most important factors. Due to the consideration of two steps to verify the prioritization, the CODAS model received the highest weight in the composite indicator. In suburban roads, the proposed index could be used to prioritize budget allocations for road safety. The innovation of this study is the use of a hierarchical and hybrid indicator for proactive data (obtained from safety audits) and reactive data (obtained from accidents). Also, in past studies, they have not examined the combination of proactive and reactive data.