Relationship between road traffic features and accidents: An application of two-stage decision-making approach for transportation engineers.

An efficient decision-making process is one of the major necessities of road safety performance analysis for human safety and budget allocation procedure. During the road safety analysis procedure, data envelopment analysis (DEA) supports policymakers in differentiating between risky and safe segments of a homogeneous highway. Cross-risk, an extension of the DEA models, provides more information about risky segments for ranking purpose. After identification of risky segments, the next goal is to identify the factors that are major contributors in making that segment risky. This research proposes a methodology to analyze road safety performance by using a combination of DEA with the decision tree (DT) technique. The proposed methodology not only provides a facility to identify problematic road segments with the help of DEA but also identifies contributing factors with the help of DT. Practical applications: The applicability of the proposed model will help policymakers to identify the major factors contributing to road accidents and analysis of safety performance of road infrastructure to allocate the budget during the decision-making process.