Ranking road safety risk factors using preference structures and fuzzy preference structures

Abstract

Traditionally, road safety research focused on describing, explaining and predicting the number of crashes and casualties. In addition to the investigation of road safety outcomes, essential underlying risk factors are worthwhile studying. Insight into the importance of each risk factor provides policymakers with valuable information about the kind of measures most urgently needed to improve road safety. Road safety risk factors may be ranked in several ways. Classical preference structures and fuzzy preference structures, both well-studied mathematical structures in the theory of preference modeling, are introduced in this paper and applied to an European data set. These techniques prove to be promising for the road safety risk context.