Road safety risk evaluation by means of improved entropy TOPSIS-RSR

Currently, comparisons of road safety performance at a national or sub-national level are worthy of being conducted; both in order to better understand one's own situation in regards to road safety risk, and to find a meaningful reference (best-in-class) to learn lessons in terms of action program formulation. In this respect, the composite road safety performance index, which condenses the vast amount of road safety information in a comprehensive manner to produce a broad picture of road safety, is rapidly developing and becoming increasingly popular. Mainly due to the unsatisfactory explanation of. more detailed aspects of crash causation and injury prevention when considering isolated indicators such as fatality rate. To this end, a means to measure the multi-dimensional concept of road safety in a scientific and systematic manner is urgently required; specifically a performance measuring technique that can combine the multilayer safety performance indicators (SPIs) into an overall index. In this study the improved entropy TOPSIS-RSR methodology is structured to conduct the road safety risk evaluation process from an overall perspective, based on a composite Road Safety Risk Index (RSRI). Using the results of clustering analysis as a relevant reference, a given set of provinces are grouped into several specific classes based on the RSRI score for case study. The contrasts in results prove to verify the robustness of the proposed model. Furthermore, they indicate the feasibility of applying this model as a valuable tool for road safety policymakers to decision-making activities and performance evaluation that contains multi-alternative and multi-criteria. (C) 2015 Elsevier Ltd. All rights reserved.