Development of a composite road safety performance indicator based on neural networks

Road safety performance indicators as a comprehensible tool provide a better understanding of current safety conditions and monitor the effect of policy interventions. New insights can be gained in case one road safety index is composed of all risk indicators. The safety performance can be evaluated, and actions can be prioritized by the assigned weights. In this paper, a composite structure of neural networks is proposed to develop an overall road safety index. By means of simulation, optimal weights are assigned to two sets of indicators based on a road safety data set for 21 European countries. The correlation of the weighted index with the number of traffic fatalities is calculated. Evaluation results imply the feasibility of this approach.