Benchmarking road safety performance: Identifying a meaningful reference (best-in-class)

For road safety improvement, comparing and benchmarking performance are widely advocated as the emerging and preferred approaches. However, there is currently no universally agreed upon approach for the process of road safety benchmarking, and performing the practice successfully is by no means easy. This is especially true for the two core activities of which: (1) developing a set of road safety performance indicators (SPIs) and combining them into a composite index; and (2) identifying a meaningful reference (best-in-class), one which has already obtained outstanding road safety practices. To this end, a scientific technique that can combine the multi-dimensional safety performance indicators (SPIs) into an overall index, and subsequently can identify the 'best-in-class' is urgently required. In this paper, the Entropy-embedded RSR (Rank-sum ratio), an innovative, scientific and systematic methodology is investigated with the aim of conducting the above two core tasks in an integrative and concise procedure, more specifically in a 'one-stop' way. Using a combination of results from other methods (e.g. the SUNflower approach) and other measures (e.g. Human Development Index) as a relevant reference, a given set of European countries are robustly ranked and grouped into several classes based on the composite Road Safety Index. Within each class the 'best-in-class' is then identified. By benchmarking road safety performance, the results serve to promote best practice, encourage the adoption of successful road safety strategies and measures and, more importantly, inspire the kind of political leadership needed to create a road transport system that maximizes safety.