Objectives: The new EU Directive on Road Infrastructure Safety Management requires Member States to classify the road network into at least three categories according to its safety level. This study examines the application and transferability of the procedures between EU countries. Methods: Our methodology consisted of two steps. First, we conducted a questionnaire survey among twenty Hungarian road safety inspectors, and second, we applied the Italian procedure to calculate the risk index and compare it with historical crash data. Two-lane rural roads were selected and divided into 200 m sections, excluding intersections. Road safety inspectors evaluated these using a matrix of 18 criteria based on video recordings. The risk index was calculated, together with a sensitivity analysis, and its consistency with the observed crash history was investigated. Finally, three homogeneous groups were identified using k-medoids cluster analysis. Results: The survey showed good acceptance of the process, but we also found differences in how inspectors rated certain criteria. Our analysis of inspectors’ ratings of severity showed that there were varying degrees of agreement. However, we also concluded that the three-level rating may help to reduce disagreement. Our risk index calculations used four years of crash data, and a moderate correlation between the crash rate and the risk index was found. By assigning a weighted average of adjacent sections and performing a k-medoids cluster analysis, we found that the optimal number of clusters is three, and these show a meaningful relationship with crash frequency. Conclusion: Regarding the application of the Italian procedure in Hungary to meet the requirements of the new EU RISM, the results are promising, and the lessons learned may also be useful for other countries.

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Black spot ranking is an important tool for finding the sites with potential safety improvement on the road network. The EU Directive on Road Infrastructure Safety Management also demands the ranking of high accident concentration sites. This paper gives an introduction to localizing high accident concentration sites and the indicators used by Italy and Hungary. Accident and traffic volume data are gathered for motorway sections from both countries. Safety ranking is made using two conventional indicators, absolute number of accidents and accident rate. A more sophisticated ranking using the Empirical Bayes method is applied. Expected average crash frequency with Empirical Bayes adjustment is calculated. Based on the estimation of the crash frequency, the Critical Crash Rate (CCR) was added to identify and rank black spots. This additional performance measure is able to take into account traffic volume as required by the EU Directive. Results of the Empirical Bayes method are compared with the conventional procedures. It is concluded that the results are not comparable; inasmuch as there are modifications in the order of black spots. Based on the comparison of results recommendations are given to change the practice in both countries.