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.

Current research and development in understanding road users’ driving behaviors play a key role in improving traffic safety. Recently, several driving simulators have been employed as a suitable approach to investigate several drivers’ responses in challenging traffic scenarios. Although professional drivers represent a particular category among driving populations, the body of literature about their comparative behavioral and psychological characteristics remains limited. This study examined the differences in driving performance and visual and physiological responses between civilian and professional drivers in a simulated environment. A total of 30 drivers, with an equal split between professional and civilian categories, took part in a series of driving simulations. The simulations incorporated various infrastructure types, including four cone avoidance tasks and a high-speed motorway task. This study collected comprehensive data on performance metrics, hand usage, heart rate, and eye movements. Eye-tracking technology was used to measure visual attention. The findings revealed that during cone avoidance scenarios, civilian drivers exhibited a similar performance, visual behavior, and physiological response, except for the speed, experiment duration, and throttle, to professional drivers. In the motorway scenario, all metrics showed no significant difference between the two driver groups. These results highlight the need for cautious interpretation, particularly given the limitations of the sample. Revalidation is needed in larger studies, especially for understanding the differences between drivers’ metrics, which is crucial to elevate drivers’ safety, and assessing training programs in Hungary.