Professional drivers play a crucial role in many businesses and the lives of people. They are responsible for transferring people and goods between distant points, enabling safe and efficient flows. The road traffic death rate is from 8.3 to 27.5 per 100,000 inhabitants in the countries globally. Because professional drivers spend a significant amount of time on the road, their appropriate selection may contribute to general traffic safety. In addition, an adequate selection of candidates significantly impacts the financial costs of the employing company. However, the recruitment procedure is a very complex task where multiple criteria should be considered. By its nature, this is a typical multi-criteria decision-making problem. The purpose of this paper is twofold: to contribute to the methodological, as well as to the professional field. Considering the professional, we propose a decision-making tool in the procedure of professional driver selection. There are several methodological contributions. By reviewing the literature, we identified 14 criteria for candidate selection. In the proposed model, by using expert opinion and implementing DEMATEL and Fuller’s pairwise comparisons, we ranked these criteria and determined the seven most important for further calculation procedure. Here, we introduced an original approach for measuring the reliability of obtained answers. Then, to rank the candidates, the fuzzy AROMAN approach is applied for the first time in the literature. The input data were obtained in the form of a survey, where the experts evaluated the importance of criteria and their interrelation. We used MS Excel and MATLAB for data processing. An additional methodological contribution of this study is an advancement of the AROMAN method by the proposal of an algorithm for the calculation of parameter λ used in the final ranking formula. To illustrate the applicability of the proposed model, a case study is provided. Based on the results, we can conclude that the new methodological approaches can be successfully used in the procedure of professional driver selection, as well as in solving other multi-criteria decision-making problems.

Motorcyclist safety remains a significant problem, and the overall safety of motorcyclists has been improved at a much slower rate in the last decade compared to passenger and commercial vehicles. Because motorcyclists are not protected by the vehicle frame, fatalities or severe injuries are often related to hitting a roadside object or safety barrier. The main objective of this study is to investigate relations between the presence and type of road safety barriers and the consequences of motorcycle crashes on rural roads. For this purpose, we analysed Croatian rural road-crash data from 2015–2019, tested several factors as single predictors, and combined them using binary logistic regression. The results show that run-off-road crashes and nighttime driving are significant risk factors. There was no significant positive impact of the presence of safety barriers on the crash consequences due to the unsuitability of the barriers for motorcyclists, which proves the fact that the functionality of existing safety barriers should be upgraded. The results of this study could be further used by researchers, road designers, and experts to improve road infrastructure safety on rural roads.