Aggregation of different variables into one road safety performance index is a popular concept in evaluating road safety and comparing the performance of territories/entities. This paper presents the development of a novel and innovative weighting methodology using grey relational analysis. Based on the proposed model, ten hierarchical road safety indicators were selected in terms of a two-layered model with three categories related to behaviour, safety and system. Grey weights are assigned to the categorized indicators in each layer, and the grey road safety composite indicator for each entity (21 selected territories) is calculated by the weighted sum approach. With relatively high weights, this systematic methodology can serve the policy makers in targeting the risk domains where improvements are needed. The results clearly illustrate effectiveness in addressing a large number of indicators with hierarchical structures.

Self-reported behavioural data, being often linguistic variables that represent a qualitative measure of respondents’ opinions/attitudes, are vague, uncertain, and fuzzy in nature. A road safety performance index, based on these fuzzy data, should consider this uncertainty. In this study, fuzzy numbers were used to describe self-reported behaviour on Montenegrin roads, which was further integrated into the data envelopment analysis (DEA), a technique for measuring the relative performance of decision-making units (DMUs). The vagueness of the performance scores obtained in this way was treated with grey relational analysis (GRA). GRA was applied to the cross-efficiency (CE) matrix constructed by the DEA to distinguish Montenegrin municipalities’ performance, with the main goal of describing road safety in the observed territories in the environment of uncertain/grey data. It is concluded that the proposed DEA–GRA model, based on fuzzy data, provides a more reasonable and encompassing measure of performance, and with which the overall ranking position of municipalities can be obtained.

Evaluation of road safety is the core of road safety management, and to prevent traffic accidents, an understanding of the factors that cause them is essential. Currently, road safety experts show great interest in finding one fair approach to...

As the need to assess the level of road safety grows, there is a noticeable tendency of experts to use one overall composite index that contains information on a number of safety performance indicators (SPIs). Indicators commonly used in road safety assessment are numerical, and their natural uncertainty and vagueness are often overlooked. However, there are also SPIs that are rather linguistic, such as data on driver behavior, which are most often collected through questionnaires and are considered qualitative, imprecise, and fuzzy. Together with inappropriate selection of weighting and aggregation methods, such data can be a source of uncertainty and can lead to unreliable results and erroneous conclusions. In this regard, the present study provides a systematic and efficient hybrid method that integrates three different procedures to deal with unavoidable uncertainty in each step of index construction. The application of fuzzy linguistic rating grasp insight into the ambiguity that is intrinsic in drivers’ self-assessment. Entropy describes each observed behavior by quantifying the disorder of a system. Grey relational analysis aggregates behavioral indicators into a composite index, doubting their sufficiency and completeness. A case study of Montenegro has been provided to demonstrate the practical applicability of the proposed method in safety assessment under uncertainty. Results abstracted not wearing the seatbelt as the most common negative behavior among drivers in Montenegro, followed by using the telephone while driving, speeding, and driving under the influence of alcohol. In addition, municipalities are ranked according to the level of road safety.

The aim of the study was to analyse whether driving behaviour differs by gender. It focused on two groups of drivers: those under the age of 24 (young drivers) and those who have held their driving licences for less than five years (inexperienced). By examining behaviours such as speeding, driving under the influence of alcohol, seatbelt usage and the use of child‐resistant systems, the study sought to gain insights into the prevalence and patterns of these behaviours. To achieve the study's objective, a survey was utilised to gather self‐reported behaviour data from 220 young drivers and 271 inexperienced drivers. The frequencies of selected behaviours were analysed, and gender disparities were identified using the Mann‐Whitney test and logistic regression analysis. The study demonstrates that gender is a statistically significant factor influencing behaviour primarily among inexperienced drivers and reveals gender‐specific driving behaviours among young and inexperienced drivers. Priority actions should focus on reducing speed limit violations among inexperienced males on main roads, restraining alcohol consumption while driving among inexperienced males on urban roads, decreasing phone use for texting and social networking among females on urban roads, and promoting the use of child‐resistant systems on both urban and regional roads.