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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.

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 evaluate and compare road safety situations in different territories. Previously, the assessment of the situation and comparisons were based on the size of the consequences in traffic accidents but recently, the road safety experts turned to observing and comparing safety indicators as a more humane approach, given that in this way critical aspects can be seen at an early stage and before accidents occur. Over time, an approach of describing the road safety situation with a composite index has been developed in which a large number of indicators have been aggregated. The composite traffic safety index is a useful tool in assessing the safety situation that provides comparison, monitoring and communication between different territories and defines the elements of the system that need to be improved. The methodological development of the index construction continues today. The main steps of the mentioned process are the selection of the relevant set of indicators and determining the influence of each of them. In this paper, a set of ten hierarchical road safety indicators in terms of final outcomes, the road users' behavior and basic territory information are weighted with grey relational analysis and aggregated in order to calculate one composite index score of 21 municipalities of Montenegro. Grey relational analysis can measure the relative importance among indicators, implying that those with higher grey weight values are more significant than those with lower grey weights. However, it cannot be claimed that indicator with the highest weight has the greatest impact on accidents occurrence, but it certainly indicates a field where strategies can be adopted to improve level of road safety.

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.