Driver behavior is a key determinant of road safety. Risky behaviors can be measured and quantified using traditional and modern methods, which enables the assessment of the driver's behavior. Following lessons from safety science, it is important to analyse and manage risks factors to optimize interventions in the transport context at the territory. The main objective of the paper is to explore the star rating of the driver's behavior to provide credible road safety monitoring and identification of the factors that most contribute to risky driving behaviors. The Data Envelopment Analysis method for selection of most significant factors is used for star rating of driver's behavior. The subject of the analysis encompasses 18 factors for 27 police administration units (PAUs) in the Republic of Serbia. The results are analysed regarding the following aspects: 1) star rating of driver's behavior and 2) defining the stages of the periodic factors monitoring for each PAU analysed. Using a mobile phone while driving, not using child restraints system, alcohol drunk driving during the night and seat belt use at rear seats of passenger vehicles were identified as the most significant factors associated with risky driving behaviors. Monitoring a broader set of factors helps to identify the strengths and weaknesses of a territory's road safety system. Star rating of driver's behavior as a tool intended for decision-makers ensures monitoring, management, the exchange of evidence-based and customized best practices and defining earlier goal-oriented actions to manage driver's behavior and to prevent risky driving.@en

Road safety developments are correlated with mobility developments, which are in turn affected by socioeconomic factors (level of motorisation, economic growth etc.). During the last few years, road traffic fatalities exhibit important annual reductions in several developed countries; these reductions cannot be justified by policy efforts alone, and are partly attributed to the global economic recession affecting most countries’ economy and mobility. The present research aims to associate annual Gross Domestic Product (GDP) changes with the related annual changes in road traffic mortality rates. Mortality rates and GDP per capita data for the period 1975–2011 are used from 27 European countries, for the development of mixed linear models. The results suggest that an annual increase of GDP per capita leads to an annual increase of mortality rates, whereas an annual decrease of GDP per capita leads to an annual decrease of mortality rates. These effects are statistically significant overall, and in different groups of countries (Northern/Western, Central/Eastern and Southern). A one-year lagged effect of annual GDP decrease was found to be significant in Northern/Western countries. These effects may capture annual GDP increases from the improvement in the prosperity level of most European countries, as well as occasional annual GDP decreases as a result of socioeconomic events (e.g. economic recessions, political changes in Central/Eastern European countries in the early nineties etc.). The models proposed in this paper are able to characterise the short-term dynamics of the examined variables, but not their long-run relationships.@en