Speeding behavior is recognized as one of the three main causes of risk on the roads and the most frequent ordinary violation among truck drivers. The study reported in this article focused on the ...

Objective: Driving anger has been found to be a motivational determinant of risky and aggressive driving. The study reported in this article focused on research questions concerning the conceptualization of driving anger and relationships between driving anger and aggressive driving. Methods: In a cross-sectional survey study, 1,020 regular Serbian drivers completed a web-based online questionnaire. Exploratory Factor Analysis and Confirmatory Factor Analysis were used to assess the factor structure and psychometric properties of the Driving Anger Scale. Results: The results showed that the adapted DAS was a valid and reliable instrument divided into five subscales such as discourteous behavior, illegal behavior, slow driving, hostile gestures and traffic obstructions. The robustness of the five-factor model obtained from the EFA was confirmed by the CFA. The study provided evidence supporting the predictive validity of the adapted DAS and revealed that the dimensions of driving anger are differently associated with prosocial and aggressive driving behaviors. Conclusions: The study supports the adapted DAS validity and produces evidence that driving anger is associated with driving outcomes.

To create quality decision-making tools that would contribute to transport sustainability, we need to build models relying on accurate, timely, and sufficiently disaggregated data. In spite of today’s ubiquity of big data, practical applications are still limited and have not reached technology readiness. Among them, passively generated telecom data are promising for studying travel-pattern generation. The objective of this study is twofold. First, to demonstrate how telecom data can be fused with other data sources and used to feed up a traffic model. Second, to simulate traffic using an agent-based approach and assess the emission produced by the model’s scenario. Taking Novi Sad as a case study, we simulated the traffic composition at 1-s resolution using the GAMA platform and calculated its emission at 1-h resolution. We used telecom data together with population and GIS data to calculate spatial-temporal movement and imported it to the ABM. Traffic flow was calibrated and validated with data from automatic vehicle counters, while air quality data was used to validate emissions. The results demonstrate the value of using diverse data sets for the creation of decision-making tools. We believe that this study is a positive endeavor toward combining big data and ABM in urban studies.

The transportation of dangerous goods (TDG) is a critical component of economic systems, especially in regions such as the Western Balkans (WB), where infrastructure and regulatory frameworks face significant challenges. This study assesses the current state of transportation of dangerous goods in Albania, Montenegro, Bosnia and Herzegovina, and Kosovo*, focusing on the alignment of national regulations with international standards such as the ADR agreement. Using a structured questionnaire distributed to 847 stakeholders, key barriers are identified, including inadequate infrastructure, insufficient training, limited oversight and low public awareness. Statistical analyses, including paired t-tests, reveal significant differences in perceptions across the countries surveyed, indicating inequalities in implementation and enforcement. Despite these challenges, there are opportunities to close gaps through targeted investments in infrastructure, increased training programs, stricter compliance and regional cooperation. The findings underscore the need for comprehensive data collection systems and advanced risk assessment tools to improve safety and efficiency. This study contributes to a deeper understanding of TDG issues in the WB countries and provides actionable recommendations for policy makers and practitioners to promote safer and more sustainable practices. The region can improve its TDG framework by addressing these challenges and ensuring economic growth and public safety while minimizing environmental risks.