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Besides the direct effects of targeted interventions and measures, the evolution of traffic safety data is continuously influenced by external processes describing or shaping the traffic system. The aim of our article was to identify social, economic, and other related processes likely to affect traffic or traffic safety, and to examine their influencing effects on accident data. Collection of the time-series data (indicators) has been carried out based on the results of the international literature, considering the issue of data collectability. To explore the influencing effects on accident data, linear regression methodology was applied. The developed methodology is illustrated through a case study conducted in Hungary. According to our results, traffic volume, social indicators, infrastructure, and vehicle fleet had a significant impact on the evolution of accident data. Based on the Hungarian data, the correlation was strongest in the case of traffic volume (development of passenger and goods transport performance, fuel consumption) and infrastructure (share of the different road categories) indicators. Our research contributes valuable insights for understanding and addressing the multifaceted factors influencing traffic safety. • Long-term crash trends assessed by time-series regression (2001–2020). • 6 indicator groups were derived from 23 time-series parameters. • Traffic volume showed the strongest correlation (R 2 = 0.89, p < 0.001). • Infrastructure indicators had significant negative impact on injuries. • Results support evidence-based road safety target setting and monitoring.
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Pauer et al. (2025) studied this question.
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