Dynamics of accident rates on the roads of the Irkutsk region

Introduction. A review of approaches to improve road safety, as well as the methods and models used for this purpose, has been conducted. It has been revealed that children safety on roads remains a pressing issue for the global community. It has been noted that, despite a significant decrease in the number of traffic accidents on Irkutsk roads, their quantity is still high, and further research on the dynamics of all indicators and influencing factors is necessary to identify their changing trends. The purpose of the study. To model tendencies in the number of road accidents and injured traffic participants with the use of regression analysis, to study changes in road accident rates and influencing factors on Irkutsk region roads for the period from 2019 to 2024. Materials and methods. To predict the number of traffic accidents and injured people (sum of hurt and fatal) on Irkutsk roads from 2019 to 2024, traffic police statistics were processed in the Statgraphics. The type of regression model was selected based on the highest value of the determination coefficient. The dynamics of traffic accident rates and road injuries were illustrated in MS Excel. The following methods were used: system analysis, computer modeling based on regression analysis, and statistical analysis of the factors that cause traffic accidents. Results. The analysis of road accidents in the Irkutsk region for the period from 2019 to 2024 has been performed. Regression models of the number of road accidents and injured people have been obtained with high determination coefficients of 99.4 - 99.6%, which allow them to be used for forecasting. Conclusion. The study has demonstrated a steady decrease in the number of road accidents and the number of people injured in them, and statistically significant regression models for their dynamics have been obtained. It was shown that in 2024, 88.7% of road accidents were caused by drivers violating traffic rules. In 70.32% of cases, drivers of passenger cars violated the rules (14.5% of which were drunk). 41% of traffic offenders were between 30 and 50 years old. In 14.5% of cases, traffic violations were committed by drivers with over 30 years of driving experience.