Mathematical Modeling of Traffic Conflicts for Assessing the Risk of Design Decisions on the Street and Road Network of Cities

Abstract

The purpose of this study is to develop a mathematical approach to assessing road safety based on the modeling of traffic conflicts at urban intersections. The research aims to identify the relationship between the traffic conflict index and traffic flow intensity and to justify its use for detecting hazardous transport nodes.

The study is based on the analysis of traffic flow intensity and the calculation of a traffic conflict index mmm, which reflects the number and type of conflict points at intersections. Data for key transport nodes of Ternopil were collected for morning and evening peak periods. A correlation analysis was conducted to determine the relationship between traffic conflict and traffic intensity, resulting in correlation coefficients of r=0.611 and r=0.600, respectively. A linear regression model was developed to describe this relationship, demonstrating that an increase in the conflict index leads to a corresponding growth in traffic intensity. The results confirm that complex intersections with higher conflict levels tend to experience greater traffic load. The obtained findings are consistent with modern approaches to proactive road safety assessment based on indirect indicators such as traffic conflicts. The study also highlights the influence of urban structure and traffic distribution on the formation of hazardous zones.

The results of the study confirm that mathematical modeling of traffic conflicts is an effective tool for road safety assessment. The traffic conflict index can be used as an indicator for early detection of potentially dangerous transport nodes. The developed model allows for estimating traffic load depending on intersection complexity and supports decision-making in traffic management. The proposed approach can be applied in urban transport planning and in the development of traffic organization schemes. The findings contribute to improving road safety and optimizing the functioning of urban transport systems.