Dynamic Model for Risk Assessment and Prevention of Road Traffic Accidents Involving Pedestrians

Pedestrian-involved road traffic accidents represent a serious challenge for traffic safety and require a comprehensive analysis of the interactions within the driver–vehicle–road–environment system. The objective of this study is to develop a methodology for risk assessment in road traffic accidents involving pedestrians based on the analysis of real court cases and dynamic modeling of vehicle motion. A database of 105 court cases was analyzed, enabling the identification of the main factors influencing the occurrence of pedestrian-related accidents. Based on this analysis, a system of 31 linguistic variables was developed to characterize driver behavior, vehicle technical characteristics, and road environment conditions. These variables were integrated into a mathematical model for quantitative risk assessment that enables the evaluation of the relative influence of different groups of factors on accident probability. In addition, a dynamic model of vehicle motion was developed to analyze the influence of driver reaction time, vehicle speed, and road surface conditions on the possibility of avoiding a collision. The results of the numerical analysis demonstrate that even minimal delays in hazard perception and driver reaction significantly increase the probability of pedestrian-related accidents. These findings highlight the importance of early hazard detection and automated emergency braking systems. The proposed methodology provides a framework for integrating intelligent driver assistance systems and automated braking control aimed at improving the safety of vulnerable road users.