Vasil Uzunov

Pedestrian-involved road traffic accidents remain a major road safety concern and require a comprehensive analysis of the interactions within the “driver–vehicle–road–environment” system. Despite the substantial body of research in this field, most existing models rely on predefined parameters and experimental data, while the considerable information potential contained in the reasoning underlying judicial decisions concerning real-world road traffic accidents remains underutilized. This study proposes a novel approach in which the reasoning underlying judicial decisions is considered a structured source of technical information. Through a systematic analysis of the documented factual circumstances, technical expert reports, witness testimonies, and judicial findings, quantitative and qualitative characteristics of the transport system are extracted. This information is subsequently transformed into a system of linguistic variables describing driver behavior, vehicle technical characteristics, and road-environment conditions. The use of a symmetrically structured system of variables enables a consistent description of different vehicle–pedestrian interaction scenarios, regardless of the direction of motion and their relative positions. The geometric symmetry of the vehicle with respect to its longitudinal axis, together with the symmetrical representation of the traffic corridor, provides a unified coordinate framework for dynamic modeling and quantitative risk assessment. The proposed methodology was developed through an analysis of the reasoning underlying 105 judicial decisions concerning real-world pedestrian-involved road traffic accidents. As a result, 31 linguistic variables were identified and combined into an information vector describing each individual case. The analysis of the empirical distribution of the risk assessments shows mean values of 55.42% for driver-related factors, 49.29% for vehicle-related factors, and 35.77% for factors characterizing the road and environment. The results obtained indicate the dominant influence of the human factor on the formation of the integrated risk.

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.