A Comprehensive Methodology for the Integrated Assessment of Road Safety of Transport and Technological Vehicles Based on Fuzzy Logic

In conditions of increasing complexity and intensity of transportation systems, ensuring road safety requires a transition to proactive and predictive methods of integral risk management. In this work a hierarchical model based on fuzzy logic has been developed to assess the safety of vehicle fleets by aggregating heterogeneous real-time data. To implement a comprehensive assessment, an algorithm has been proposed that performs automated multi-criteria analysis by merging key safety indicators related to technical condition, driver behavior, and operational factors. This algorithm calculates an integrated safety assessment, ranks carriers by risk level, and identifies potential violations. A method of adaptive membership functions has been applied to handle uncertainty and qualitative parameters. A verification study was conducted on theoretical cases covering a range of operational scenarios. A software solution — a Python module for fuzzy inference and visualization has also been implemented, expanding the capabilities of intelligent transportation systems. The results demonstrate that the developed system correctly ranks transport enterprises by risk level. Verification on five theoretical cases (TK۱-TK۵) confirmed the model's ability to generate an Integrated Safety Assessment (ISA) from ۰ to ۱, effectively distinguishing between exemplary compliance and systematic critical violations. For instance, a critically problematic scenario (TK۴) received a low ISA of ۰.۳۴, signaling the need for immediate intervention, while a case with systematic violations (TK۵) scored ۰.۵۵, near the predefined acceptability threshold of ۰.۵.

کلیدواژه ها:

Road Safety ، Fuzzy logic ، integrated risk assessment ، Intelligent Transportation Systems ، proactive management ، adaptive decision support system