Integration of Cognitive Analysis Methods Into the Road Infrastructure Safety Assessment System

This article presents an innovative approach to assessing the hazard levels of rural road sections, based on the integration of cognitive modeling methods and fuzzy logic. The authors propose a comprehensive methodology that allows for the consideration of a wide range of both quantitative and qualitative characteristics of road conditions, as well as modeling complex non-linear relationships between various risk factors. The developed approach includes several key stages: construction of a detailed cognitive map reflecting the structure of relationships between safety factors, formalization of hazard factors using fuzzy set theory, and a risk analysis algorithm based on impulse modeling. The article also suggests promising directions for further research, including integration of the developed approach with geographic information systems, application of machine learning methods for automatic model parameter tuning, and development of dynamic cognitive maps capable of adapting to changing conditions in real-time.