Advancements in automated traffic management using fuzzy logic: Prospects and challenges

This article reviews modern methods of automated traffic flow control based on fuzzy logic, which enables the processing of incomplete or imprecise information – a characteristic feature of dynamic traffic conditions. The aim of this study was to evaluate the prospects and challenges associated with implementing fuzzy logic in transport system management to enhance the efficiency and safety of road traffic. The paper examined the potential and difficulties of using fuzzy logic for traffic light control, its integration with intelligent transport systems, and its combination with artificial intelligence and Internet of Things technologies. Fuzzy logic allows systems to adapt to real-time changes, considering factors such as traffic intensity, weather conditions, and driver behaviour. The article analysed several examples of the implementation of such systems in different countries, particularly Japan, Germany, and the United States, where fuzzy algorithms have demonstrated effectiveness in reducing congestion, improving road safety, and optimising the use of transport infrastructure. The main challenges associated with implementing these systems are also outlined, including the complexity of developing fuzzy logic models, the need for highly trained experts to configure such systems, and the technical and financial barriers encountered during the modernisation of transport infrastructure. Additionally, the study discussed cybersecurity and data protection issues, which are increasingly relevant given the extensive use of data in intelligent transport systems. The practical significance of this work lies in identifying effective solutions and opportunities for their adaptation to enhance the safety and capacity of urban and intercity transport systems