Developing Intelligent Transportation Systems for Smart Cities: A Multi-Agent Approach

Abstract

Growing populations and traffic congestion affect urban transit networks. This article discusses about Intelligent Transportation Systems (ITS) optimise traffic flow, safety, and environmental effect by combining sensors, communication networks, and data analytics. Decentralised Multi-Agent systems (MAS) manage complex transportation networks with real-time decision-making, flexibility, and scalability. MAS may regulate traffic signals, organise routes, handle incidents, and coordinate autonomous vehicles. MAS implementation issues include data integration, communication, and human-agent interaction. Develop autonomous learning techniques, improve security and privacy, and study human-agent cooperation models. MAS is promise for building ITS for smart cities, optimising traffic flow, enhancing safety, and minimising environmental impact despite these obstacles. The article emphasizes the need to develop autonomous learning techniques, enhance security and privacy, and study human-agent cooperation models, offering a comprehensive view of MAS as a transformative solution for building efficient and sustainable ITS in smart cities.