Soft Computing Approaches in Traffic Control Systems: A Review

Handling congestion in urban traffic through next generation artificial intelligence techniques is an important research area. Various models and approaches have been developed using soft computing techniques to tackle with this problem. Major soft computing approaches for this purpose are Fuzzy Approaches, Neural Network and Genetic Algorithms, Petri Nets and many more. Also, multi-agent systems are highly applicable in this approach. This paper is an effort towards revisiting such approaches in developing modern traffic control systems.