An Intelligent Traffic Control Model Based on Intersection Agent

Urban traffic control is a complex large system. Using multi-agent system, a traffic control framework was set up, and different control strategies were simulated. The intersection agent (IA) which uses of fuzzy control strategy and has coordination ability was designed. Simulations showed that fuzzy control has better results than either fix-cycle control or local inductive control. Meanwhile, a traffic coordination model and a multi-agent coordination algorithm is presented by self organizing. The functionality of the proposed urban traffic multi-agent system to manage the gradual congestion of the traffic network is tested. Position sliding window algorithm can reduce computing scale. Finally, an intersection agent hardware platform is designed based on embedded system.