An Agent Approach for Intelligent Traffic-Light Control

In this paper we have adopted an agent approach for traffic light control. According to this approach, our system consists of agents and their world. In the traffic context, the world consists of cars, road networks, traffic lights, etc. Each of these agents controls all traffic lights at a road junction by an observe-think-act cycle. That is, the agent repeatedly observes the current traffic condition at the junction, it then uses this information to reason with condition-action rules to determine how the agent should act in what traffic condition, and finally it performs those actions in order to efficiently manage the traffic flows. We have also developed a NetLogo-based traffic simulator to serve as the agents' world. Our approach is experimented with traffic control of a few connected junctions and the result obtained is promising; it can reduce the average delayed time of each car at each traffic-light near a junction rather substantially when compared with other approaches

[1]  Gilberto Nakamiti,et al.  Fuzzy sets in distributed traffic control , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[2]  Xiao-Xiong Weng,et al.  Architecture of multi-agent system for traffic signal control , 2004, ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004..

[3]  Henk Taale,et al.  Comparing methods to optimise vehicle actuated signal control , 2002 .

[4]  U. Netlogo Wilensky,et al.  Center for Connected Learning and Computer-Based Modeling , 1999 .

[5]  Yukinori Kakazu,et al.  Genetic reinforcement learning for cooperative traffic signal control , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[6]  Ying Li,et al.  Microscopic urban traffic simulation with multi-agent system , 2003, Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint.

[7]  Eswaran Subrahmanian,et al.  Intelligent agents in decentralized traffic control , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[8]  S. Chand,et al.  Self-organizing traffic control via fuzzy logic , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.