Abstract
To optimize urban arterial traffic control, this paper analyzed coordination mechanism of all individual junctions along the road. We set up a traffic control system for urban area network based upon multi-agent technology. Each individual junction and the coordination were considered as agents. Each of them was embodiment of fuzzy neural network. We utilized particle swarm optimization arithmetic to optimize these FNNs. The agent directly talked to each other with FIPA ACL standard language. Compared to the traditional timing control mode, at a junction with moderate traffic volume, the average delay expressed in queue length can be reduced from 120.9(veh./h) to 25.4 (veh./h). Congestion thus significantly relieved.
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Zhao, J., Tang, D., Geng, X., Jia, L. (2010). Urban Arterial Traffic Coordination Control System. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16527-6_35
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DOI: https://doi.org/10.1007/978-3-642-16527-6_35
Publisher Name: Springer, Berlin, Heidelberg
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