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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 104349, 13 pages
http://dx.doi.org/10.1155/2014/104349
Research Article

Multiagent Based Decentralized Traffic Light Control for Large Urban Transportation System

School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Received 2 February 2014; Revised 27 May 2014; Accepted 19 June 2014; Published 15 July 2014

Academic Editor: X. Zhang

Copyright © 2014 Yang Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Intelligent traffic control is an important issue of the modern transportation system. However, in large-scale urban transportation systems, traditional centralized coordination methods suffer bottlenecks in both communication and computation. Decentralized control is hard if there is very limited observation to the whole network as evidences to support joint traffic coordination decisions. In this paper, we proposed a novel decentralized, multiagent based approach for massive traffic lights coordination to promote the large-scale green transportation. Considering that only the traffic from the adjacent intersections may affect the state of a given intersection one time ahead, the key of our approach is using the observations of a local intersection and its neighbors as evidences to support the traffic light coordination decisions. Therefore, we can model the interactions as decentralized agents coordinating with a decision theoretical model. Within a local intersection, constraint optimizing agents are designed to efficiently search for joint activities of the lights. Since this approach involves only local intersection cooperation, it is well scalable and easily implemented with small communication overhead. In the last section, we present our software design on this approach and based on our simulation, this approach is feasible to a large urban transportation system.