Multi-agent system model for urban traffic simulation and optimizing based on random walk

Abstract

Intelligent control and guiding of urban traffic syste-m become so important nowadays especially under the current traffic status, which is more and more congested and complicated. In this paper, we proposed a method of modeling the urban traffic flow system combining the global and local model information for the whole city net. We consider that the traffic digraph is composed from several nodes and those nodes are linked with routes lines. The proposed system is inspired by the random walk theory: for each traffic flow in the urban network, we simulated it with a random walk processing, with vehicle flow density and driver strategy independent. These flows only shared traffic lights and affected each other in the congestion situation. Finally we get simulator solution only by seeking the stable solutions of random walk. This intelligent system is very powerful and only the topology structure of city, the start and destination and numbers of each vehicles flow are known, it can return all of the optimized control strategy for each traffic light and driver in the traffic net. For evaluation, different road situations with various system parameters are simulated on the proposed system. The experiments results are satisfied and show the feasibility and robustness our system. © 2010 Springer-Verlag Berlin Heidelberg.