USING BOSE-EINSTAIN STATSISTICS TO MINIMISE END-TO-END DELAY IN DYNAMIC TRAFFIC NETWORKS

Abstract

Statistical mechanics mapping techniques have been applied to improve the traffic delay times encountered around a large shopping centre in Adelaide, Australia. The shopping centre is large enough to act as a super node attracting a significant number of vehicles within the network.
In the context of the locality scope, the dynamic evolution of the traffic network can be mapped as a Bose gas. We define nodes to be the sites at which a vehicle stops; thus can be represented as energy levels. Links are paths or inter-connectors that allow one or more vehicle to travel between them. They represent particles in Bose-Einstein picture. The mapping shows the emerging of the topological distinct phase-states: “fit get rich” and “winner takes all” when a fitness equation was introduced. The fitness parameter can then be used to control the evolution of these phase-states through its control parameter T. A Locality-Scope based evolutionary algorithm would then be recalled to optimise the traffic signal solutions as required by the phase-state diagram of the evolving network.