Abstract

Traffic flow simulation is recently being applied to types of studies which require at the same time a large study area and models deeper than macroscopic assignments. Examples are investigations of the effects dynamic route guidance over large networks and the coupling with environmental models on large domains. The computational complexity can be reduced first by moving from microscopic to mesoscopic traffic flow models of the Payne-Cremer type. Where still more computing power is needed, parallelisation of the model may offer a solution. This paper describes a particular mesoscopic traffic flow model and its parallelisation undertaken in the ESPRIT project SIMTRAP. A new two step decomposition strategy is detailed along with its implementation using the message passing model PVM. The resulting speed-up is reported, drawing on both theoretical considerations and on measurements taken in the SIMTRAP demonstrator applications. The paper concludes with lessons learned from the experiments and directions for future work.

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