planomat: a comprehensive scheduler for a large-scale multi-agent transportation simulation

An external strategy module for an iterative multi-agent micro-simulation of travel demand is presented. This module called planomat currently optimizes the time allocation and route choice of activity plans, which are the agent-based representation of travel demand. The module combines broad search for alternative timing decisions with an optimization procedure for a scoring function that evaluates activity plans. As part of t he existing Multi-Agent Transportation SIMulation Toolbox (MATSIM-T), regional traffic systems of several 100’000 agents can be simulated. The test scenario used here is the Canton of Zurich, the biggest metropolitan area of Switzerland, with 550’000 agents. The comprehensive opt imization of activity plans leads to a system relaxation within an acceptable number of 60 iterations. The quality of the time allocation optimization is shown by departure time distributions.

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