An Improved Framework for Large-Scale Multi-Agent Simulations of Travel Behavior

Bryan Raney and Kai Nagel
Institute for Computational Science, ETH Zürich,
8092 Zürich, Switzerland
braney|nagel@inf.ethz.ch

Abstract:

We describe a framework for running large-scale multi-agent simulations of travel behavior. The framework represents each traveler as an individual ``Agent'' that makes independent decisions about its desired use of the transportation system during a typical day. An Agent keeps a record of its decisions in a ``Plan.'' A Plan contains the Agent's schedule of activities it wants to perform during the day, including times and locations, along with the travel modes and routes it intends to utilize to travel between activities.

An Agent database gives every Agent a memory where it can store several possible Plans, as well as performance information it uses to compare how well different Plans meet its needs. Agents score a Plan's performance based on the output of the micro-simulator. The Agent database also allows Agents to periodically generate new Plans by connecting them to behavioral Modules that model the different kinds of decisions that affect an Agent's Plan. For example, one Module chooses routes, another chooses activity durations. This paper describes the design and our current implementation of this framework, plus the results of some verification scenarios.