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MATSim-T: Architecture and Simulation Times

MATSim-T: Architecture and Simulation Times

Michael Balmer, Marcel Rieser, Konrad Meister, David Charypar, Nicolas Lefebvre, Kai Nagel
Copyright: © 2009 |Pages: 22
ISBN13: 9781605662268|ISBN10: 1605662267|ISBN13 Softcover: 9781616924720|EISBN13: 9781605662275
DOI: 10.4018/978-1-60566-226-8.ch003
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MLA

Balmer, Michael, et al. "MATSim-T: Architecture and Simulation Times." Multi-Agent Systems for Traffic and Transportation Engineering, edited by Ana Bazzan and Franziska Klügl, IGI Global, 2009, pp. 57-78. https://doi.org/10.4018/978-1-60566-226-8.ch003

APA

Balmer, M., Rieser, M., Meister, K., Charypar, D., Lefebvre, N., & Nagel, K. (2009). MATSim-T: Architecture and Simulation Times. In A. Bazzan & F. Klügl (Eds.), Multi-Agent Systems for Traffic and Transportation Engineering (pp. 57-78). IGI Global. https://doi.org/10.4018/978-1-60566-226-8.ch003

Chicago

Balmer, Michael, et al. "MATSim-T: Architecture and Simulation Times." In Multi-Agent Systems for Traffic and Transportation Engineering, edited by Ana Bazzan and Franziska Klügl, 57-78. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-226-8.ch003

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Abstract

Micro-simulations for transport planning are becoming increasingly important in traffic simulation, traffic analysis, and traffic forecasting. In the last decades the shift from using typically aggregated data to more detailed, individual based, complex data (e.g. GPS tracking) andthe continuously growing computer performance on fixed price level leads to the possibility of using microscopic models for large scale planning regions. This chapter presents such a micro-simulation. The work is part of the research project MATSim (Multi Agent Transport Simulation, http://matsim.org). In the chapter here the focus lies on design and implementation issues as well as on computational performance of different parts of the system. Based on a study of Swiss daily traffic – ca. 2.3 million individuals using motorized individual transport producing about 7.1 million trips, assigned to a Swiss network model with about 60,000 links, simulated and optimized completely time-dynamic for a complete workday – it is shown that the system is able to generate those traffic patterns in about 36 hours computation time.

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