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  • Multi-Agent Transport Simulation MATSim

    Andreas Horni, Kai Nagel, Kay W Axhausen (eds.)

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    The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. This book takes stock of the current status.

    The first part of the book gives an introduction to the most important concepts, with the intention of enabling a potential user to set up and run basic simulations.The second part of the book describes how the basic functionality can be extended, for example by adding schedule-based public transit, electric or autonomous cars, paratransit, or within-day replanning. For each extension, the text provides pointers to the additional documentation and to the code base. It is also discussed how people with appropriate Java programming skills can write their own extensions, and plug them into the MATSim core.

    The project has started from the basic idea that traffic is a consequence of human behavior, and thus humans and their behavior should be the starting point of all modelling, and with the intuition that when simulations with 100 million particles are possible in computational physics, then behavior-oriented simulations with 10 million travelers should be possible in travel behavior research. The initial implementations thus combined concepts from computational physics and complex adaptive systems with concepts from travel behavior research. The third part of the book looks at theoretical concepts that are able to describe important aspects of the simulation system; for example, under certain conditions the code becomes a Monte Carlo engine sampling from a discrete choice model. Another important aspect is the interpretation of the MATSim score as utility in the microeconomic sense, opening up a connection to benefit cost analysis.

    Finally, the book collects use cases as they have been undertaken with MATSim. All current users of MATSim were invited to submit their work, and many followed with sometimes crisp and short and sometimes longer contributions, always with pointers to additional references.

    We hope that the book will become an invitation to explore, to build and to extend agent-based modeling of travel behavior from the stable and well tested core of MATSim documented here.

    Table of Contents

    Multi-Agent Transport Simulation MATSim TOC

    • Introducing MATSim (Andreas Horni, Kai Nagel and Kay W. Axhausen)

    • Let’s Get Started (Marcel Rieser, Andreas Horni and Kai Nagel)

    • A Closer Look at Scoring (Kai Nagel, Benjamin Kickhöfer, Andreas Horni and David Charypar)

    • More About Configuring MATSim (Andreas Horni and Kai Nagel)

    • Available Functionality and How to Use It (Andreas Horni and Kai Nagel)

    • MATSim Data Containers (Marcel Rieser, Kai Nagel and Andreas Horni)

    • Generation of the Initial MATSim Input (Marcel Rieser, Kai Nagel and Andreas Horni)

    • MATSim JOSM Network Editor (Andreas Neumann and Michael Zilske)

    • Map-to-Map Matching Editors in Singapore (Sergio Arturo Ordóñez)

    • The “Network Editor” Contribution (Kai Nagel)

    • QSim (Marcel Rieser, Kai Nagel and Andreas Horni)

    • Traffic Signals and Lanes (Dominik Grether and Theresa Thunig)

    • Parking (Rashid A.Waraich)

    • Electric Vehicles (Rashid A.Waraich and Joschka Bischoff)

    • Road Pricing (Kai Nagel)

    • Modeling Public Transport with MATSim (Marcel Rieser)

    • The “Minibus” Contribution (Andreas Neumann and Johan W. Joubert)

    • Semi-Automatic Tool for Bus Route Map Matching (Sergio Arturo Ordóñez)

    • New Dynamic Events-Based Public Transport Router (Sergio Arturo Ordóñez)

    • Matrix-Based pt router (Kai Nagel)

    • The “Multi-Modal” Contribution (Christoph Dobler and Gregor Lämmel)

    • Car Sharing (Francesco Ciari and Milos Balac)

    • Dynamic Transport Services (Michal Maciejewski)

    • Freight Trac (Michael Zilske and Johan W. Joubert)

    • WagonSim (Michael Balmer)

    • freightChainsFromTravelDiaries (Kai Nagel)

    • Destination Innovation (Andreas Horni, Kai Nagel and Kay W. Axhausen)

    • Joint Decisions (Thibaut Dubernet)

    • Socnetgen (Kai Nagel)

    • Within-Day Replanning (Christoph Dobler and Kai Nagel)

    • Making MATSim Agents Smarter with the Belief-Desire-Intention Framework (Lin Padgham and Dhirendra Singh)

    • CaDyTS: Calibration of Dynamic Trac Simulations (Kai Nagel, Michael Zilske and Gunnar Flötteröd)

    • Senozon Via (Marcel Rieser)

    • OTFVis: MATSim’s Open-Source Visualizer (David Strippgen)

    • Accessibility (Dominik Ziemke)

    • Emission Modeling (Benjamin Kickhöfer)

    • Interactive Analysis and Decision Support with MATSim (Alexander Erath and Pieter Fourie)

    • The “Analysis” Contribution (Kai Nagel)

    • Multi-Modeling in MATSim: PSim (Pieter Fourie)

    • Other Experiences with Computational Performance Improvements (Kai Nagel)

    • Evacuation Planning: An Integrated Approach (Gregor Lämmel, Christoph Dobler and Hubert Klüpfel)

    • MATSim4UrbanSim (Kai Nagel)

    • Discontinued Modules (Kai Nagel and Andreas Horni)

    • Organization: Development Process, Code Structure and Contributing to MATSim (Marcel Rieser, Andreas Horni and Kai Nagel)

    • How to Write Your Own Extensions and Possibly Contribute Them to MATSim (Michael Zilske)

    • Some History of MATSim (Kai Nagel and Kay W. Axhausen)

    • Agent-Based Traffic Assignment (Kai Nagel and Gunnar Flötteröd)

    • MATSim as a Monte-Carlo Engine (Gunnar Flötteröd)

    • Choice Models in MATSim (Gunnar Flötteröd and Benjamin Kickhöfer)

    • Queueing Representation of Kinematic Waves (Gunnar Flötteröd)

    • Microeconomic Interpretation of MATSim for Benet-Cost Analysis (Benjamin Kickhöfer and Kai Nagel)

    • Scenarios Overview (Marcel Rieser, Andreas Horni and Kai Nagel)

    • Berlin I: BVG Scenario (Andreas Neumann)

    • Berlin II: CEMDAP-MATSim-Cadyts Scenario (Dominik Ziemke)

    • Switzerland (Andreas Horni and Michael Balmer)

    • Zürich (Nadine Rieser-Schüssler, Patrick M. Bösch, Andreas Horni and Michael Balmer)

    • Singapore (Alexander Erath and Artem Chakirov)

    • Munich (Benjamin Kickhöfer)

    • Sioux Falls (Artem Chakirov)

    • Aliaga (Pelin Onelcin, Mehmet Metin Mutlu and Yalcin Alver)

    • Baoding: A Case Study for Testing a New Household Utility Function in MATSim (Chengxiang Zhuge and Chunfu Shao)

    • Barcelona (Miguel Picornell and Maxime Lenormand)

    • Belgium: The Use of MATSim within an Estimation Framework for Assessing Economic Impacts of River Floods (Ismaïl Saadi, Jacques Teller and Mario Cools)

    • Brussels (Daniel Röder)

    • Caracas (Walter J. Hernández B. and Héctor E. Navarro U.)

    • Cottbus: Traffic Signal Simulation (Joschka Bischoff and Dominik Grether)

    • Dublin (Gavin McArdle, Eoghan Furey, Aonghus Lawlor and Alexei Pozdnoukhov)

    • European Air- and Rail-Transport (Dominik Grether)

    • Gauteng (Johan W. Joubert)

    • Germany (Johannes Illenberger)

    • Hamburg Wilhelmsburg (Hubert Klüpfel and Gregor Lämmel)

    • Joinville (Davi Guggisberg Bicudo and Gian Ricardo Berkenbrock)

    • London (Joan Serras, Melanie Bosredon, Vassilis Zachariadis, Camilo Vargas-Ruiz, Thibaut Dubernet and Mike Batty)

    • Nelson Mandela Bay (Johan W. Joubert)

    • New York City (Christoph Dobler)

    • Padang (Gregor Lämmel)

    • Patna (Amit Agarwal)

    • The Philippines: Agent-Based Transport Simulation Model for Disaster Response Vehicles (Elvira B. Yaneza)

    • Poznan (Michal Maciejewski and Waldemar Walerjanczyk)

    • Quito Metropolitan District (Rolando Armas and Hernán Aguirre)

    • Rotterdam: Revenue Management in Public Transportation with Smart-Card Data Enabled Agent-Based Simulations (Paul Bouman and Milan Lovric)

    • Samara (Oleg Saprykin, Olga Saprykina and Tatyana Mikheeva)

    • San Francisco Bay Area: The SmartBay Project - Connected Mobility (Alexei Pozdnoukhov, Andrew Campbell, Sidney Feygin, Mogeng Yin and Sudatta Mohanty)

    • Santiago de Chile (Benjamin Kickhöfer and Alejandro Tirachini)

    • Seattle Region (Kai Nagel)

    • Seoul (Seungjae Lee and Atizaz Ali)

    • Shanghai (Lun Zhang)

    • Sochi (Marcel Rieser)

    • Stockholm (Joschka Bischoff)

    • Tampa, Florida: High-Resolution Simulation of Urban Travel and Network Performance for Estimating Mobile Source Emissions (Sashikanth Gurram, Abdul R. Pinjari and Amy L. Stuart)

    • Tel Aviv (Christoph Dobler)

    • Tokyo: Simulating Hyperpath-Based Vehicle Navigations and its Impact on Travel Time Reliability (Daisuke Fukuda, Jiangshan Ma, Kaoru Yamada and Norihito Shinkai)

    • Toronto (Adam Weiss, Peter Kucireck and Khandker Nurul Habib)

    • Trondheim (Stefan Flügel, Julia Kern and Frederik Bockemühl)

    • Yarrawonga and Mulwala: Demand-Responsive Transportation in Regional Victoria, Australia (Nicole Ronald)

    • Yokohama: MATSim Application for Resilient Urban Design (Yoshiki Yamagata, Hajime Seya and Daisuke Murakami)

    • Research Avenues (Kai Nagel, Kay W. Axhausen, Benjamin Kickhöfer and Andreas Horni)

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    Large-scale simulation Agent-based modeling Choice modeling Transport modeling Transport planning 




    How to cite
    Horni, A et al. 2016. Multi-Agent Transport Simulation MATSim. London: Ubiquity Press. DOI: http://dx.doi.org/10.5334/baw

    This is an Open Access book distributed under the terms of the Creative Commons Attribution 4.0 license (unless stated otherwise), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. Copyright is retained by the author(s).

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    This book has been peer reviewed. See our Peer Review Policies for more information.

    Additional Information

    Published on 10 Aug 2016


    Pages: 618



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