MATSim-T: Architecture and simulation times

Multi-Agent Systems for Traffic and Transportation Engineering

Volumn , Issue , 2009, Pages 57-78

  Balmer, Michael ^a   Rieser, Marcel ^b   Meister, Konrad ^a   Charypar, David ^a   Lefebvre, Nicolas ^a   Nagel, Kai ^b  

^a ETH ZURICH   (Switzerland)

^b TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84901529182     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-60566-226-8.ch003     Document Type: Chapter

References (48)

1. Arentze, T., Hofman, F., van Mourik, H., & Timmermans, H. (2000). ALBATROSS: A multi-agent rule-based model of activity pattern decisions. Paper 00-0022, Transportation Research Board Annual Meeting, Washington, D.C.
2. Arnott, R., Palma, A. D., & Lindsey, R. (1993). A structural model of peak-period congestion: A traffic bottleneck with elastic demand. The American Economic Review, 83(1), 161-179.
3. Avineri, E., & Prashker, J. (2003). Sensitivity to uncertainty: Need for paradigm shift. Transportation Research Record, 1854, 90-98.
4. Axhausen, K. (1988). Eine ereignisorientierte Simulation von Aktivitätenketten zur Parkstandswahl. Ph.D. thesis, Universität Karlsruhe, Germany.
5. Axhausen, K., & Herz, R. (1989). Simulating activity chains: German approach. Journal of Transportation Engineering, 115(3), 316-325.
6. Axhausen, K., Zimmermann, A., Schönfelder, S., Rindsfüser, G., & Haupt, T. (2002). Observing the rhythms of daily life: A six-week travel diary. Transportation, 29(2), 95-124.
7. Balmer, M. (2007). Travel demand modeling for multi-agent transport simulations: Algorithms and systems. Ph.D. thesis, Swiss Federal Institute of Technology (ETH) Zürich, Switzerland.
8. Balmer, M., Axhausen, K., & Nagel, K. (2006). Agent-based demand modeling framework for large scale micro-simulations. Transportation Research Record, 1985, 125-134.
9. Balmer, M., & Nagel, K. (2006). Shape morphing of intersection layouts using curb side oriented driver simulation. In J. Van Leeuwen, & H. Timmermans (Eds.), Innovations in Design & Decision Support Systems in Architecture and Urban Planning (pp. 167-183).
10. Bhat, C., Guo, J., Srinivasan, S., & Sivakumar, A. (2004). A comprehensive econometric microsimulator for daily activity-travel patterns. Transportation Research Record, 1894, 57-66.
11. Bowman, J., Bradley, M., Shiftan, Y., Lawton, T., & Ben-Akiva, M. (1999). Demonstration of an activity-based model for Portland. In World Transport Research: Selected Proceedings of the 8th World Conference on Transport Research 1998, 3, 171-184. Elsevier, Oxford.
12. Cetin, N. (2005). Large-Scale parallel graph-based simulations. Ph.D. thesis, Swiss Federal Institute of Technology (ETH) Zürich, Switzerland.
13. Cetin, N., Burri, A., & Nagel, K. (2003). A large-scale agent-based traffic microsimulation based on queue model. In Proceedings of Swiss Transport Research Conference (STRC). Monte Verita, CH. See www.strc.ch. Earlier version, with inferior performance values: Transportation Research Board Annual Meeting 2003 paper number 03-4272.
14. Charypar, D., Axhausen, K., & Nagel, K. (2007). An event-driven parallel queue-based microsimulation for large scale traffic scenarios. In Proceedings of the Word Conference on Transport Research. Berkeley, CA.
15. Charypar, D., & Nagel, K. (2005). Generating complete all-day activity plans with genetic algorithms. Transportation, 32(4), 369-397.
16. Ciari, F., Balmer, M., & Axhausen, K. (2007). Mobility tool ownership and mode choice decision processes in multi-agent transportation simulation. In Proceedings of Swiss Transport Research Conference (STRC). Monte Verita, CH. See www.strc.ch.
17. de Palma, A., & Marchal, F. (2002). Real case applications of the fully dynamic METROPOLIS tool-box: An advocacy for large-scale mesoscopic transportation systems. Networks and Spatial Economics, 2(4), 347-369.
18. Gawron, C. (1998). An iterative algorithm to determine the dynamic user equilibrium in a traffic simulation model. International Journal of Modern Physics C, 9(3), 393-407.
19. Hanson, S., & Burnett, K. (1982). The analysis of travel as an example of complex human behaviour in spatially-constraint situation: Definition and measurement issues. Transportation Research Part A: Policy and Practice, 16(2), 87-102.
20. Holland, J. (1992). Adaptation in Natural and Artificial Systems. Bradford Books. Reprint edition.
21. Hunt, J., Johnston, R., Abraham, J., Rodier, C., Garry, G., Putman, S., & de la Barra, T. (2000). Comparisons from Sacramento mode test bed. Transportation Research Record, 1780, 53-63.
22. Lefebvre, N., & Balmer, M. (2007). Fast shortest path computation in time-dependent traffic networks. In Proceedings of Swiss Transport Research Conference (STRC). Monte Verita, CH. See www.strc.ch.
23. Meister, K. (2004). Erzeugung kompletter Aktivitätenpläne für Haushalte mit genetischen Algorithmen. Master's thesis, IVT, ETH Zürich. See www.ivt.ethz.ch/docs/students/dip44.pdf.
24. Meister, K., Rieser, M., Ciari, F., Horni, A., Balmer, M., & Axhausen, K. (2008). Anwendung eines agentenbasierten Modells der Verkehrsnachfrage auf die Schweiz. In Proceedings of Heureka '08. Stuttgart, Germany.
25. Nagel, K., & Rickert, M. (2001). Parallel implementation of the TRANSIMS micro-simulation. Parallel Computing, 27(12), 1611-1639.
26. Nagel, K., & Schleicher, A. (1994). Microscopic traffic modeling on parallel high performance computers. Parallel Computing, 20, 125-146.
27. Nagel, K., & Schreckenberg, M. (1992). A cellular automaton model for freeway traffic. Journal de Physique I France, 2, 2221-2229.
28. Palmer, R., Arthur, W. B., Holland, J. H., LeBaron, B., & Tayler, P. (1994). Artificial economic life: a simple model of a stockmarket. Physica D, 75, 264-274.
29. Pendyala, R. (2004). Phased Implementation of a Multimodal Activity-Based Travel Demand Modeling System in Florida. Volume II: FAMOS Users Guide. Research report, Florida Department of Transportation, Tallahassee. See www.eng.usf.edu/~pendyala/publications.
30. PTV (accessed 2008). Traffic Mobility Logistics. See www.ptv.de.
31. Raney, B., & Nagel, K. (2004). Iterative route planning for large-scale modular transportation simulations. Future Generation Computer Systems, 20(7), 1101-1118.
32. Raney, B., & Nagel, K. (2006). An improved framework for large-scale multi-agent simulations of travel behaviour. In P. Rietveld, B. Jourquin, & K. Westin (Eds.), Towards better performing European Transportation Systems (p. 42). London: Routledge.
33. Rieser, M., & Nagel, K. (2008). Network breakdown "at the edge of chaos" in multi-agent traffic simulations. European Journal of Physics. Doi 10.1140/epjb/e2008-00153-6.
34. Salvini, P., & Miller, E. (2005). ILUTE: An operational prototype of a comprehensive microsimulation model of urban systems. Network and Spatial Economics, 5(2), 217-234.
35. Schnittger, S., & Zumkeller, D. (2004). Longitudinal microsimulation as a tool to merge transport planning and traffic engineering models - the MobiTopp model. In Proceedings of the European Transport Conference. Strasbourg.
36. Schönfelder, S., Axhausen, K., & Antille, M., N.and Bierlaire(2002). Exploring the potentials of automatically collected GPS data for travel behaviour analysis - a Swedish data source. In J. Mölthen, & A. Wytzisk (Eds.), GI-Technologien für Verkehr und Logistik - IfGI, 13, 155-179. Münster, Germany: Institut für Geoinformatik.
37. SFSO (2000). Eidgenössische Volkszählung. Swiss Federal Statistical Office, Neuchatel.
38. SFSO (2001). Eidgenössische Betriebszählung 2001 - Sektoren 2 und 3. Swiss Federal Statistical Office, Neuchatel.
39. SFSO (2006). Ergebnisse des Mikrozensus 2005 zum Verkehrs. Swiss Federal Statistical Office, Neuchatel.
40. TRANSIMS (accessed 2008). TRansportation ANalysis and SIMulation System. See transims.tsasa. lanl.gov.
41. Vickrey, W. S. (1969). Congestion theory and transport investment. The American Economic Review, 59(2), 251-260.
42. Vovsha, P., Petersen, E., & Donnelly, R. (2002). Microsimulation in travel demand modeling: lessons learned from the New York best practice model. Transportation Research Record, 1805, 68-77.
43. Vrtic, M., Froehlich, P., & Axhausen, K. (2003). Schweizerische Netzmodelle für Strassen- und Schienenverkehr. In T. Bieger, C. Lässer, & R. Maggi (Eds.), Jahrbuch 2002/2003 Schweizerische Verkehrswirtschaft (pp. 119-140). St. Gallen: SVWG Schweizerische Verkehrswissenschaftliche Gesellschaft.
44. W3C (2006). eXtensible Markup Language (XML). World Wide Web Consortium (W3C). See www.w3.org/XML.
45. Waddell, P., Borning, A., Noth, M., Freier, N., Becke, M., & Ulfarsson, G. (2003). Microsimulation of urban development and location choices: Design and implementation of UrbanSim. Networks and Spatial Economics, 3(1), 43-67.
46. Wardrop, J. (1952). Some theoretical aspects of road traffic research. Proceedings of the Institute of Civil Engineers, 1, 325-378.
47. Wiedemann, R. (1974). Simulation des Straßenverkehrsflusses. Schriftenreihe Heft 8, Institute for Transportation Science, University of Karlsruhe, Germany.
48. Wolf, J., Schönfelder, S., Samaga, U., Oliveira, M., & Axhausen, K. (2004). Eighty weeks of Global Positioning System traces. Transportation Research Record, 1870, 46-54.