Abstract
In contrast to aggregated macroscopic models of traffic simulation, multi-agent microscopic models, such as MATSim, enable modeling of individual behavior and facilitate more detailed traffic analysis. However, such detailed modeling also leads to an increased computational burden, such that simulation performance becomes critical.
This paper looks specifically at the MATSim simulation framework and proposes several ways to improve its performance. This is achieved through a combination of several approaches, including reducing disk access, decoupling computational tasks, and making use of parallel computing. Additionally, for the traffic simulation, an event-based model is adopted instead of a fixed-increment time advance approach.
Experiments show that by applying these methods, a simulation speedup of four times and more is achieved (depending on the scenario) when compared to the current Java micro-simulation in MATSim.
Initial simulation experiments on a high-resolution navigation network of Switzerland – containing around one million roads and 7.3 million agents – demonstrate that real-world scenarios can now be executed in around one-and-a-half weeks using the improved model. Ways to further shorten the computational time of MATSim are also described.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Have been conducted in 2010 (see, Meister et al. 2010)
References
Amdahl G (1967) Validity of the single processor approach to achieving large scale computing capabilities. In: Spring joint computer conference. ACM, New York, pp 483–485
Axhausen KW (1988) Eine ereignisorientierte simulation von Aktivitätenketten zur Parkstandswahl. Ph.D. thesis, University of Karlsruhe, Karlsruhe (in German)
Axhausen KW, Gärling T (1992) Activity based approaches to travel analysis: conceptual frameworks, models and research problems. Transp Rev 12(4):323–341
Balmer M, Rieser M, Meister K, Charypar D, Lefebvre N, Nagel K (2009) MATSim-T: architecture and simulation times. In: Bazzan ALC, Klügl F (eds) Multi-agent systems for traffic and transportation engineering. Information Science Reference, Hershey, pp 57–78
Barceló J, Ferrer JL, García D, Florian M, Le Saux E (1998) Parallelization of microscopic traffic simulation for ATT systems analysis. In: Equilibrium and advanced transportation modelling. Springer, New York, pp 1–26
Ben-Akiva M, Bierlaire M, Koutsopoulos H, Mishalani R (1998) DynaMIT: a simulation-based system for traffic prediction. In: DACCORS short term forecasting workshop, The Netherlands, February 1998.
Cayford R, Wie-Hua L, Daganzo CF (1997) The NETCELL simulation package: technical description. California PATH research report UCB–ITS–PRR–97–23, University of California, Berkeley, CA
Cetin N (2005) Large-scale parallel graph-based simulations. Ph.D. thesis, ETH Zurich, Zurich.
Charypar D, Axhausen KW, Nagel K (2007a) An event-driven queue-based traffic flow microsimulation. Transp Res Rec 2003:35–40
Charypar D, Axhausen KW, Nagel K (2007b) An event-driven parallel queue-based microsimulation for large scale traffic scenarios. In: The 11th world conference on transportation research, Berkeley, June 2007
Ciari F, Balmer M, Axhausen KW (2008) Concepts for a large scale car-sharing system: modelling and evaluation with an agent-based approach, Arbeitsberichte Verkehrs und Raumplanung, 517. IVT, ETH Zürich, Zürich
de Dios Ortúzar J, Willumsen LG (2011) Modelling transport, 4th edn. Wiley, Chichester
Fellendorf M, Vortisch P (2010) Microscopic traffic flow simulator VISSIM. In: Barceló J (ed) Fundamentals of traffic simulation. Springer, New York, pp 63–93
Hahne E (1991) Round-Robin scheduling for max-fin fairness in data networks. IEEE J Select Areas Commun 9(7):1024–1039
Holland JH (1992) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT Press, Cambridge
Lea D (1999) Concurrent programming in Java: design principles and patterns. Addison-Wesley Longman Publishing Co., Inc., Boston
Lindholm T, Yellin F (1999) Java virtual machine specification. Addison-Wesley Longman Publishing Co., Inc., Boston
MATSim (2009) Multi agent transportation simulation toolkit. Webpage: http://www.matsim.org, August 2009
Meister K, Balmer M, Axhausen KW, Nagel K (2006) planomat: a comprehensive scheduler for a large-scale multi-agent transportation simulation. Paper presented at the 11th international conference on travel behaviour research, Kyoto, August 2006
Meister K, Balmer M, Ciari F, Horni A, Rieser M, Waraich RA, Axhausen KW (2010) Large-scale agent-based travel demand optimization applied to Switzerland, including mode choice. In: The 12th world conference on transportation research, Lisbon, July 2010
Nagel K, Rickert M (2001) Parallel implementation of the TRANSIMS micro-simulation. Parallel Comput 27(12):1611–1639
NAVTEQ (2009) NAVTEQ. Webpage: http://www.navteq.com. June 2009
Nökel K, Schmidt M (2002) Parallel DYNEMO: meso-scopic traffic flow simulation on large networks. Netw Spatial Econ 2(4):387–403
OMNeT++ (2009) OMNeT++. Webpage: http://www.omnetpp.org
Raney B, Cetin N, Völlmy A, Vrtic M, Axhausen K, Nagel K (2003) An agent-based microsimulation model of Swiss travel: first results. Netw Spatial Econ 3(1):23–41
Snir M, Otto S, Walker D, Dongarra J, Huss-Lederman S (1995) MPI: the complete reference. MIT Press, Cambridge, MA
Strippgen D, Nagel K (2009) Using common graphics hardware formulti-agent traffic simulation with cuda. In: Simutools’09: proceedings of the 2nd international conference on simulation tools and techniques. ICST, Brussels, pp 1–8
Waraich RA, Galus MD, Dobler C, Balmer M, Andersson G, Axhausen KW (2009) Plug-in hybrid electric vehicles and smart grid: investigations based on a micro-simulation. In: Proceedings of the 12th international conference on travel behaviour research (IATBR), Jaipur, December 2009
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Waraich, R.A., Charypar, D., Balmer, M., Axhausen, K.W. (2015). Performance Improvements for Large-Scale Traffic Simulation in MATSim. In: Helbich, M., Jokar Arsanjani, J., Leitner, M. (eds) Computational Approaches for Urban Environments. Geotechnologies and the Environment, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-11469-9_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-11469-9_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11468-2
Online ISBN: 978-3-319-11469-9
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)