Geoscience Reference
In-Depth Information
The main contribution of this chapter is that two methods are proposed and im-
plemented to enhance the performance of the agent-based travel demand simulation
MATSim. This is achieved by refining the micro-simulation and by parallelizing the
processing of its output. As a result of these performance improvements, larger runs
can be simulated in less time and using fewer CPUs/cores than possible before.
Experiments show that, through the proposed changes, the runtime of the current
Java-based micro-simulation is improved by a factor of four and more, depending
on the scenario. As MATSim is aimed at the simulation of large-scale scenarios and
simulation runs of the whole of Switzerland are planned in the near future on high-
resolution networks, it is shown that the computational time for the whole MATSim
run is reduced by a factor of around 3 to about 4.5 h per iteration.
While this is a significant performance enhancement, further improvements of
various modules of the MATSim simulation are also proposed, especially with
regards to the parallelization of the micro-simulation.
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
Park-
standswahl. 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 microsim-
ulation. Transp Res Rec 2003:35-40
Charypar D, Axhausen KW, Nagel K (2007b) An event-driven parallel queue-based microsimula-
tion 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
Search WWH ::
Custom Search