Agent-based simulation of travel demand: Structure and computational performance of MATSim-T

The model toolkit MATSim-T provides a variety of tools and resulting approaches to model travel demand and traffic flow and their interactions. The currently preferred configuration is presented in this paper together with detailed information about its computational performance. The application is small in comparison with the abilities of the system, but as computing times scale approximately linearly for the system it gives an idea of how the system can be used for practical planning studies: a 10% sample of the travellers in the Greater Zurich Area (190’000 agents). The outlook highlights the next steps of the development. Dieser Aufsatz gibt eine knappe Darstellung des Modellsystems MATSim-T und einer Anwendung in Grossraum Zurich. Die Betonung liegt auf den erreichbaren Rechenzeiten und damit auf der Anwendbarkeit fur Planungsstudien. Der Ausblick zeigt auf, in welchen Teilen das Modell weiter verbessert werden kann und soll.

[1]  M. D. McKay,et al.  Creating synthetic baseline populations , 1996 .

[2]  Hani S. Mahmassani,et al.  Dynamic Network Traffic Assignment and Simulation Methodology for Advanced System Management Applications , 2001 .

[3]  Konrad Meister,et al.  Erzeugung kompletter Aktivitätenpläne für Haushalte mit genetischen Algorithmen , 2004 .

[4]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[5]  S. Fujii,et al.  TWO COMPUTATIONAL PROCESS MODELS OF ACTIVITY-TRAVEL CHOICE. , 1998 .

[6]  Fabrice Marchal,et al.  Computation of Location Choice of Secondary Activities in Transportation Todels with Cooperative Agents , 2005, Applications of Agent Technology in Traffic and Transportation.

[7]  Fabrice Marchal,et al.  Real Cases Applications of the Fully Dynamic METROPOLIS Tool-Box: An Advocacy for Large-Scale Mesoscopic Transportation Systems , 2002 .

[8]  Kay W. Axhausen,et al.  A Dynamic Understanding of Travel Demand: A Sketch , 2005 .

[9]  Francesco Ciari,et al.  Mobility tool ownership and mode choice decision processes in multi-agent transportation simulation; 7th Swiss Transport Research Conference; Working paper / IVT; , 2007 .

[10]  Kai Nagel,et al.  Parallel Queue Model Approach to Traffic Microsimulations , 2003 .

[11]  Michael Schreckenberg,et al.  A cellular automaton model for freeway traffic , 1992 .

[12]  Kay W. Axhausen,et al.  An event-driven queue-based microsimulation of traffic flow , 2006 .

[13]  K. Nagel.  Computational methods for multi-agent simulations of travel behavior , 2003 .

[14]  Kay W. Axhausen,et al.  An Agent-Based Microsimulation Model of Swiss Travel: First Results , 2003 .

[15]  W. Arthur.  Inductive Reasoning, Bounded Rationality and the Bar Problem , 1994 .

[16]  Ryuichi Kitamura,et al.  Activity-based Travel Analysis , 1985 .

[17]  C. M. Sperberg-McQueen,et al.  Extensible markup language , 1997 .

[18]  T. Arentze,et al.  Social Networks, Social Interactions, and Activity-Travel Behavior: A Framework for Microsimulation , 2008 .

[19]  Kay W. Axhausen,et al.  Agent-Based Demand-Modeling Framework for Large-Scale Microsimulations , 2006 .

[20]  Eric van Damme,et al.  Non-Cooperative Games , 2000 .

[21]  Kw Axhausen,et al.  Neue Modellansätze der Verkehrs-nachfragesimulati- on: Entwicklungslinien, Stand der Forschung, For- schungsperspektiven , 2006 .

[22]  K. Axhausen.  Moving through nets: The physical and social dimensions of travel : selected papers from the 10th International Conference on Travel Behaviour Research , 2007 .

[23]  Piet H. L. Bovy,et al.  Modelling route choice behaviour in multi-modal transport networks , 2005 .

[24]  Kay W. Axhausen,et al.  Social networks and travel: Some hypotheses , 2003 .

[25]  Mark Bradley,et al.  White Paper for the Conference on Innovations in Travel Demand Modeling, Austin, TX, May 2006 A Summary of Design Features of Activity-Based Microsimulation Models for U.S. MPOs , 2006 .

[26]  Michael Bernard,et al.  Verfahren zur Berücksichtigung der Zuverlässigkeit in Evaluationen , 2007 .

[27]  David A. Hensher,et al.  Travel behaviour research : the leading edge , 2001 .

[28]  Nurhan Çetİn,et al.  Large-scale parallel graph-based simulations , 2005 .

[29]  Kay W. Axhausen.  Neue Modellansätze der Verkehrsnachfragesimulation , 2006 .

[30]  W. Vickrey.  Congestion Theory and Transport Investment , 1969 .

[31]  Yixuan Li,et al.  Large-Scale Dynamic Traffic Assignment: Implementation Issues and Computational Analysis , 2004 .

[32]  Kay W. Axhausen,et al.  Simulating Activity Chains: German Approach , 1989 .

[33]  Kay W. Axhausen,et al.  An improved replanning module for agent-based micro simulations of travel behavior , 2005 .

[34]  Yosef Sheffi,et al.  Urban Transportation Networks: Equilibrium Analysis With Mathematical Programming Methods , 1985 .

[35]  Kai Nagel,et al.  Issues of Simulation-Based Route Assignment , 1999 .

[36]  Kay W. Axhausen,et al.  Eine ereignisorientierte Simulation von Aktivitätenketten zur Parkstandswahl , 1989 .

[37]  Kai Nagel,et al.  Truly Agent-Based Strategy Selection for Transportation Simulations , 2003 .

[38]  Christopher L. Barrett,et al.  Using Microsimulation Feedback For Trip Adaptation For Realistic Traffic In Dallas , 1997, adap-org/9706002.

[39]  Terence Kelly,et al.  Relaxation Criteria for Iterated Traffic Simulations , 1998 .

[40]  Athanasios K. Ziliaskopoulos,et al.  Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future , 2001 .

[41]  David Charypar,et al.  Q-Learning for Flexible Learning of Daily Activity Plans , 2005 .

[42]  Toshiyuki Yamamoto,et al.  Florida activity mobility simulator - Overview and preliminary validation results , 2005 .

[43]  Kay W. Axhausen,et al.  planomat: a comprehensive scheduler for a large-scale multi-agent transportation simulation , 2006 .

[44]  Josef Hofbauer,et al.  The theory of evolution and dynamical systems , 1988 .

[45]  Harry Timmermans,et al.  ALBATROSS: Multiagent, Rule-Based Model of Activity Pattern Decisions , 2000 .

[46]  Phil. Goodwin,et al.  Some principles of dynamic analysis of travel behaviour , 1990 .

[47]  Kai Nagel,et al.  Adjustments of Activity Timing and Duration in an Agent-Based Traffic Flow Simulation , 2005 .

[48]  Francesco Ciari,et al.  A new mode choice model for a multi-agent transport simulation , 2008 .

[49]  Torsten Hägerstraand.  WHAT ABOUT PEOPLE IN REGIONAL SCIENCE , 1970 .

[50]  Marcel Rieser,et al.  Network breakdown “at the edge of chaos” in multi-agent traffic simulations , 2008 .

[51]  K. Axhausen,et al.  An agent model of social network and travel behavior interdependence , 2006 .

[52]  Fabrice Marchal,et al.  Modeling Location Choice of Secondary Activities with a Social Network of Cooperative Agents , 2005 .

[53]  J. G. Wardrop,et al.  Some Theoretical Aspects of Road Traffic Research , 1952 .

[54]  Milenko Vrtic,et al.  Schweizerische Netzmodelle für den Strassen- und Schienenverkehr , 2003 .

[55]  Matthew J. Roorda,et al.  Prototype Model of Household Activity-Travel Scheduling , 2003 .

[56]  D. McFadden,et al.  URBAN TRAVEL DEMAND - A BEHAVIORAL ANALYSIS , 1977 .

[57]  C. Gawron,et al.  An Iterative Algorithm to Determine the Dynamic User Equilibrium in a Traffic Simulation Model , 1998 .

[58]  Kay W. Axhausen,et al.  Implementing activity-based models: accelerating the replanning process of agents using an evolution strategy , 2006 .

[59]  F. Chapin.  Human activity patterns in the city , 1974 .

[60]  Kay W. Axhausen,et al.  A simultaneous simulation of activity chains , 1990 .

[61]  Ryuichi Kitamura,et al.  Micro-simulation of daily activity-travel patterns for travel demand forecasting , 2000 .

[62]  Francesco Ciari,et al.  Anwendung eines agentenbasierten Modells der Verkehrsnachfrage auf die Schweiz; ; Strassenverkehrstechnik; , 2009 .

[63]  Kai Nagel,et al.  Iterative route planning for large-scale modular transportation simulations , 2004, Future Gener. Comput. Syst..

[64]  B. Lenntorp.  Paths in space-time environments : a time-geographic study of movement possibilities of individuals , 1976 .

[65]  Peter Vovsha,et al.  Microsimulation in Travel Demand Modeling: Lessons Learned from the New York Best Practice Model , 2002 .

[66]  F. Webster,et al.  Overview of an international study to compare models and evaluate land‐use and transport policies , 1991 .

[67]  Kay W. Axhausen,et al.  A GA-based household scheduler , 2005 .

[68]  K Sigmund,et al.  The theory of evolution and dynamic systems mathematical aspects of selection , 1984 .

[69]  M. Ben-Akiva,et al.  DEMONSTRATION OF AN ACTIVITY-BASED MODEL FOR PORTLAND , 1999 .

[70]  Yoram Shiftan,et al.  The analysis of travel and emission impacts of travel demand management strategies using activity-based models , 2002 .

[71]  Brian Gardner,et al.  Incorporating Feedback in Travel Forecasting , 1997 .

[72]  P. Jones,et al.  Understanding Travel Behaviour , 1983 .

[73]  Peter Jones,et al.  Developments in dynamic and activity-based approaches to travel analysis , 1990 .

[74]  Chandra R. Bhat,et al.  Comprehensive Econometric Microsimulator for Daily Activity-Travel Patterns , 2004 .

[75]  Nicolas Lefebvre,et al.  Fast shortest path computation in time-dependent traffic networks , 2007 .

[76]  Marcel Rieser,et al.  Agent-Oriented Coupling of Activity-Based Demand Generation with Multiagent Traffic Simulation , 2007 .

[77]  Kay W. Axhausen,et al.  Event-Driven Queue-Based Traffic Flow Microsimulation , 2007 .

[78]  Eric J. Miller,et al.  ILUTE: An Operational Prototype of a Comprehensive Microsimulation Model of Urban Systems , 2005 .

[79]  K. Nagel,et al.  Generating complete all-day activity plans with genetic algorithms , 2005 .

[80]  Marcel Rieser,et al.  Truly agent-oriented coupling of an activity-based demand generation with a multi-agent traffic simulation , 2002 .

[81]  R M Pendyala.  PHASED IMPLEMENTATION OF A MULTIMODAL ACTIVITY-BASED TRAVEL DEMAND MODELING SYSTEM IN FLORIDA. VOLUME II: FAMOS USERS GUIDE , 2004 .

[82]  Fan Yang,et al.  An evolutionary game theory approach to the day-to-day traffic dynamics , 2005 .

[83]  Bryan Raney,et al.  Learning framework for large-scale multi-agent simulations , 2005 .

[84]  John L. Bowman,et al.  Activity Based Travel Demand Model System with Daily Activity Schedules , 1995 .

[85]  Gunnar Flötteröd,et al.  Enhancing MATSim with capabilities of within-day re-planning , 2007, 2007 IEEE Intelligent Transportation Systems Conference.

[86]  Kai Nagel,et al.  An Improved Framework for Large-Scale Multi-Agent Sim- ulations of Travel Behavior , 2004 .