Multi-Agent-Based Simulation for Analysis of Transport Policy and Infrastructure Measures

  • Johan Holmgren
  • Linda Ramstedt
  • Paul Davidsson
  • Jan A. Persson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7580)

Abstract

In this paper we elaborate on the usage of multi-agent-based simulation (MABS) for quantitative impact assessment of transport policy and infrastructure measures. We provide a general discussion on how to use MABS for freight transport analysis, focusing on issues related to input data management, validation and verification, calibration, output data analysis, and generalization of results. The discussion is built around an agent-based transport chain simulation tool called TAPAS (Transportation And Production Agent-based Simulator) and a simulation study concerning a transport chain around the Southern Baltic Sea.

Keywords

Multi-agent-based simulation MABS Multi-agent systems Supply chain simulation Freight transportation Transport policy assessment 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Button, K.: Transport Economics, 2nd edn. Edward Elgar Publishing Limited, Glos (1997)Google Scholar
  2. 2.
    Davidsson, P., Holmgren, J., Persson, J.A., Ramstedt, L.: Multi agent based simulation of transport chains. In: Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), May 12-16, pp. 1153–1160. International Foundation for Autonomous Agents and Multiagent Systems, Estoril (2008)Google Scholar
  3. 3.
    de Jong, G., Ben-Akiva, M.: A micro-simulation model of shipment size and transport chain choice. Transportation Research Part B 41(9), 950–965 (2007)CrossRefGoogle Scholar
  4. 4.
    European Commission: White paper - European transport policy for 2010: time to decide. Tech. rep., Luxemburg (2001)Google Scholar
  5. 5.
    Friberg, G., Flack, M., Hill, P., Johansson, M., Vierth, I., McDaniel, J., Lundgren, T., Hesselborn, P., Bångman, G.: Kilometerskatt för lastbilar - Effekter på näringar och regioner. Redovisning av ett regeringsuppdrag i samverkan med ITPS. Report 2007:2, Swedish Institute for Transport and Communications Analysis, SIKA (2007)Google Scholar
  6. 6.
    Gambardella, L., Rizzoli, A., Funk, P.: Agent-based planning and simulation of combined rail/road transport. Simulation 78(5), 293–303 (2002)CrossRefGoogle Scholar
  7. 7.
    Holmgren, J.: An extended EastWest Transport Corridor (EWTC) scenario (2011), http://www.bth.se/tek/jhm.nsf/attachments/eewtc_pdf/$file/eewtc.pdf
  8. 8.
    Holmgren, J., Davidsson, P., Persson, J.A., Ramstedt, L.: TAPAS: A multi-agent-based model for simulation of transport chains. Simulation Modelling Practice and Theory 23, 1–18 (2012)CrossRefGoogle Scholar
  9. 9.
    Kelton, W.D., Barton, R.R.: Experimental design for simulation. In: Proceedings of the 2003 Winter Simulation Conference, December 7-10, pp. 59–65. IEEE, New Orleans (2003)Google Scholar
  10. 10.
    Kleijnen, J.P.C.: An overview of the design and analysis of simulation experiments for sensitivity analysis. European Journal of Operational Research 164(2), 287–300 (2005)MATHCrossRefGoogle Scholar
  11. 11.
    Kleijnen, J.P.C.: Design of experiments: overview. In: Proceedings of the 2008 Winter Simulation Conference, December 7-10, pp. 479–488. IEEE, Miami (2008)CrossRefGoogle Scholar
  12. 12.
    Law, A.M.: Statistical analysis of simulation output data: the practical state of the art. In: Proceedings of the 2007 Winter Simulation Conference, December 9-12, pp. 77–83. IEEE, Washington, DC (2007)CrossRefGoogle Scholar
  13. 13.
    Law, A.M., Kelton, W.D.: Simulation modelling and analysis, 3rd edn. McGraw-Hill, Singapore (2000)Google Scholar
  14. 14.
    Liedtke, G.: Principles of micro-behavior commodity transport modeling. Transportation Research Part E 45(5), 795–809 (2009)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Rich, J., Bröcker, J., Hansen, C.O., Korchenewych, A., Nielsen, O.A., Vuk, G.: Report on scenario, traffic forecast and analysis of traffic on the TEN-T, taking into consideration the external dimension of the union - TRANS-TOOLS version 2; Model and data improvements. Tech. rep., Copenhagen, Denmark (2009)Google Scholar
  16. 16.
    Sapsford, R., Jupp, V. (eds.): Data collection and analysis, 2nd edn. SAGE Publications Ltd., Chennai (2006)Google Scholar
  17. 17.
    Sargent, R.G.: Verification and validation of simulation models. In: Proceedings of the 2005 Winter Simulation Conference, December 4-7, pp. 130–143. IEEE, Orlando (2005)CrossRefGoogle Scholar
  18. 18.
    SIKA: Vilken koldioxidskatt krävs för att nå framtida utsläppsmål? PM 2008:4, Swedish Institute for Transport and Communications Analysis, SIKA (2008)Google Scholar
  19. 19.
    Swahn, H.: The Swedish national model systems for goods transport SAMGODS - a brief introductory overview. SAMPLAN Report 2001:1, Swedish Institute for Transport and Communications Analysis, SIKA (2001)Google Scholar
  20. 20.
    Tavasszy, L., Smeenk, B., Ruijgrok, C.: A DSS for modelling logistic chains in freight transport policy analysis. International Transactions in Operational Research 5(6), 447–459 (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Johan Holmgren
    • 1
  • Linda Ramstedt
    • 2
  • Paul Davidsson
    • 3
  • Jan A. Persson
    • 3
  1. 1.School of ComputingBlekinge Institute of TechnologyKarlshamnSweden
  2. 2.VecturaSolnaSweden
  3. 3.School of TechnologyMalmö UniversityMalmöSweden

Personalised recommendations