Skip to main content

Anticipatory Traffic Forecast Using Multi-Agent Techniques

  • Conference paper
Traffic and Granular Flow ’99

Abstract

In this contribution, intelligent transportation systems (ITS) and their impact on traffic systems are discussed. Although traffic forecast offers the possibility to rearrange the temporal distribution of traffic patterns, it suffers from a fundamental problem because the reaction of the driver to the forecast is a priori unknown. On the other hand the behaviour of drivers can have a serious impact on the quality of a traffic forecast since it can result in a feedback - an anticipatory forecast is needed. To include such effects we propose a two-layered agent architecture for modelling drivers’ behaviour in more detail. The layers distinguish different tasks of road users.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J. L. Adler and V.J. Blue,Toward the design of intelligent traveler information systems, Transpn. Res. C 6, 157 (1998).

    Article  Google Scholar 

  2. W. Barfield and T.A. Dingus, Human Factors in Intelligent Transportation Systems (Lawrence Erlbaum Associates Inc., Mahwah, New Jersey, 1998).

    Google Scholar 

  3. ITS International, Proc. of the 6th World Congress on Intelligent Transport Systems (ITS World Congress, CD-ROM, Toronto, 1999).

    Google Scholar 

  4. H. Gorr, Die Logik der individuellen Verkehrsmittelwahl (Focus Verlag, Giefien, 1996).

    Google Scholar 

  5. B.S. Kerner, H. Rebhorn, and M. Aleksic, Forecasting of traffic congestion, in: these proceedings.

    Google Scholar 

  6. B. Schürmann, Application of neural networks for predictive and control purposes, in: these proceedings.

    Google Scholar 

  7. J. Bottom, M. Ben-Akiva, M. Bierlaire, I. Chabini, H. Koutsopoulos, and Q. Yang, Investigation of route guidance generation issues by simulation with DynaMIT, in: Proc. of the 14th Int. Symp. on Transp. and Traffic Theory, A. Ceder, (Ed.), pp. 577–600 (Pergamon, Amsterdam, 1999).

    Google Scholar 

  8. W.B. Arthur, Inductive reasoning and bounded rationality, Am. Econ. Rev. 84, 406 (1994).

    Google Scholar 

  9. D. Challet and Y.-C. Zhang, Emergence of cooperation and organization in an evolutionary game, Physica A 246, 407–418 (1997).

    Article  Google Scholar 

  10. A.L.C. Bazzan, R.H. Bordini, G.K. Andrioti, R.M. Vicari, and J. Wahle, Wayward agents in a commuting scenario (personalites in the minority game), in: Proc. of the 4th Int. Conf. MultiAgent Systems (ICMAS’2000), accepted, IEEE Computer Society.

    Google Scholar 

  11. R. Berkemer, Modal split and social dilemmas, in: these proceedings.

    Google Scholar 

  12. R. Nagel, Unraveling in guessing games: An experimental study, Am. Econ. Rev. 85, 1013–1026 (1995).

    Google Scholar 

  13. A.L.C. Bazzan, J. Wahle, and F. Klügl, Agents in traffic modelling - from reactive to social behaviour, in: KI-99: Advances in Artificial Intelligence, W. Burgard, T. Christaller, and A.B. Cremers, (Eds.), (LNAI 1701, Springer, Berlin, 1999).

    Google Scholar 

  14. K. Nagel and M. Schreckenberg, A cellular automaton model for freeway traffic, J. Phys. I France 2, 2221 (1992).

    Article  Google Scholar 

  15. F. Klügl and F. Puppe, The multi-agent simulation environment SeSAM, in: Simulation in wissensbasierten Systemen (Universtiät Paderborn, 1998).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wahle, J., Bazzan, A.L.C., Klügl, F., Schreckenberg, M. (2000). Anticipatory Traffic Forecast Using Multi-Agent Techniques. In: Helbing, D., Herrmann, H.J., Schreckenberg, M., Wolf, D.E. (eds) Traffic and Granular Flow ’99. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59751-0_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-59751-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-64109-1

  • Online ISBN: 978-3-642-59751-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics