Counterflow Extension for the F.A.S.T.-Model

  • Tobias Kretz
  • Maike Kaufman
  • Michael Schreckenberg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5191)


The F.A.S.T. (Floor field and Agent based Simulation Tool) model is a microscopic model of pedestrian dynamics [1], which is discrete in space and time [2,3]. It was developed in a number ofmore or less consecutive steps from a simple CA model [4,5,6,7,8,9,10]. This contribution is a summary of a study [11] on an extension of the F.A.S.T-model for counterflow situations. The extensions will be explained and it will be shown that the extended F.A.S.T.-model is capable of handling various counterflow situations and to reproduce the well known lane formation effect.


Cellular Automaton Fundamental Diagram Evacuation Dynamics Cellular Automaton Approach Pedestrian Dynamics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Schadschneider, A., Klingsch, W., Klüpfel, H., Kretz, T., Rogsch, C., Seyfried, A.: Evacuation Dynamics: Empirical Results, Modeling and Applications. In: Meyers, R.A. (ed.) Encyclopedia of Complexity and System Science, Springer, Heidelberg (to be published, 2009); arXiv:0802.1620v1Google Scholar
  2. 2.
    Kretz, T., Schreckenberg, M.: The F.A.S.T.-Model. In: El Yacoubi., et al. (eds.) [27], pp. 712–715Google Scholar
  3. 3.
    Kretz, T.: Pedestrian Traffic - Simulation and Experiments. PhD thesis, Universität Duisburg-Essen (2007)Google Scholar
  4. 4.
    Burstedde, C., Klauck, K., Schadschneider, A., Zittarz, J.: Simulation of pedestrian dynamics using a 2-dimensional cellular automaton. Phys. A 295, 507 (2001)zbMATHCrossRefGoogle Scholar
  5. 5.
    Kirchner, A., Schadschneider, A.: Cellular Automaton Simulations of Pedestrian Dynamics and Evacuation Processes. In: Fukui, et al. (eds.) [25], pp. 531–536Google Scholar
  6. 6.
    Kirchner, A., Schadschneider, A.: Simulation of Evacuation Processes Using a Bionics-inspired Cellular Automaton Model for Pedestrian Dynamics. Phys. A 312(1-2), 260–276 (2002)zbMATHCrossRefGoogle Scholar
  7. 7.
    Schadschneider, A.: Cellular Automaton Approach to Pedestrian Dynamics - Theory. In: Schreckenberg, Sharma (eds.) [24], pp. 76–85Google Scholar
  8. 8.
    Schadschneider, A.: Bionics-Inspired Cellular Automaton Model for Pedestrian Dynamics. In: Fukui, et al. (eds.) [25], pp. 499–509Google Scholar
  9. 9.
    Kirchner, A., Nishinari, K., Schadschneider, A.: Friction Effects and Clogging in a Cellular Automaton Model for Pedestrian Dynamics. PRE 67(056122) (2003)Google Scholar
  10. 10.
    Nishinari, K., Kirchner, A., Namazi, A., Schadschneider, A.: Extended Floor Field CA Model for Evacuation Dynamics. IEICE Trans. Inf. & Syst. E87-D, 726–732 (2004)Google Scholar
  11. 11.
    Kaufman, M.: Lane Formation in Counterflow Situations of Pedestrian Traffic. Master’s thesis. Universität Duisburg-Essen (2007)Google Scholar
  12. 12.
    Muramatsu, M., Irie, T., Nagatani, T.: Jamming transition in pedestrian counterflow. Phys. A 267, 487–498 (1999)CrossRefGoogle Scholar
  13. 13.
    Helbing, D., Farkas, I.J., Vicsek, T.: Freezing by Heating in a Driven Mesoscopic System. Phys. Rev. Lett. 84, 1240–1243 (2000)CrossRefGoogle Scholar
  14. 14.
    Muramatsu, M., Nagatani, T.: Jamming transition in two-dimensional pedestrian traffic. Phys. A 275, 281–291 (2000)CrossRefGoogle Scholar
  15. 15.
    Blue, V.J., Adler, J.L.: Cellular Automata Microsimulation of Bi-Directional Pedestrian Flows. TRR, TRB 1678, 135–141 (2000)Google Scholar
  16. 16.
    Schadschneider, A., Kirchner, A., Nishinari, K.: CA Approach to Collective Phenomena in Pedestrian Dynamics. In: Bandini, et al. (eds.) [26], pp. 239–248Google Scholar
  17. 17.
    Tajima, Y., Takimoto, K., Nagatani, T.: Pattern formation and jamming transition in pedestrian counter flow. Phys. A 313, 709–723 (2002)zbMATHCrossRefMathSciNetGoogle Scholar
  18. 18.
    Isobe, M., Adachi, T., Nagatani, T.: Experiment and simulation of pedestrian counter flow. Phys. A 336, 638–650 (2004)CrossRefGoogle Scholar
  19. 19.
    John, A., Schadschneider, A., Chowdhury, D., Nishinari, K.: Collective effects in traffic on bi-directional ant trails. J. Theor. Biol. 231, 279–285 (2004)CrossRefMathSciNetGoogle Scholar
  20. 20.
    Nagai, R., Fukamachi, M., Nagatani, T.: Experiment and simulation for counter flow of people going on all fours. Phys. A 358, 516–528 (2005)CrossRefGoogle Scholar
  21. 21.
    Kretz, T., Wölki, M., Schreckenberg, M.: Characterizing correlations of flow oscillations at bottlenecks. JSTAT, P02005 (2006)Google Scholar
  22. 22.
    Kretz, T., Grünebohm, A., Kaufman, M., Mazur, F., Schreckenberg, M.: Experimental study of pedestrian counterflow in a corridor. JSTAT, P10001 (2006)Google Scholar
  23. 23.
    Blue, V.J., Adler, J.L.: Cellular Automata Microsimulation For Modeling Bi-Directional Pedestrian Walkways. TRB, 35(293) (2001)Google Scholar
  24. 24.
    Schreckenberg, M., Sharma, S.D. (eds.): Pedestrian and Evacuation Dynamics. Springer, Heidelberg (2002)zbMATHGoogle Scholar
  25. 25.
    Fukui, M., Sugiyama, Y., Schreckenberg, M., Wolf, D.E. (eds.): Traffic and Granular Flow 2001. Springer, Heidelberg (2003)zbMATHGoogle Scholar
  26. 26.
    Bandini, S., Chopard, B., Tomassini, M. (eds.): ACRI 2002. LNCS, vol. 2493. Springer, Heidelberg (2002)zbMATHGoogle Scholar
  27. 27.
    El Yacoubi, S., Chopard, B., Bandini, S. (eds.): ACRI 2006. LNCS, vol. 4173. Springer, Heidelberg (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Tobias Kretz
    • 1
    • 3
  • Maike Kaufman
    • 2
    • 3
  • Michael Schreckenberg
    • 3
  1. 1.PTV AGKarlsruheGermany
  2. 2.Robotics Research Group – Dept. of Engineering ScienceUniversity of OxfordOxfordUK
  3. 3.Physics of Transport and TrafficUniversity of Duisburg-EssenDuisburgGermany

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