Fundamental Diagram as a Model Input: Direct Movement Equation of Pedestrian Dynamics

  • E. Kirik
  • A. Malyshev
  • E. Popel
Conference paper


Inspiriting by advantages of continuous and discrete approaches to model pedestrian dynamics a new discrete-continuous model SIgMA.DC. was developed This model is of individual type; people (particles) move in a continuous space - in this sense model is continuous, but number of directions where particles may move is a model parameter (limited and predetermined by a user) - in this sense model is discrete. To find current velocity vector we do not describe forces that act on people. To have a value of velocity we use a fundamental diagram data; and probability approach is used to find a direction. Description of the model and some simulation results are presented.



This work is supported by the Integration project of SB RAS 2012–2014, contract 49.


  1. 1.
    Chraibi, M., Seyfried, A., Schadschneider, A. (2010) Generalized centrifugal-force model for pedestrian dynamics // Physical Review E, 82, 046111.CrossRefGoogle Scholar
  2. 2.
    Helbing, D, Farkas, I., Vicsek, T. (2000) Simulating dynamical features of escape panic // Nature 407, 487–490.CrossRefGoogle Scholar
  3. 3.
    Kholshevnikov, V.V., Samoshin, D.A. (2009) Evacuation and human behavior in fire, Moscow, Academy of State Fire Service, EMERCOM of Russia, 212 p. (Rus.)Google Scholar
  4. 4.
    Kholshevnikov, V.V. (2011) Forecast of human behaviour during fire evacuation // In the book “Emergency evacuation of people from buildings” (EMEVAC’2011 Proceedings), Warsaw: Belstudio, 139–153.Google Scholar
  5. 5.
    Kirik, E., Yurgel’yan, T., Krouglov D. (2010) On Influencing of a Space Geometry on Dynamics of Some CA Pedestrian Movement Model // Lecture Notes in Computer Science, V. 6350, Cellular Automata, 474–479.Google Scholar
  6. 6.
    Kirik, E., T. Yurgel'yan, A. Malyshev (2011). On discrete-continuous stochastic floor field pedestrian dynamics model SIgMA.DC // In the book “Emergency evacuation of people from buildings” (EMEVAC`2011 Proceedings), Warsaw: Belstudio, 155–161.Google Scholar
  7. 7.
    Kirik, E., Yurgel'yan, T., Krouglov, D. (2011) On realizing the shortest time strategy in a CA FF pedestrian dynamics model // Cybernetics and Systems, vol.42:01, 1–15.Google Scholar
  8. 8.
    Parzen, E. (1962) On estimation of probability Density Function // Ann.Math. Stat., Vol.33, 1065–1076.Google Scholar
  9. 9.
    Predtechenskii, V.M., Milinskii, A.I. (1978) Planing for foot traffic flow in buildings. American Publishing, New Dehli. Translation of: Proektirovanie Zhdanii s Uchetom organizatsii Dvizheniya Lyudskikh potokov, Stroiizdat Publisher, Moscow, 1969.Google Scholar
  10. 10.
    Rogsch, C. Vergleichende Untersuchungen zur dynamischen Simulation von Personenströmen, Diploma thesis of the University of Wuppertal and the Research Center Julich, 2005.Google Scholar
  11. 11.
    Schadschneider, A., Klingsch, W., Kluepfel, H., Kretz, T., Rogsch, C., Seyfried, A. (2009) Evacuation Dynamics: Empirical Results, Modeling and Applications. Encyclopedia of Complexity and System Science. Springer.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Institute of Computational Modelling SB RASKrasnoyarskRussia
  2. 2.Siberian Federal UniversityKrasnoyarskRussia

Personalised recommendations