Analysis of Crowd Dynamics with Laboratory Experiments

Part of the The International Series in Video Computing book series (VICO, volume 11)


For the proper understanding and modelling of crowd dynamics, reliable empirical data is necessary for analysis and verification. Laboratory experiments give us the opportunity to selectively analyze parameters independently of undesired influences and adjust them to high densities seldom seen in field studies. The setup of the experiments, the extraction of the trajectories of the pedestrians and the analysis of the resulting data are discussed.Two strategies for the time-efficient automatic collection of accurate pedestrian trajectories from stereo recordings are presented. One strategy uses markers for detection and the other one is based on a perspective depth field. Measurement methods for quantities like density, velocity and specific flow are compared. The fundamental diagrams from trajectories for different experiments are analyzed.


Assure Pyramid 



This study was performed within the project funded by the German Research Foundation (DFG) KL 1873/1-1 and SE 1789/1-1 and the project Hermes funded by the Federal Ministry of Education and Research (BMBF) Program on “Research for Civil Security – Protecting and Saving Human Life”.


  1. 1.
    Schreckenberg, M., Scharma, S.D. (eds.): Pedestrian and Evacuation Dynamics. Springer, Berlin/Heidelberg (2002)MATHGoogle Scholar
  2. 2.
    Galea, E.R. (ed.): Pedestrian and Evacuation Dynamics. CMS, London (2003)Google Scholar
  3. 3.
    Klingsch, W.W.F., Rogsch, C., Schadschneider, A., Schreckenberg, M. (eds.): Pedestrian and Evacuation Dynamics. Springer Berlin/Heidelberg (2010).
  4. 4.
    Peacock, R.D., Kuligowski, E.D., Averill, J.D. (eds.): Pedestrian and Evacuation Dynamics. Springer, Berlin/Heidelberg (2011). doi:10.1007/978-1-4419-9725-8Google Scholar
  5. 5.
    Grayson, S., Inter Science Communications Limited, Babrauskas, V., Building Research Establishment, UK, National Fire Protection Association, USA, National Institute for Standards & Technology, Building, Fire Research Laboratory, USA, Society of Fire Protection Engineers, USA, SP Technical Institute of Sweden: Interflam 2007: Proceedings of the Eleventh International Conference, no. Bd. 1. Interscience Communications (2007).
  6. 6.
    Predtechenskii, V.M., Milinskii, A.I.: Planning for Foot Traffic Flow in Buildings. Amerind Publishing, New Dehli (1978). Translation of Proekttirovanie Zhdanii s Uchetom Organizatsii Dvizheniya Lyuddskikh Potokov, Stroiizdat Publishers, Moscow, 1969Google Scholar
  7. 7.
    Nelson, H.E., Mowrer, F.W.: In: DiNenno, P.J. (ed.) SFPE Handbook of Fire Protection Engineering, 3rd edn., chap.  14, pp. 367–380. National Fire Protection Association, Quincy (2002)
  8. 8.
    Weidmann, U.: Transporttechnik der Fussgänger. Tech. Rep. Schriftenreihe des IVT Nr. 90, Institut für Verkehrsplanung, Transporttechnik, Strassen- und Eisenbahnbau, ETH Zürich, ETH Zürich (1993). Zweite, ergänzte AuflageGoogle Scholar
  9. 9.
    Thompson, P.A., Marchant, E.W.: Fire Saf. J. 24(2), 131 (1995). doi:10.1016/0379-7112(95)00019-P,
  10. 10.
    TraffGo HT GmbH: Handbuch PedGo 2, PedGo Editor 2 (2005).
  11. 11.
    Kretz, T., Hengst, S., Vortisch, P.: In: Sarvi, M. (ed.) International Symposium of Transport Simulation (ISTS08). Monash University, Melbourne (2008).
  12. 12.
    Hostikka, S., Korhonen, T., Paloposki, T., Rinne, T., Matikainen, K., Heliövaara, S.: Development and validation of fds+evac for evacuation simulations. Tech. Rep. VTT Technical Research Centre of Finland (2008)Google Scholar
  13. 13.
    Schadschneider, A., Klingsch, W., Kluepfel, H., Kretz, T., Rogsch, C., Seyfried, A.: Encyclopedia of Complexity and System Science, vol. 5, chap. Evacuation Dynamics: Empirical Results, Modeling and Applications, pp. 3142–3176. Springer, Berlin/Heidelberg (2009)Google Scholar
  14. 14.
    Seyfried, A., Passon, O., Steffen, B., Boltes, M., Rupprecht, T., Klingsch, W.: Transp. Sci. 43(3), 395 (2009). doi:10.1287/trsc.1090.0263CrossRefGoogle Scholar
  15. 15.
    Liddle, J., Seyfried, A., Steffen, B., Klingsch, W., Rupprecht, T., Winkens, A., Boltes, M.: Microscopic insights into pedestrian motion through a bottleneck, resolving spatial and temporal variations. (2011).
  16. 16.
    Seyfried, A., Portz, A., Schadschneider, A.: In: Bandini, S., Manzoni, S., Umeo, H., Vizzari, G. (eds.) Cellular Automata, 9th International Conference on Cellular Automata for Reseach and Industry, ACRI, Ascoli Piceno, September 2010. Lecture Notes in Computer Science, vol. 6350, pp. 496–505. Springer, Berlin/Heidelberg (2010). doi:10.1007/978-3-642-15979-4_53Google Scholar
  17. 17.
    Zhang, J., Klingsch, W., Schadschneider, A., Seyfried, A.: J. Stat. Mech. Theory Exp. 2012(2), P02002 (2012).
  18. 18.
    Wong, S.C., Leung, W.L., Chan, S.H., Lam, W.H.K., Yung, N.H., Liu, C.Y., Zhang, P.: J. Transp. Eng. 136(3), 234 (2010). doi: 10.1061/(ASCE)TE.1943-5436.0000086 CrossRefGoogle Scholar
  19. 19.
    Liu, X., Song, W., Zhang, J.: Phys. A Stat. Mech. Appl. 388(13), 2717 (2009). doi:10.1016/j.physa.2009.03.017CrossRefGoogle Scholar
  20. 20.
    Fang, Z., Song, W., Zhang, J., Wu, H.: Phys. A Stat. Mech. Appl. 389, 815 (2010). doi:doi:10.1016/j.physa.2009.10.019Google Scholar
  21. 21.
    Ma, J., Song, W.G., Liao, G.X.: Chin. Phys. B 19(12), 128901 (2010). doi:10.1088/1674-1056/19/12/128901CrossRefGoogle Scholar
  22. 22.
    Lam, W.H.K., Lee, J.Y.S., Cheung, C.Y.: Transportation 29, 169 (2002). doi:10.1023/A:1014226416702CrossRefGoogle Scholar
  23. 23.
    Lee, J.Y.S., Lam, W.H.K.: Transp. Res. Rec. 1982, 122 (2006). doi:10.3141/1982-17CrossRefGoogle Scholar
  24. 24.
    Ren-Yong, G., Wong, S.C., Yin-Hua, X., Hai-Jun, H., Lam, W.H.K., Keechoo, C.: Chin. Phys. Lett. 29(6), 068901 (2012). Google Scholar
  25. 25.
    LI Xiang, D.L.Y.: Chin. Phys. Lett. 29(9), 98902 (2012). doi:10.1088/0256-307X/29/9/098902, Google Scholar
  26. 26.
  27. 27.
    Moussaïd, M., Helbing, D., Garnier, S., Johansson, A., Combe, M., Theraulaz, G.: Proc. R. Soc. B 276(1668), 2755 (2009). doi:10.1098/rspb.2009.0405CrossRefGoogle Scholar
  28. 28.
    Jelić, A., Appert-Rolland, C., Lemercier, S., Pettré, J.: Properties of pedestrians walking in line: Stepping behavior Phys. Rev. E 86, 046111 (2012)Google Scholar
  29. 29.
    Moussaid, M., Guillot, E.G., Moreau, M., Fehrenbach, J., Chabiron, O., Lemercier, S., Pettre, J., Appert-Rolland, C., Degond, P., Theraulaz, G.: PLoS Computat. Biol. 8, 1002442 (2012). Article published in PLoS Computational biology. Freely available here: LPT-ORSAY 12–75 LPT-ORSAY 12–75
  30. 30.
    Hoogendoorn, S.P., Daamen, W.: Transp. Sci. 39(2), 147 (2005). doi:10.1287/trsc.1040.0102CrossRefGoogle Scholar
  31. 31.
    Daamen, W., Hoogendoorn, S.: Procedia Eng. 3, 53 (2010). doi:10.1016/j.proeng.2010.07.007, First International Conference on Evacuation Modeling and Management
  32. 32.
    Yanagisawa, D., Kimura, A., Tomoeda, A., Ryosuke, N., Suma, Y., Ohtsuka, K., Nishinari, K.: Phys. Rev. E 80, 036110 (2009)CrossRefGoogle Scholar
  33. 33.
    Yanagisawa, D., Tomoeda, A., Nishinari, K.: Physical Review E 85, 016111+ (2012). doi:10.1103/PhysRevE.85.016111,
  34. 34.
    Nagai, R., Fukamachi, M., Nagatani, T.: Physica A 367, 449 (2006). doi:10.1016/j.physa.2005.11.031,
  35. 35.
    Isobe, M., Adachi, T., Nagatani, T.: Physica A 336, 638 (2004). doi:10.1016/j.physa.2004.01.043CrossRefGoogle Scholar
  36. 36.
    Kretz, T., Grünebohm, A., Schreckenberg, M.: J. Stat. Mech. 10, P10014 (2006). doi:10.1088/1742-5468/2006/10/P10014CrossRefGoogle Scholar
  37. 37.
    Plaue, M., Chen, M., Bärwolff, G., Schwandt, H.: In: Stilla, U., Rottensteiner, F., Mayer, H., Jutzi, B., Butenuth, M. (eds.) Photogrammetric Image Analysis. Lecture Notes in Computer Science, vol. 6952, pp. 285–296. Springer, Berlin/Heidelberg (2011). doi:10.1007/978-3-642-24393-6_24,
  38. 38.
    Seyfried, A., Steffen, B., Klingsch, W., Boltes, M.: J. Stat. Mech. Theory Exp. P10002 (2005). doi:10.1088/1742-5468/2005/10/P10002Google Scholar
  39. 39.
    Chattaraj, U., Seyfried, A., Chakroborty, P.: Adv. Complex Syst. 12(3), 393 (2009). doi:10.1142/S0219525909002209CrossRefGoogle Scholar
  40. 40.
    Seyfried, A., Boltes, M., Kähler, J., Klingsch, W., Portz, A., Rupprecht, T., Schadschneider, A., Steffen, B., Winkens, A.: In: Klingsch, W.W.F., et al. (eds.) Pedestrian and Evacuation Dynamics, pp. 145–156. Springer Berlin/Heidelberg (2010). doi:10.1007/978-3-642-04504-2_11,
  41. 41.
    Holl, S., Seyfried, A.: inSiDe 7(1), 60 (2009).
  42. 42.
    Boltes, M., Seyfried, A., Steffen, B., Schadschneider, A.: In: Klingsch, W.W.F., et al. (eds.) Pedestrian and Evacuation Dynamics, pp. 43–54. doi:10.1007/978-3-642-04504-2-3,
  43. 43.
    Hirschmüller, H.: IEEE Trans. Pattern Anal. Mach. Intell. 30, 328 (2008). doi:
  44. 44.
    Bradski, G.R., Pisarevsky, V.: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2796+ (2000). doi:,
  45. 45.
    Boltes, M., Seyfried, A., Steffen, B., Schadschneider, A.: In: Peacock, R.D., et al. (eds.) Pedestrian and Evacuation Dynamics, pp. 751–754. Springer, Berlin/Heidelberg (2011). doi:10.1007/978-1-4419-9725-8Google Scholar
  46. 46.
    Leibe, B., Seemann, E., Schiele, B.: In: Computer Vision and Pattern Recognition, San Diego, pp. 878–885 (2005)Google Scholar
  47. 47.
    Brostow, G.J., Cipolla, R.: In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, New York, vol. 1, pp. 594–601. IEEE Computer Society, Washington, DC (2006). doi:10.1109/CVPR.2006.320,
  48. 48.
    Tu, P., Sebastian, T., Doretto, G., Krahnstoever, N., Rittscher, J., Yu, T.: In: European Conference on Computer Vision, Marseille, pp. 691–704 (2008)Google Scholar
  49. 49.
    Cheriyadat, A.M., Bhaduri, B.L., Radke, R.J.: In: Computer Vision and Pattern Recognition Workshops, Anchorage, vol. 0, pp. 1–8. IEEE Computer Society, Los Alamitos (2008). doi:
  50. 50.
    Saadat, S., Teknomo, K., Fernandez, P.: Fire Technol. 1–18 (2010). doi:10.1007/s10694-010-0174-9,
  51. 51.
    Johansson, A., Helbing, D., Al-Abideen, H.Z., Al-Bosta, S.: Adv. Complex Syst. 11, 4 (2008).
  52. 52.
    Rittscher, J., Tu, P., Krahnstoever, N.: In: Schmid, C., Soatto, S., Tomasi, C. (eds.) IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, vol. 2, pp. 486–493. IEEE Computer Society (2005)Google Scholar
  53. 53.
    Hu, W., Zhou, X., Tan, T., Lou, J., Maybank, S.: IEEE Trans. Pattern Anal. Mach. Intell. 28(4), 663 (2006)CrossRefGoogle Scholar
  54. 54.
    Cutler, R., Davis, L.: IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 781 (2000)CrossRefGoogle Scholar
  55. 55.
    Pai, C., Tyan, H., Liang, Y., Liao, H., Chen, S.: Pattern Recognit. 37(5), 1025 (2004). doi:10.1016/j.patcog.2003.10.005CrossRefMATHGoogle Scholar
  56. 56.
    Darrell, T., Gordon, G., Harville, M., Woodfill, J.: Int. J. Comput. Vis. 37(2), 175 (2000)CrossRefMATHGoogle Scholar
  57. 57.
    Muñoz Salinas, R., Aguirre, E., García-Silvente, M.: Image Vis. Comput. 25, 995 (2007). doi:10.1016/j.imavis.2006.07.012,
  58. 58.
    Hou, Y.L., Pang, G.K.H.: In: Real, P., Díaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W.G. (eds.) International Conference on Computer Analysis of Images and Patterns, Seville. Lecture Notes in Computer Science, vol. 6854, pp. 93–101. Springer (2011)Google Scholar
  59. 59.
    Harville, M.: Image Vis. Comput. 22(2), 127 (2004). doi:10.1016/j.imavis.2003.07.009,
  60. 60.
    García-Martín, Á., Hauptmann, A., Martinez, J.M.: In: 8th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), Klagenfurt, p. 5 (2011)Google Scholar
  61. 61.
    Eshel, R., Moses, Y.: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Anchorage, vol. 1 (2008). doi:
  62. 62.
    Kelly, P., O’Connor, N.E., Smeaton, A.F.: Image Vis. Comput. 27(10), 1445 (2009). doi:10.1016/j.imavis.2008.04.006CrossRefGoogle Scholar
  63. 63.
    van Oosterhout, T., Bakkes, S., Kröse, B.: In: International Conference on Computer Vision Theory and Applications (VISAPP), Vilamoura, pp. 620–625 (2011)Google Scholar
  64. 64.
    Bouguet, J.Y.: OpenCV Documents (1999)Google Scholar
  65. 65.
    Arun, K.S., Huang, T.S., Blostein, S.D.: IEEE Trans. Pattern Anal. Mach. Intell. 9, 698 (1987). doi:10.1109/TPAMI.1987.4767965,
  66. 66.
    Zhang, J., Klingsch, W., Schadschneider, A., Seyfried, A.: J. Stat. Mech. Theory Exp. (2011). ArXiv:1102.4766
  67. 67.
    Liddle, J., Seyfried, A., Klingsch, W., Rupprecht, T., Schadschneider, A., Winkens, A.: In: Traffic and Granular Flow (2009). ArXiv:0911.4350
  68. 68.
    Voronoi, G.M.: Journal für die reine und angewandte Mathematik 133, 198 (1908)Google Scholar
  69. 69.
    Steffen, B., Seyfried, A.: Physica A 389(9), 1902 (2010). doi:10.1016/j.physa.2009.12.015CrossRefGoogle Scholar
  70. 70.
    Hankin, B.D., Wright, R.A.: Oper. Res. Q. 9, 81 (1958)CrossRefGoogle Scholar
  71. 71.
    John, A., Schadschneider, A., Chowdhury, D., Nishinari, K.: J. Theor. Biol. 231, 279 (2004). Google Scholar
  72. 72.
    Müller, K.: Zur Gestaltung und Bemessung von Fluchtwegen für die Evakuierung von Personen aus Bauwerken auf der Grundlage von Modellversuchen. Dissertation, Technische Hochschule Magdeburg (1981)Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Jülich Supercomputing CentreForschungszentrum Jülich GmbHJülichGermany
  2. 2.Computer Simulation for Fire Safety and Pedestrian TrafficBergische Universität WuppertalWuppertalGermany

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