Turns of different angles and discrete-continuous pedestrian dynamics model

  • Ekaterina KirikEmail author
  • Tat’yana Vitova
  • Andrey Malyshev


In the paper we discuss a problem of correct simulation of movement of the people on the pathes with angles. The shortest path strategy does not work in this cases and gives unrealistic trajectories and increased evacuation time. The discrete-continuous pedestrian dynamics model have been discussed. Angles from \(90^\circ\) to \(180^\circ\) were considered: “L”-, “Z”- and “U”-shaped geometries. A way to identify such geometrical artifacts is proposed.


Pedestrian dynamics Simulation Turns on the path 



  1. Blue VJ, Adler JL (2001) Cellular automata microsimulation for modeling bi-directional pedestrian walkways. Transp Res Part B 35:293–312CrossRefGoogle Scholar
  2. Boltes M, Seyfried A (2013) Collecting pedestrian trajectories. Neurocomputing 100:127–133CrossRefGoogle Scholar
  3. Boltes M, Chraibi M, Holl S, Kemloh Wagoum AU, Lammel G, Liao W, Mehner W, Tordeux A, Zhang J (2014) Experimentation, data collection, modeling and simulation of pedestrian dynamics. In: Procceding’s Book Statistics, probability and numerical analysis 2014, SPNA2014. Tirana, Albania, pp 49–60Google Scholar
  4. Chraibi M, Steffen B (2018) The automatic generation of an efficient floor field for CA simulations in crowd management. In: Mauri G, El Yacoubi S, Dennunzio A, Nishinari K, Manzoni L (eds) Cellular Automata. ACRI 2018. Lecture Notes in Computer Science, 11115:185–195Google Scholar
  5. Chraibi M, Seyfried A, Schadschneider A (2010) Generalized centrifugal force model for pedestrian dynamics. Phys Rev E 82:046111CrossRefGoogle Scholar
  6. Crociani L, Shimura K, Vizzari G, Bandini S (2018) Simulating pedestrian dynamics in corners and bends: a floor field approach. In: Mauri G, El Yacoubi S, Dennunzio A, Nishinari K, Manzoni L (eds) Cellular Automata. ACRI 2018. Lecture Notes in Computer Science, 11115:460–469CrossRefGoogle Scholar
  7. Data archive of experimental data from studies about pedestrian dynamics. Accessed 5 Aug 2019
  8. Dias C, Lovreglio R (2018) Calibrating Cellular Automaton Models for Pedestrians Walking Through Corners. Phys Lett A 382(19):1255–1261CrossRefGoogle Scholar
  9. Dias C, Sarvi M (2016) Exploring the effect of turning manoeuvres on macroscopic properties of pedestrian flow. In: 38th Australasian transport research forum. Melbourne, AustraliaGoogle Scholar
  10. Dias C, Ejtemai O, Sarvi M, Burd M (2014) Exploring pedestrian walking through angled corridors. Transp Res Procedia 2:19–25CrossRefGoogle Scholar
  11. Dias C, Sarvi M, Ejtemai O, Burd M (2015) Elevated desired speed and change in desired direction effects on collective pedestrian flow characteristics. Transp Res Rec 490:65–75CrossRefGoogle Scholar
  12. Duives DC, Daamen W, Hoogendoorn SP (2018) Continuum modelling of pedestrian flows—part 2: sensitivity analysis featuring crowd movement phenomena. Physica A 447:36–48CrossRefGoogle Scholar
  13. Gorrini A, Bandini S, Sarvi M, Dias C, Shiwakoti N (2013) An empirical study of crowd and pedestrian dynamics: the impact of different angle paths and grouping. In: Transportation Research Board, 92nd Annual Meeting, Washington, D.C., 42Google Scholar
  14. Helbing D, Farkas I, Vicsek T (2000) Simulation dynamics features of escape panic. Nature 407:487–490CrossRefGoogle Scholar
  15. Kholshevnikov V (2011) Forecast of human behavior during fire evacuation. In: Proceedings of the international conference on emergency evacuation of people from buildings—EMEVAC, pp 139–153. Belstudio, WarsawGoogle Scholar
  16. Kholshevnikov V, Samoshin D (2009) Evacuation and human behavior in fire. Academy of State Fire Service, EMERCOM of Russia, MoscowGoogle Scholar
  17. Kholshevnikov VV, Shields TJ, Boyce KE, Samoshin DA (2008) Recent developments in pedestrian flow theory and research in Russia. Fire Saf J 43(2):108–118CrossRefGoogle Scholar
  18. Kirchner A, Klupfel H, Nishinari K, Schadschneider A, Schreckenberg M (2004) Discretization effects and the influence of walking speed in cellular automata models for pedestrian dynamics. J Stat Mech Theory Exp 10:10011CrossRefGoogle Scholar
  19. Kirik E, Malyshev A (2014) On validation of SigmaEva pedestrian evacuation computer simulation module with bottleneck flow. J Comput Sci 5(5):847–850CrossRefGoogle Scholar
  20. Kirik E, Vitova T (2014) Cellular automata pedestrian movement model SIgMA.CA: model parameters as an instrument to regulate movement regimes. In: Was J, Sirakoulis GCh, Bandini S (eds.) ACRI 2014. Lecture Notes in Computer Science, 8751:501–507Google Scholar
  21. Kirik E, Vitova T (2016) On formal presentation of update rules, density estimate and using floor fields in CA FF pedestrian dynamics model SIgMA.CA. In: El Yacoubi S, Was J, Bandini S (eds) Cellular Automata, ACRI 2016. Lecture Notes in Computer Science, 9863:435–445Google Scholar
  22. Kirik E, Yurgel’yan T, Krouglov D (2011) On realizing the shortest time strategy in a CA FF pedestrian dynamics model. Cybern Syst 42(1):1–15CrossRefGoogle Scholar
  23. Kirik E, Yurgel’yan T, Malyshev A (2011) On discrete-continuous stochastic floor field pedestrian dynamics model SIgMA.DC. In: Proceedings of the international conference on emergency evacuation of people from buildings. Warsaw, Belstudio, pp 155–161Google Scholar
  24. Kirik E, Malyshev A, Popel E (2014) Fundamental diagram as a model input—direct movement equation of pedestrian dynamics. In: Weidmann U, Kirsch U, Schreckenberg M (eds) Pedestrian and evacuation dynamics 2012. Springer, Cham, pp 691–703CrossRefGoogle Scholar
  25. Kirik E, Vitova T, Malyshev A, Popel E (2018) The impact of different angle paths on discrete-continuous pedestrian dynamics model. In: Mauri G, El Yacoubi S, Dennunzio A, Nishinari K, Manzoni L (eds) Cellular Automata. ACRI 2018. Lecture Notes in Computer Science, 11115:207–217CrossRefGoogle Scholar
  26. Kirik E, Malyshev A, Vitova T, Popel E, Kharlamov E (2018) Pedestrian movement simulation for stadiums design. IOP Conf Ser Mater Sci Eng 456:012074CrossRefGoogle Scholar
  27. Kirik E, Vitova T, Malyshev A, Popel E (2019) On the validation of pedestrian movement models under transition and steady-state conditions. In: Proceedings of the ninth international seminar on fire and explosion hazards (ISFEH9). St. Peterburg, pp 1270–1280Google Scholar
  28. Kretz T, Bonisch C, Vortisch P (2010) Comparison of various methods the calculation of the distance potential field. In: Klingsch WWF, Rogsch C, Schadschneider A, Schreckenberg M (eds) Pedestrian and evacuation dynamics 2008. Springer, Berlin, pp 335–346CrossRefGoogle Scholar
  29. Li S, Li X, Yunchao Q, Jia B (2015) Block-based floor field model for pedestrian’s walking through corner. Physica A 432:337–353CrossRefGoogle Scholar
  30. Lovreglio R, Ronchi E, Nilsson D (2015) Calibrating floor field cellular automaton models for pedestrian dynamics by using likelihood function optimization. Physica A 438:308–320CrossRefGoogle Scholar
  31. Nishinari K, Kirchner A, Namazi A, Schadschneider A (2004) Extended floor field CA model for evacuation dynamics. IEICE Trans Inf Syst E87–D:726–732Google Scholar
  32. Nishinari K, Suma Y, Yanagisawa D, Tomoeda A, Kimura A, Nishi R (2010) Toward smooth movement of crowds. In: Klingsch WWF, Rogsch C, Schadschneider A, Schreckenberg M (eds) Pedestrian and evacuation dynamics 2008. Springer, Berlin, pp 293–308CrossRefGoogle Scholar
  33. Predtechenskii VM, Milinskii AI (1978) Planing for foot traffic flow in buildings. American Publishing, New Dehli. Translation of “Proektirovanie Zhdanii s Uchetom organizatsii Dvizheniya Lyudskikh potokov, Stroiizdat Publishers, Moscow, 1969”Google Scholar
  34. Ren-Yong G, Tie-Qiao T (2012) A simulation model for pedestrian flow through walkways with corners. Simul Model Pract Theory 21(1):103–113CrossRefGoogle Scholar
  35. Schadschneider A, Seyfried A (2009) Validation of CA models of pedestrian dynamics with fundamental diagrams. Cybern Syst 40(5):367–389CrossRefGoogle Scholar
  36. Schadschneider A, Klingsch W, Klupfel H, Kretz T, Rogsch C, Seyfried A, Dynamics E (2009) Empirical results, modeling and applications. In: Meyers RA (ed) Encyclopedia of complexity and system science, vol 3. Springer, Berlin, pp 3142–3192CrossRefGoogle Scholar
  37. Seitz MJ, Koster G (2012) Natural discretization of pedestrian movement in continuous space. Phys Rev E 86(4):046108CrossRefGoogle Scholar
  38. Steffen B, Seyfried A (2009) Modeling of pedestrian movement around 90 and 180 degree bends. arXiv:0912.0610Google Scholar
  39. Zeng W, Nakamura H, Chen P (2014) A modified social force model for pedestrian behavior simulation at signalized crosswalks. Soc Behav Sci 138(14):521–530CrossRefGoogle Scholar
  40. Zeng Y, Song W, Huo F, Vizzari G, Zeng Y, Song W, Huo F, Vizzari G (2018) Modeling evacuation dynamics on stairs by an extended optimal steps model. Simul Model Pract Theory 84:177–189CrossRefGoogle Scholar
  41. Zhang J, Klingsch W, Rupprecht T, Schadschneider A, Seyfried A (2011) Empirical study of turning and merging of pedestrian streams in T-junction. arXiv:1112.5299Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Institute of Computational ModellingRussian Academy of Sciences, Siberian BranchKrasnoyarskRussia

Personalised recommendations