Empirical Results of Pedestrian and Evacuation Dynamics

  • Maik Boltes
  • Jun Zhang
  • Antoine Tordeux
  • Andreas SchadschneiderEmail author
  • Armin Seyfried
Reference work entry
Part of the Encyclopedia of Complexity and Systems Science Series book series (ECSSS)



A bottleneck is in general a part of facility limiting pedestrian flows. This can be, for example, a door, a narrowing in a corridor, or stairs, i.e., locations of reduced capacity. At bottlenecks jamming occurs if the inflow is higher than the capacity.


The maximal flow rate supported by a facility is called “capacity.”

Crowd disaster

Crowd disaster is an accident in which the specific behavior of the crowd is a relevant factor, e.g., through competitive and nonadaptive behavior. In the media, it is often called “panic” which is a scientifically not proven concept in crowd dynamics and should thus be avoided.


A large group of pedestrians who have gathered together. Depending on the perspective, more specific definitions exist.


Evacuation is the movement of persons from a dangerous place due to the threat or occurrence of a disastrous event. In normal situations this is called “egress” instead.

Flow rate

The flow rate Jis a measure for...


Primary Literature

  1. Abe K (1986) The science of human panic. Brain Publishing, Tokyo (in Japanese)Google Scholar
  2. Alhajyaseen WK, Nakamura H, Asano M (2011) Effects of bidirectional pedestrian flow characteristics upon the capacity of signalized cross-walks. Procedia Soc Behav Sci 16:526–535CrossRefGoogle Scholar
  3. Ali S, Shah M (2007) A lagrangian particle dynamics approach for crowd flow segmentation and stability analysis. In: Conference on computer vision and pattern recognition, pp 1–6Google Scholar
  4. Allen JG, Xu RYD, Jin JS. Object tracking using camshift algorithm and multiple quantized feature spaces. In: Proceedings of the Pan-Sydney area workshop on visual information processing (Darlinghurst, Australia, Australia, 2004), VIP ’05, Australian Computer Society, pp 3–7Google Scholar
  5. Appert-Rolland C, Chevoir F, Gondret P, Lassarre S, Lebacque J-P, Schreckenberg M (2009) Traffic and granular flow ’07. Springer, Berlin/HeidelbergzbMATHCrossRefGoogle Scholar
  6. ASA. In disasters, panic is rare; altruism dominates. Technical report, ASA, Aug 2002Google Scholar
  7. Ashe B, Shields TJ (1999) Analysis and modelling of the unannounced evacuation of a large retail store. Fire Mater 23:333–336CrossRefGoogle Scholar
  8. Barlovic R, Santen L, Schadschneider A, Schreckenberg M (1998) Metastable states in cellular automata for traffic flow. Eur Phys J B 5:793CrossRefGoogle Scholar
  9. Benedek C (2014) 3d people surveillance on range data sequences of a rotating lidar. Pattern Recogn Lett Special Issue Depth Image Anal 50:149Google Scholar
  10. Bode NWF, Holl S, Mehner W, Seyfried A (2015) Disentangling the impact of social groups on response times and movement dynamics in evacuation. PLoS One 10:0121227Google Scholar
  11. Boltes M, Seyfried A (2013) Collecting Pedestrian Trajectories. Neurocomputing, Special Issue Behav Video 100:127–133Google Scholar
  12. Boltes M, Seyfried A, Steffen B, Schadschneider A (2010) Automatic extraction of pedestrian trajectories from video recordings. In: Klingsch WWF, Rogsch C, Schadschneider A, Schreckenberg M (eds) Pedestrian and evacuation dynamics 2008. Springer, Berlin/Heidelberg, pp 43–54CrossRefGoogle Scholar
  13. Boltes M, Seyfried A, Steffen B, Schadschneider A (2011) Using stereo recordings to extract pedestrian trajectories automatically in space. In: Peacock RD et al (eds) Pedestrian and evacuation dynamics. Springer, Berlin/Heidelberg, pp 751–754CrossRefGoogle Scholar
  14. Boltes M, Holl S, Tordeux A, Seyfried A, Schadschneider A, Lang U (2017a) Influences of extraction techniques on the quality of measured quantities of pedestrian characteristics. In: Song W, Ma J, Fu L (eds) Proceedings of pedestrian and evacuation dynamics 2016. Collective Dynamics 1, 0, pp 500–547, 618Google Scholar
  15. Boltes M, Schumann J, Salden D (2017b) Gathering of data under laboratory conditions for the deep analysis of pedestrian dynamics in crowds. In: 2017 14th IEEE international conference on advanced video and signal based surveillance (AVSS)Google Scholar
  16. Bouguet J-Y (1999) Pyramidal implementation of the Lucas Kanade feature tracker. OpenCV DocumentsGoogle Scholar
  17. Boyce KE, Shields TJ, Silcock GWH (1999) Toward the characterization of building occupancies for fire safety engineering: capabilities of disabled people moving horizontally and on an incline. Fire Technol 35:51–67CrossRefGoogle Scholar
  18. Bradski GR (1998) Computer vision face tracking for use in a perceptual user interface. Intel Technol J 2:1–15Google Scholar
  19. Brown DC (1971) Close-range camera calibration. Photogramm Eng 37:855–866Google Scholar
  20. Bryan JL (1995) Chapter 3. Behavioral response to fire and smoke. In: DiNenno PJ (ed) SFPE handbook of fire protection engineering, 2nd edn. National Fire Protection Association, Quincy, p 263Google Scholar
  21. Bukáček M, Hrabák P, Krbálek M (2014) Experimental study of phase transition in pedestrian flow. Transp Res Procedia 2:105–113CrossRefGoogle Scholar
  22. Bukáček M, Hrabák P, Krbálek M (2015) Experimental analysis of two-dimensional pedestrian flow in front of the bottleneck – experimental analysis of 2d pedestrian flow. In: Chraibi M et al (eds) Traffic and granular flow ’13. Springer, Heidelberg, pp 93–101Google Scholar
  23. Burghardt S, Seyfried A, Klingsch W (2010) Improving egress design through measurement and correct interpretation of the fundamental diagram for stairs. In: Panda M, Chattaraj U (eds) Developments in road transportation. NIT Rourkela, Odisha, India. Macmillan Publishers India Ltd, pp 181–187Google Scholar
  24. Burghardt S, Seyfried A, Klingsch W (2013) Performance of stairs – fundamental diagram and topographical measurements. Transp Res C Emerg Technol 37:268CrossRefGoogle Scholar
  25. Burstedde C, Klauck K, Schadschneider A, Zittartz J (2001) Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A 295:507–525zbMATHCrossRefGoogle Scholar
  26. Cao S, Zhang J, Salden D, Ma J, Shi C, Zhang R (2016) Pedestrian dynamics in single-file movement of crowd with different age compositions. Phys Rev E 94: 012312Google Scholar
  27. Cao S, Seyfried A, Zhang J, Holl S, Song W (2017) Fundamental diagrams for multidirectional pedestrian flows. J Stat Mech Theory Exp 2017:033404CrossRefGoogle Scholar
  28. Chakrabarti J, Dzubiella J, Löwen H (2004) Reentrance effect in the lane formation of driven colloids. Phys Rev E 70:012401CrossRefGoogle Scholar
  29. Chattaraj U, Seyfried A, Chakroborty P (2009) Comparison of pedestrian fundamental diagram across cultures. Adv Complex Syst 12(3):393–405CrossRefGoogle Scholar
  30. Chen X, Ye J, Jian N (2010) Relationships and characteristics of pedestrian traffic flow in confined passageways. Transp Res Rec J Transp Res Board 2198:32–40CrossRefGoogle Scholar
  31. Chen J, Lo SM, Ma J (2017) Pedestrian ascent and descent fundamental diagram on stairway. J Stat Mech Theory Exp 2017(8):083403CrossRefGoogle Scholar
  32. Chraibi M, Seyfried A, Schadschneider A (2010) Generalized centrifugal force model for pedestrian dynamics. Phys Rev E 82:046111CrossRefGoogle Scholar
  33. Chraibi M, Boltes M, Schadschneider A, Seyfried A (eds) (2015) Traffic and granular flow ’13. Springer, HeidelbergGoogle Scholar
  34. Chraibi M, Tordeux A, Schadschneider A, Seyfried A (2018) Modelling of pedestrian and evacuation dynamics. In: Encyclopedia of complexity and system sciences, SpringerGoogle Scholar
  35. Christensen K, Sharifi MS, Stuart D, Chen A, Kim YS, Chen Y (2014) Overview of a large-scale controlled experiment on pedestrian walking behavior involving individual with disabilities. In The 93rd annual meeting of the transportation research boardGoogle Scholar
  36. Clarke LP (2002) Myth or reality? Contexts 1:21–26CrossRefGoogle Scholar
  37. Code H. International code of safety for high-speed craft, 2000 (2000 HSC Code). Technical report, International Maritime Organization (IMO), 2000. Resolution MSC97(73)Google Scholar
  38. Coleman JS (1990) Foundation of social theory. Belknap, Cambridge, MA. Chapter 9Google Scholar
  39. Corbetta A, Bruno L, Muntean A, Toschi F (2014) High statistics measurements of pedestrian dynamics. Transp Res Procedia 2:96–104CrossRefGoogle Scholar
  40. Daamen W, Hoogendoorn SP (2006) Flow-density relations for pedestrian traffic. In: Schadschneider A et al (eds) Traffic and granular flow ’05. Springer, BerlinGoogle Scholar
  41. Daamen W, Hoogendoorn SP (2010) Capacity of doors during evacuation conditions. Procedia Eng 3(0):53–66. 1st Conference on Evacuation Modeling and ManagementCrossRefGoogle Scholar
  42. Daamen W, Bovy PHL, Hoogendoorn SP (2002) Modelling pedestrians in transfer stations. In: Schreckenberg M, Sharma SD (eds) Pedestrian and evacuation dynamics. Springer, Berlin/Heidelberg, pp 59–73Google Scholar
  43. Daganzo CF (2006) On the variational theory of traffic flow: well-posedness, duality and applications. Netw Heterog Media 1:601MathSciNetzbMATHCrossRefGoogle Scholar
  44. de Gelder B, Snyder J, Greve D, Gerard G, Hadjikhani N (2004) Fear fosters flight: a mechanism for fear contagion when perceiving emotion expressed by a whole body. Proc Natl Acad Sci 101(47):16701–16706CrossRefGoogle Scholar
  45. Dieckmann D (1911) Die Feuersicherheit in Theatern. Jung (München). (in German)Google Scholar
  46. Dogliani M (2002) An overview of present and under-development IMO’s requirements concerning evacuation from ships. In: Schreckenberg M, Sharma SD (eds) Pedestrian and evacuation dynamics. Springer, Berlin/Heidelberg, pp 339–354Google Scholar
  47. Dollár P, Wojek C, Schiele B, Perona P (2012) Pedestrian detection: An evaluation of the state of the art. Pattern Anal Mach Intell IEEE Trans 34(4):743–761CrossRefGoogle Scholar
  48. Dzubiella J, Hoffmann GP, Löwen H (2002) Lane formation in colloidal mixtures driven by an external field. Phys Rev E 65:021402CrossRefGoogle Scholar
  49. Edie L (1963) Discussion of traffic stream measurements and definitions. In: Almond J (ed) Proceedings of the 2nd international symposium theory of traffic flow, pp 139–154Google Scholar
  50. El Yacoubi S, Chopard B, Bandini S (eds) (2006) Cellular automata – 7th international conference on cellular automata for research and industry, ACRI 2006. Springer, PerpignanGoogle Scholar
  51. Ezaki T, Ohtsuka K, Chraibi M, Boltes M, Yanagisawa D, Seyfried A, Schadschneider A, Nishinari K (2016) Inflow process of pedestrians to a confined space. Collective Dyn 1:1–18CrossRefGoogle Scholar
  52. FAA (1990) F. A. A. Emergency evacuation – cfr sec. 25.803. Regulation CFR Sec. 25.803, Federal Aviation AdministrationGoogle Scholar
  53. Feliciani C, Nishinari K (2016) Empirical analysis of the lane formation process in bidirectional pedestrian flow. Phys Rev E 94:032304CrossRefGoogle Scholar
  54. Fischer H (1933) Über die Leistungsfähigkeit von Türen, Gängen und Treppen bei ruhigem, dichtem Verkehr. Dissertation, Technische Hochschule Dresden. in GermanGoogle Scholar
  55. Forell B, Seidenspinner R, Hosser D (2010) Quantitative comparison of international design standards of escape routes in assembly buildings. In: Klingsch W et al (eds) Pedestrian and evacuation dynamics 2008. Springer, Berlin/Heidelberg, pp 791–801CrossRefGoogle Scholar
  56. Forschungszentrum Jülich, Jülich Supercomputing Centre. Data archive of experiments on pedestrian dynamics. 18 Nov 2018
  57. Frantzich H (1994) A model for performance-based design of escape routes. Technical report 1011, Department of Fire Safety Engineering, Lund Institute of TechnologyGoogle Scholar
  58. Frantzich H (1996) Study of movement on stairs during evacuation using video analysing techniques. Technical report, Department of Fire Safety Engineering, Lund Institute of TechnologyGoogle Scholar
  59. Fruin JJ (1971) Pedestrian planning and design. Elevator World, New YorkGoogle Scholar
  60. Fujiyama T, Tyler N (2004a) An explicit study on walking speeds of pedestrians on stairs. In: 10th international conference on mobility and transport for elderly and disabled peopleGoogle Scholar
  61. Fujiyama T, Tyler N (2004b) Pedestrian speeds on stairs: an initial step for a simulation model. In: Proceedings of 36th Universities’ Transport Studies Group ConferenceGoogle Scholar
  62. Galea ER (2002) Simulating evacuation and circulation in planes, trains, buildings and ships using the EXODUS software. In: Schreckenberg M, Sharma SD (eds) Pedestrian and evacuation dynamics. Springer, Berlin/Heidelberg, pp 203–226Google Scholar
  63. Galea ER (ed) (2003) Pedestrian and evacuation dynamics 2003. CMS Press, LondonGoogle Scholar
  64. Garcimartín A, Parisi DR, Pastor JM, Martín-Gómez C, Zuriguel I (2016) Flow of pedestrians through narrow doors with different competitiveness. J Stat Mech Theory Exp 2016:043402MathSciNetCrossRefGoogle Scholar
  65. Gmiterko A, Liptak T (2013) Motion capture of human for interaction with service robot. Am J Mech Eng 1:212–216Google Scholar
  66. Graat E, Midden C, Bockholts P (1999) Complex evacuation; effects of motivation level and slope of stairs on emergency egress time in a sports stadium. Saf Sci 31:127–141CrossRefGoogle Scholar
  67. Grosshandler W, Sunder S, Snell J (2003) Building and fire safety investigation of the world trade center disaster. In: Galea ER (ed) Pedestrian and evacuation dynamics 2003. CMS Press, London, pp 279–281Google Scholar
  68. Hadi HS, Rosbi M, Sheikh UU (2013) A review of infrared spectrum in human detection for surveillance systems. Int J Interact Digit Media 1(3):13–20Google Scholar
  69. Hamacher HW, Tjandra SA (2002) Mathematical modelling of evacuation problems – a state of the art. In: Schreckenberg M, Sharma SD (eds) Pedestrian and evacuation dynamics. Springer, Berlin/Heidelberg, pp 227–266zbMATHGoogle Scholar
  70. Hankin BD, Wright RA (1958) Passenger flow in subways. Oper Res Q 9(2):81–88CrossRefGoogle Scholar
  71. Helbing D (2001) Traffic and related self-driven many-particle systems. Rev Mod Phys 73:1067MathSciNetCrossRefGoogle Scholar
  72. Helbing D, Buzna L, Johansson A, Werner T (2005) Self-organized pedestrian crowd dynamics: experiments, simulations, and design solutions. Transp Sci 39:1–24CrossRefGoogle Scholar
  73. Helbing D, Johansson A, Al-Abideen HZ (2007) Dynamics of crowd disasters: an empirical study. Phys Rev E 75:046109CrossRefGoogle Scholar
  74. Holl S, Seyfried A (2009) Hermes – an evacuation assistent for mass events. inSiDe 7:60Google Scholar
  75. Holl S, Schadschneider A, Seyfried A (2014) Hermes: an evacuation assistant for large arenas. In: Weidmann U et al (eds) Pedestrian and evacuation dynamics 2012 (Zürich, 2014). Springer, Berlin/Heidelberg, p 345Google Scholar
  76. Hoogendoorn SP, Daamen W (2005) Pedestrian behavior at bottlenecks. Transp Sci 39(2):0147–0159CrossRefGoogle Scholar
  77. Hoogendoorn S, Daamen W, Bovy P (2003a) Extracting microscopic pedestrian characteristics from video data. In: TRB2003 annual meetingGoogle Scholar
  78. Hoogendoorn SP, Daamen W, Bovy PHL (2003b) Microscopic pedestrian traffic data collection and analysis by walking experiments: behaviour at bottlenecks. In: Galea ER (ed) Pedestrian and evacuation dynamics 2003. CMS Press, London, pp 89–100Google Scholar
  79. Hoskin KJ, Spearpoint M (2004) Crowd characteristics and egress at stadia. In: Shields TJ (ed) Human Behaviour in Fire. Intersience, London, pp 367–376Google Scholar
  80. ISO-TR-13387-8-1999 (1999) Fire safety engineering – part 8: life safety – occupant behaviour, location and condition. Technical report, International Organization for Standardization.
  81. Jafari OH, Mitzel D, Leibe B (2014) Real-time rgb-d based people detection and tracking for mobile robots and head-worn cameras. In: IEEE international conference on robotics and automation (ICRA)Google Scholar
  82. Jelić A, Appert-Rolland C, Lemercier S, Pettré J (2012) Properties of pedestrians walking in line: fundamental diagrams. Phys Rev E 85:9CrossRefGoogle Scholar
  83. Johnson NR (1987) Panic at “The Who Concert Stampede”: an empirical assessment. Soc Probl 34:362–373CrossRefGoogle Scholar
  84. Jungermann H, Göhlert C (2000) Emergency evacuation from double-deck aircraft. In: Cottam M, Harvey D, Pape R, Tait J (eds) Foresight and precaution. Proceedings of ESREL 2000, SARS and SRA Europe annual conference. A.A. Balkema, Rotterdam, pp 989–992Google Scholar
  85. Keating JP (1982) The myth of panic. Fire J:57–62Google Scholar
  86. Kerner BS (2004) The physics of traffic. Springer, BerlinCrossRefGoogle Scholar
  87. Kerner B (2017) Breakdown in traffic networks – fundamentals of transportation science. Springer, Berlin/HeidelbergzbMATHCrossRefGoogle Scholar
  88. Kirchner A, Klüpfel 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 2004(10):P10011zbMATHCrossRefGoogle Scholar
  89. Kiss Á, Szirányi T (2013) Localizing people in multi-view environment using height map reconstruction in real-time. Pattern Recogn Lett 34(16):2135–2143CrossRefGoogle Scholar
  90. Kitazawa K, Fujiyama T (2010) Pedestrian vision and collision avoidance behavior: investigation of the information process space of pedestrians using an eye tracker. In: Klingsch W et al (eds) Pedestrian and evacuation dynamics 2008. Springer, Berlin/Heidelberg, pp 95–108CrossRefGoogle Scholar
  91. Klingsch W, Rogsch C, Schadschneider A, Schreckenberg M (eds) (2010) Pedestrian and evacuation dynamics 2008. Springer, Berlin/HeidelbergzbMATHGoogle Scholar
  92. Knoop VL, Daamen W (eds) (2016) Traffic and granular flow ’15. Springer, Berlin/HeidelbergzbMATHGoogle Scholar
  93. Knoop V, Hoogendoorn S, van Zuylen H (2009) Empirical differences between time mean speed and space mean speed. In: Appert-Rolland C, Chevoir F, Gondret P, Lassarre S, Lebacque J-P, Schreckenberg M (eds) Traffic and Granular Flow ‘07. Springer, Berlin/HeidelbergGoogle Scholar
  94. Kozlov V, Buslaev A, Bugaev A, Yashina M, Schadschneider A, Schreckenberg M (eds) (2013) Traffic and granular flow ’11. Springer, HeidelbergGoogle Scholar
  95. Krausz B, Bauckhage C (2012) Loveparade 2010: automatic video analysis of a crowd disaster. Comput Vis Image Underst 116(3):307–319 Special issue on Semantic Understanding of Human Behaviors in Image SequencesCrossRefGoogle Scholar
  96. Kretz T (2007) Pedestrian traffic – simulation and experiments. PhD thesis, Universität Duisburg-Essen, Fachbereich PhysikGoogle Scholar
  97. Kretz T, Grünebohm A, Kaufman M, Mazur F, Schreckenberg M (2006a) Experimental study of pedestrian counterflow in a corridor. J Stat Mech 2006:P10001CrossRefGoogle Scholar
  98. Kretz T, Grünebohm A, Schreckenberg M (2006b) Experimental study of pedestrian flow through a bottleneck. J Stat Mech 2006:P10014CrossRefGoogle Scholar
  99. Kretz T, Grünebohm A, Kessel A, Klüpfel H, Meyer-König T, Schreckenberg M (2008) Upstairs walking speed distributions on a long stairway. Saf Sci 46(1):72–78CrossRefGoogle Scholar
  100. Lam WHK, Cheung CY (2000) Pedestrian speed/flow relationships for walking facilities in hong kong. J Transp Eng 126:343–349CrossRefGoogle Scholar
  101. Lam WHK, Lee JYS, Cheung CY (2002) A study of the bidirectional pedestrian flow characteristics at Hong Kong signalized crosswalk facilities. Transportation 29:169–192CrossRefGoogle Scholar
  102. Lam WHK, Lee JYS, Chan KS, Goh PK (2003) A generalised function for modeling bi-directional flow effects on indoor walkways in Hong Kong. Transp Res A Policy Pract 37:789–810CrossRefGoogle Scholar
  103. Le Bon G (1895) The crowd: a study of the popular mind (Psychologie des Foules). Sparkling BooksGoogle Scholar
  104. Lemercier S, Moreau M, Moussaïd M, Theraulaz G, Donikian S, Pettré J (2011) Reconstructing motion capture data for human crowd study. Lect Notes Comput Sci 7060:365–376CrossRefGoogle Scholar
  105. Leutzbach W (1988) Introduction to the theory of traffic flow. Springer, BerlinCrossRefGoogle Scholar
  106. Lian L, Mai X, Song W, Kit YK (2015a) An experimental study on four-directional intersecting pedestrian flows. J Stat Mech 2015:P08024CrossRefGoogle Scholar
  107. Lian L, Mai X, Song W, Richard KYK, Wei X, Ma J (2015b) An experimental study on four-directional intersecting pedestrian flows. J Stat Mech Theory Exp 2015(8):P08024CrossRefGoogle Scholar
  108. Liddle J, Seyfried A, Klingsch W, Rupprecht T, Schadschneider A, Winkens A (2009) An experimental study of pedestrian congestions: Influence of bottleneck width and length. available from
  109. Liu X, Song W, Zhang J (2009) Extraction and quantitative analysis of microscopic evacuation characteristics based on digital image processing. Physica A 388(13):2717–2726CrossRefGoogle Scholar
  110. Liu X, Song W, Fu L, Fang Z (2016) Experimental study of pedestrian inflow in a room with a separate entrance and exit. Physica A 442:224–238CrossRefGoogle Scholar
  111. McPhail C, Tucker C (2003) Collective behaviour. In: Reynolds L, Herman-Kinney NJ (eds) Handbook of symbolic interactionism. Altamira, Walnut Creek, pp 721–741Google Scholar
  112. Mehner W, Boltes M, Seyfried A (2016) Methodology for generating individualized trajectories from experiments. In: Knoop VL, Daamen W (eds) Traffic and granular flow ’15. Springer, Berlin/Heidelberg, pp 3–10CrossRefGoogle Scholar
  113. Mehner W, Boltes M, Mathias M, Leibe B (2015) Robust marker-based tracking for measuring crowd dynamics. Springer International Publishing, Cham, pp 445–455Google Scholar
  114. Meyer-König T, Klüpfel H, Schreckenberg M (2002) Assessment and analysis of evacuation processes on passenger ships by microscopic simulation. In: Schreckenberg M, Sharma SD (eds) Pedestrian and evacuation dynamics. Springer, Berlin/Heidelberg, pp 297–302Google Scholar
  115. Mintz A (1951) Non-adaptive group behaviour. J Abnorm Soc Psychol 46:150–159CrossRefGoogle Scholar
  116. Morerio P, Marcenaro L, Regazzoni CS (2012) People count estimation in small crowds. In: Advanced video and signal-based surveillance (AVSS), 2012 I.E. ninth international conference on, pp 476–480Google Scholar
  117. Morrall JF, Ratnayake LL, Seneviratne PN (1991) Comparison of central business district pedestrian characteristics in Canada and Sri Lanka. Transp Res Rec 1294:57Google Scholar
  118. MSC-Circ.1033. Interim guidelines for evacuation analyses for new and existing passenger ships. Technical report, International Maritime Organization, Marine Safety Committee, London, June, 6th 2002. MSC/Circ. 1033Google Scholar
  119. MSC-Circ.1166. Guidelines for a simplified evacuation analysis for high-speed passenger craft. Technical report, International Maritime Organisation 2005Google Scholar
  120. Muir HC (2002) Airplane of the 21st century: challenges in safety and survivability. In: Airplane survivability issues in the 21st centuryGoogle Scholar
  121. Muir HC, Bottomley DM, Marrison C (1996) Effects of motivation and cabin configuration on emergency aircraft evacuation behavior and rates of Egress. Int J Aviat Psychol 6(1):57–77CrossRefGoogle Scholar
  122. Müller K (1981) Zur Gestaltung und Bemessung von Fluchtwegen für die Evakuierung von Personen aus Bauwerken auf der Grundlage von Modellversuchen. Dissertation, Technische Hochschule MagdeburgGoogle Scholar
  123. Muybridge E (1887) Animal locomotion, plate 519. Da Capo Press, New YorkGoogle Scholar
  124. MVStättV – Erläuterungen: Musterverordnung über den Bau und Betrieb von Versammlungsstätten, Erläuterungen, Juni 2005.
  125. Nagai R, Fukamachi M, Nagatani T (2006) Evacuation of crawlers and walkers from corridor through an exit. Physica A 367:449–460CrossRefGoogle Scholar
  126. Navin FD, Wheeler RJ (1969) Pedestrian flow characteristics. Traffic Eng 39:30–36Google Scholar
  127. Nelson HE, Mowrer FW (2002) Chapter 14. Emergency movement. In: DiNenno PJ (ed) SFPE handbook of fire protection engineering. National Fire Protection Association, Quincy, pp 367–380Google Scholar
  128. Nguyen DT, Li W, Ogunbona PO (2016) Human detection from images and videos: A survey. Pattern Recogn 51:148–175CrossRefGoogle Scholar
  129. NMJP. The high-speed craft MS Sleipner Disaster 26 November 1999. Official Norwegian Reports 2000:31, Norwegian Ministry of Justice and Police, Oslo, 2000Google Scholar
  130. Oeding D. Verkehrsbelastung und Dimensionierung von Gehwegen und anderen Anlagen des Fußgängerverkehrs. Forschungsbericht 22, Technische Hochschule Braunschweig, 1963Google Scholar
  131. Older SJ (1968) Movement of pedestrians on footways in shopping streets. Traffic Eng Control 10:160–163Google Scholar
  132. Owen M, Galea ER, Lawrence PJ, Filippidis L (1998) AASK – aircraft accident statistics and knowledge: a database of human experience in evacuation, derived from aviation accident reports. Aeronaut J 102:353–363Google Scholar
  133. Pathan SS, Richter K (2015) Pedestrian behavior analysis with image-based method in crowds. In: Chraibi M et al (eds) Traffic and granular flow ’13. Springer, Heidelberg, pp 187–194Google Scholar
  134. Pauls JL Evacuation drill held in the b. c. hydro building 26 June 1969. Building Research Note 80, NRCC, September 1971Google Scholar
  135. Pauls JL, Fruin JJ, Zupan JM (2006) Minimum stair width for evacuytion, overtaking movement and counterflow – technical bases and suggestions for the past, present and future. In: Waldau N et al (eds) Pedestrian and evacuation dynamics 2005. Springer, Berlin, pp 57–69Google Scholar
  136. Peacock RD, Kuligowski ED, Averill JD (eds) (2011) Pedestrian and evacuation dynamics. Springer, Berlin/HeidelbergGoogle Scholar
  137. Pellicanò N, Aldea E, Hegarat-Mascle SL (2017) Geometry-based multiple camera head detection in dense crowds. In: Proceedings of 28th British Machine Vision Conference (BMVC) – 5th activity monitoring by multiple distributed sensing workshopGoogle Scholar
  138. Portz A, Seyfried A (2011) Analyzing stop-and-go waves by experiment and modeling. In: Peacock RD et al. (eds) Pedestrian and evacuation dynamics. Springer Berlin/Heidelberg, pp. 577–586Google Scholar
  139. Predtechenskii VM, Milinskii AI (1978) Planing for foot traffic flow in buildings. Amerind Publishing, New Delhi. Translation of: Proekttirovanie Zhdanii s Uchetom Organizatsii Dvizheniya Lyuddskikh Potokov, Stroiizdat Publishers, Moscow 1969Google Scholar
  140. Predtetschenski W, Milinski A (1971) Personenströme in Gebäuden – Berechnungsmethoden für die Modellierung. Müller, Köln-BraunsfeldGoogle Scholar
  141. Purser DA, Bensilium M (2001) Quantification of behaviour for engineering design standards and escape time calculations. Saf Sci 38(2):158–182CrossRefGoogle Scholar
  142. Pushkarev B, Zupan JM (1975) Capacity of walkways. Transp Res Rec 538:1–15Google Scholar
  143. Rameshbabu K, Swarnadurga J, Archana G, Menaka K (2012) Target tracking system using kalman filter. Int J Adv Eng Res Stud 2:90–94Google Scholar
  144. Revi A (2006) Pre and post-cyclone & storm surge evacuation & emergency response in India. In: Waldau N et al (eds) Pedestrian and evacuation dynamics 2005. Springer, BerlinGoogle Scholar
  145. Rex M, Löwen H (2007) Lane formation in oppositely charged colloids driven by an electric field: chaining and two-dimensional crystallization. Phys Rev E 75:051402CrossRefGoogle Scholar
  146. Rupprecht T, Klingsch W, Seyfried A (2011) Influence of geometry parameters on pedestrian flow through bottleneck. In: Peacock RD et al (eds) Pedestrian and evacuation dynamics. Springer, Berlin/Heidelberg, pp 71–80CrossRefGoogle Scholar
  147. Ryan D, Denman S, Sridharan S, Fookes C (2014) An evaluation of crowd counting methods, features and regression models. Comput Vis Image Underst 130:1–17CrossRefGoogle Scholar
  148. Saadat S, Teknomo K (2011) Automation of pedestrian tracking in a crowded situation. In: Peacock RD et al (eds) Pedestrian and evacuation dynamics. Springer, Berlin/Heidelberg, pp 231–239CrossRefGoogle Scholar
  149. Saito H, Hagihara T, Hatanaka K, Sawai T (2008) Development of pedestrian detection system using far-infrared ray camera. SEI Techn Rev 66:112–117Google Scholar
  150. Saloma C (2006) Herding in real escape panic. In: Waldau N et al (eds) Pedestrian and evacuation dynamics 2005. Springer, BerlinGoogle Scholar
  151. Schadschneider A, Seyfried A (2011) Empirical results for pedestrian dynamics and their implications for modeling. Netw Heterog Media 6:545–560MathSciNetzbMATHCrossRefGoogle Scholar
  152. Schadschneider A, Pöschel T, Kühne R, Schreckenberg M, Wolf D (eds) (2006) Traffic and granular flow ’05. Springer, BerlinGoogle Scholar
  153. Schadschneider A, Eilhardt C, Nowak S, Wagoum AK, Seyfried A (2013) Hermes – an evacuation assistant for large sports arenas based on microscopic simulations of pedestrian dynamics. In: Kozlov V et al (eds) Traffic and granular flow ’11. Springer, Heidelberg, p 287CrossRefGoogle Scholar
  154. Schelajew J, Schelajewa E, Semjonow N (2000) Nikolaus II. Der letzte russische Zar. Bechtermünz, AugsburgGoogle Scholar
  155. Schneider U, Kath K, Oswald M, Kirchberger H (2006) Evakuierung und Verhalten von Personen im Brandfall unter spezieller Berücksichtigung von schienengebundenen Fahrzeugen. Technical report 12, TU WienGoogle Scholar
  156. Schreckenberg M, Sharma SD (eds) (2002) Pedestrian and evacuation dynamics. Springer, Berlin/HeidelbergzbMATHGoogle Scholar
  157. Schreckenberg M, Wolf DE (eds) (1998) Traffic and granular flow ’97. Springer, SingaporeGoogle Scholar
  158. Schumann J, Boltes M (2017) Tracking of wheelchair users in dense crowds. In: 2017 international conference on indoor positioning and indoor navigation (IPIN)Google Scholar
  159. Schweingruber D, Wohlstein RT (2005) The madding crowd goes to school: myths about crowds in introductory sociology textbooks. Teach Sociol 33(2):136–153CrossRefGoogle Scholar
  160. Seeger PG, John R (1978) Untersuchung der Räumungsabläufe in Gebäuden als Grundlage für die Ausbildung von Rettungswegen, Teil III: Reale Räumungsversuche. Technical report T395, Forschungsstelle für Brandschutztechik an der Universität Karlsruhe (TH)Google Scholar
  161. Seer S, Bauer D, Brändle N, Ray M (2008) Estimating pedestrian movement characteristics for crowd control at public transport facilities. In: 11th international IEEE conference on intelligent transport systemsGoogle Scholar
  162. Seitz MJ, Köster G (2012) Natural discretization of pedestrian movement in continuous space. Phys Rev E 86:046108CrossRefGoogle Scholar
  163. Seyfried A, Steffen B, Klingsch W, Boltes M (2005) The fundamental diagram of pedestrian movement revisited. J Stat Mech 2005:P10002CrossRefGoogle Scholar
  164. Seyfried A, Steffen B, Lippert T (2006) Basics of modelling the pedestrian flow. Physica A 368:232–238CrossRefGoogle Scholar
  165. Seyfried A, Rupprecht T, Passon O, Steffen B, Klingsch W, Boltes M (2007) Capacity estimation for emergency exits and bootlenecks. In: Interflam 2007 – conference proceedingsGoogle Scholar
  166. Seyfried A, Portz A, Schadschneider A (2010a) Phase coexistence in congested states of pedestrian dynamics. Lect Notes Comp Sci 6350:496zbMATHCrossRefGoogle Scholar
  167. Seyfried A, Boltes M, Kähler J, Klingsch W, Portz A, Rupprecht T, Schadschneider A, Steffen B, Winkens A (2010b) Enhanced empirical data for the fundamental diagram and the flow through bottlenecks. In: Klingsch W et al (eds) Pedestrian and evacuation dynamics 2008. Springer, Berlin/Heidelberg, pp 145–156CrossRefGoogle Scholar
  168. Shi X, Ye Z, Shiwakoti N, Li Z (2015) A review of experimental studies on complex pedestrian movement behaviors. In: CICTP 2015, pp 1081–1096Google Scholar
  169. Shiwakoti N, Gong Y, Shi X, Ye Z (2015a) Examining influence of merging architectural features on pedestrian crowd movement. Saf Sci 75:15–22CrossRefGoogle Scholar
  170. Shiwakoti N, Shi X, Zhirui Y, Wang W (2015b) Empirical study on pedestrian crowd behaviour in right angled junction. In: 37th Australasian Transport Research Forum (ATRF)Google Scholar
  171. Sieben A, Schumann J, Seyfried A (2017) Collective phenomena in crowds – where pedestrian dynamics need social psychology. PLoS One 12:1–19CrossRefGoogle Scholar
  172. Sime JD (1990) Chapter. 5. The concept of panic. In: Canter D (ed) Fires and human behaviour, vol 1. Wiley, London, pp 63–81Google Scholar
  173. Song W, Ma J, Fu L (2017) Proceedings of pedestrian and evacuation dynamics 2016. Collective Dyn 1(0):618Google Scholar
  174. Steffen B, Seyfried A (2010) Methods for measuring pedestrian density, flow, speed and direction with minimal scatter. Physica A 389:1902–1910CrossRefGoogle Scholar
  175. Stuart D, Christensen K, Chen A, Kim YS, Chen Y (2013) Utilizing augmented reality technology for crowd pedestrian analysis involving individuals with disabilities. In: ASME 2013 international design engineering technical conferences and computers and information in engineering conferenceGoogle Scholar
  176. Sun J, Lu S, Lo S, Ma J, Xie Q (2018) Moving characteristics of single file passengers considering the effect of ship trim and heeling. Physica A 490:476CrossRefGoogle Scholar
  177. Tanaboriboon Y, Hwa SS, Chor CH (1986) Pedestrian characteristics study in singapore. J Transp Eng 112:229–235CrossRefGoogle Scholar
  178. Teixeira T, Dublon G, Savvides A (2010) A survey of human-sensing: methods for detecting presence, count, location, track, and identity. ACM Comput Surv 5:1Google Scholar
  179. Templer JA (1992) The staircase: studies of hazards, falls, and safer design. The MIT Press, Cambridge, MAGoogle Scholar
  180. Thompson PA, Marchant EW Simulex; developing new computer modelling techniques for evaluation. In: Kashiwagi T (ed) Fire safety science – proceedings of the fourth international symposium (Interscience Communications Ltd, West Yard House, Guildford Grove, London, 1994). The International Association for Fire Safety Science, pp 613–624. ISBN:1-88627-900-4Google Scholar
  181. Tian W, Song W, Ma J, Fang Z, Seyfried A, Liddle J (2012) Experimental study of pedestrian behaviors in a corridor based on digital image processing. Fire Saf J 47:8–15CrossRefGoogle Scholar
  182. Tomoeda A, Yanagisawa D, Nishinari K (2015) Escape velocity of the leader in a queue of pedestrians. In: Traffic and granular flow 2013. Springer, Berlin/Heidelberg, pp 213–218Google Scholar
  183. Transportation Research Board (2000) Highway capacity manual. Technical report, Transportation Research Board, Washington, DCGoogle Scholar
  184. Tsuji Y (2003) Numerical simulation of pedestrian flow at high densities. In: Galea ER (ed) Pedestrian and evacuation dynamics 2003. CMS Press, London, p 27Google Scholar
  185. van Oosterhout T, Englebienne G, Kröse B (2015) RARE: people detection in crowded passages by range image reconstruction. Mach Vis Appl, 26(5):561–573Google Scholar
  186. von Sivers I, Köster G (2015) Dynamic stride length adaptation according to utility and personal space. Transp Res B Methodol 74:104–117CrossRefGoogle Scholar
  187. Waldau N, Gattermann P, Knoflacher H, Schreckenberg M (eds) (2006) Pedestrian and evacuation dynamics 2005. Springer, BerlinGoogle Scholar
  188. Wardrop J (1952) Some theoretical aspects of road traffic research. Proc Inst Civ Eng 1:325–362Google Scholar
  189. Weckman LS, Mannikkö S (1999) Evacuation of a theatre: exercise vs calculations. Fire Mater 23:357–361CrossRefGoogle Scholar
  190. Weidmann U (1993) Transporttechnik der Fussgänger. Technical report. Schriftenreihe des IVT Nr. 90, Institut für Verkehrsplanung,Transporttechnik, Strassen- und Eisenbahnbau, ETH ZürichGoogle Scholar
  191. Weidmann U, Kirsch U, Schreckenberg M (2014) (eds) Pedestrian and evacuation dynamics 2012 (Zürich, 2014). Springer, Berlin/HeidelbergGoogle Scholar
  192. Wolf D, Grassberger P (eds) (1996) Friction, arching, contact dynamics. World Scientific, SingaporeGoogle Scholar
  193. Wong SC, Leung WL, Chan SH, Lam WHK, Yung NHC, Liu CY, Zhang P (2010) Bidirectional pedestrian stream model with oblique intersecting angle. J Transp Eng 136(3):234–242CrossRefGoogle Scholar
  194. Yamori K (1998) Going with the flow: micro-macro dynamics in the macrobehavioral patterns of pedestrian crowds. Psychol Rev 105:530–557CrossRefGoogle Scholar
  195. Yanagisawa D, Kimura A, Tomoeda A, Nishi R, Suma Y, Ohtsuka K, Nishinari K (2009) Introduction of frictional and turning function for pedestrian outflow with an obstacle. Phys Rev E 80:036110CrossRefGoogle Scholar
  196. Ye J, Chen X, Yang C, Wu J (2008) Walking behavior and pedestrian flow characteristics for different types of walking facilities. Transp Res Rec J Transp Res Board 2048:43–51CrossRefGoogle Scholar
  197. Zhang J, Klingsch W, Schadschneider A, Seyfried A (2011) Transitions in pedestrian fundamental diagrams of straight corridors and T-junctions. J Stat Mech Theory Exp 2011:06004Google Scholar
  198. Zhang J, Klingsch W, Rupprecht T, Schadschneider A, Seyfried A (2012a) Empirical study of turning and merging of pedestrian streams in T-junction. In: Fourth international symposium on agent-based modeling and simulation (ABModSim-4)Google Scholar
  199. Zhang J, Klingsch W, Schadschneider A, Seyfried A (2012b) Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram. J Stat Mech Theory Exp 2012:P02002Google Scholar
  200. Zhang J, Klingsch W, Schadschneider A, Seyfried A (2013) Experimental study of pedestrian flow through a T-junction. In: Kozlov V et al (eds) Traffic and granular flow ’11. Springer, HeidelbergGoogle Scholar
  201. Ziemer V, Seyfried A, Schadschneider A (2016) Congestion dynamics in pedestrian single-file motion. In: Traffic and granular flow 2015Google Scholar
  202. Zuriguel I (2014) Invited review: clogging of granular materials in bottlenecks. Pap Phys 6:060014CrossRefGoogle Scholar
  203. Zuriguel I, Parisi DR, Hidalgo RC, Lozano C, Janda A, Gago PA, Peralta JP, Ferrer LM, Pugnaloni LA, Clément E, Maza D, Pagonabarraga I, Garcimartín A (2014) Clogging transition of many-particle systems flowing through bottlenecks. Sci Rep 4:7324CrossRefGoogle Scholar

Books and Reviews

  1. Ali S, Nishino K, Manocha D, Shah M (eds) (2013) Modeling, simulation and visual analysis of crowds: a multidisciplinary perspective. Springer, New YorkGoogle Scholar
  2. Collective dynamics – a multidisciplinary journal for pedestrian dynamics, vehicular traffic and other systems of self-driven particles.
  3. DiNenno PJ (ed) (2002) SFPE handbook of fire protection engineering. National Fire Protection AssociationGoogle Scholar
  4. Knoop VL, Daamen W (eds) (2016) Traffic and granular flow ’15. Springer, Berlin/Heidelberg (see also previous issues of this conference series)Google Scholar
  5. Moeslund TB, Hilton A, Krüger V, Sigal L (eds) (2011) Visual analysis of humans – looking at people. Springer, LondonGoogle Scholar
  6. Online data archive of experiments studying the dynamics of pedestrians.
  7. Predtechenskii VM, Milinskii AI (1978) Planing for foot traffic flow in buildings, Amerint Publishing, New DelhiGoogle Scholar
  8. Schadschneider A, Chowdhury D, Nishinari K (2010) Stochastic transport in complex systems: from molecules to vehicles. Elsevier, AmsterdamzbMATHGoogle Scholar
  9. Schreckenberg M, Sharma SD (eds) (2002) Pedestrian and evacuation dynamics. Springer, BerlinGoogle Scholar
  10. Song W, Ma J, Fu L (eds) Pedestrian and evacuation dynamics 2016. Available from (see also previous issues of this conference series)
  11. Still K (2013) Introduction to Crowd Science. CRC Press, Boca RatonGoogle Scholar
  12. Timmermans H (ed) (2009) Pedestrian behavior – models, data collection and applications. Emerald, BingleyGoogle Scholar
  13. Tubbs JS, Meacham BJ (2007) Egress design solution – a guide to evacuation and crowd management planning. Wiley, HobokenGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Maik Boltes
    • 1
  • Jun Zhang
    • 2
  • Antoine Tordeux
    • 3
  • Andreas Schadschneider
    • 6
    Email author
  • Armin Seyfried
    • 4
    • 5
  1. 1.Institute for Advanced SimulationForschungszentrum JülichJülichGermany
  2. 2.State Key Laboratory of Fire ScienceUniversity of Science and Technology of ChinaHefeiChina
  3. 3.School of Mechanical Engineering and Safety EngineeringUniversity of WuppertalWuppertalGermany
  4. 4.Institute for Advanced SimulationForschungszentrum Jülich GmbHJülichGermany
  5. 5.School of Architecture and Civil EngineeringUniversity of WuppertalWuppertalGermany
  6. 6.Institut für Theoretische PhysikUniversität zu KölnKölnGermany

Personalised recommendations