Encyclopedia of Complexity and Systems Science

2009 Edition
| Editors: Robert A. Meyers (Editor-in-Chief)

Pedestrian, Crowd and Evacuation Dynamics

  • Dirk Helbing
  • Anders Johansson
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-30440-3_382

Definition of the Subject

The modeling of pedestrian motion is of great theoretical and practical interest. Recentexperimental efforts have revealed quantitative details of pedestrian interactions, which have been successfully cast into mathematicalequations. Furthermore, corresponding computer simulations of large numbers of pedestrians have been compared with the empirically observed dynamics ofcrowds. Such studies have led to a deeper understanding of how collective behavior on a macroscopic scale emerges from individual humaninteractions. Interestingly enough, the non-linear interactions of pedestrians lead to various complex, spatio-temporalpattern-formation phenomena. This includes the emergence of lanes of uniform walking direction, oscillations of the pedestrian flow at bottlenecks,and the formation of stripes in two intersecting flows. Such self-organized patterns of motion demonstrate that efficient, “intelligent”collective dynamics can be based on simple, local...

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Notes

Acknowledgments

The authors are grateful for partial financial support by the German Research Foundation(research projects He 2789/7-1, 8-1) and by the “Cooperative Center for Communication Networks Data Analysis”, a NAP project sponsored bythe Hungarian National Office of Research and Technology under grant No. KCKHA005.

Bibliography

Primary Literature

  1. 1.
    Hankin BD, Wright RA (1958) Passenger flow in subways. Operat Res Q 9:81–88 Google Scholar
  2. 2.
    Older SJ (1968) Movement of pedestrians on footways in shopping streets. Traffic Eng Control 10:160–163Google Scholar
  3. 3.
    Weidmann U (1993) Transporttechnik der Fußgänger. In: Schriftenreihe des Instituts für Verkehrsplanung, Transporttechnik, Straßen- und Eisenbahnbau. Institut für Verkehrsplanung, Transporttechnik, Straßen- und Eisenbahnbau, ZürichGoogle Scholar
  4. 4.
    Fruin JJ (1971) Designing for pedestrians: A level-of-service concept. In: Highway research record, Number 355: Pedestrians. Highway Research Board, Washington DC, pp 1–15Google Scholar
  5. 5.
    Pauls J (1984) The movement of people in buildings and design solutions for means of egress. Fire Technol 20:27–47Google Scholar
  6. 6.
    Whyte WH (1988) City. Rediscovering the center. Doubleday, New YorkGoogle Scholar
  7. 7.
    Helbing D (1997) Verkehrsdynamik. Springer, BerlinzbMATHGoogle Scholar
  8. 8.
    Helbing D, Buzna L, Johansson A, Werner T (2005) Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions. Transport Sci 39(1):1–24Google Scholar
  9. 9.
    Predtetschenski WM, Milinski AI (1971) Personenströme in Gebäuden – Berechnungsmethoden für die Projektierung. Müller, Köln-BraunsfeldGoogle Scholar
  10. 10.
    Transportation Research Board (1985) Highway Capacity Manual, Special Report 209. Transportation Research Board, Washington DCGoogle Scholar
  11. 11.
    Yuhaski SJ Jr, Macgregor Smith JM (1989) Modelling circulation systems in buildings using state dependent queueing models. Queueing Syst 4:319–338zbMATHGoogle Scholar
  12. 12.
    Garbrecht D (1973) Describing pedestrian and car trips by transition matrices. Traffic Q 27:89–109Google Scholar
  13. 13.
    Ashford N, O'Leary M, McGinity PD (1976) Stochastic modelling of passenger and baggage flows through an airport terminal. Traffic Engin Control 17:207–210Google Scholar
  14. 14.
    Borgers A, Timmermans H (1986) City centre entry points, store location patterns and pedestrian route choice behaviour: A microlevel simulation model. Socio-Econ Plan Sci 20:25–31Google Scholar
  15. 15.
    Helbing D (1993) Stochastische Methoden, nichtlineare Dynamik und quantitative Modelle sozialer Prozesse. Ph.D. thesis University of Stuttgart, 1992 (published by Shaker, Aachen)Google Scholar
  16. 16.
    Helbing D, Isobe M, Nagatani T, Takimoto K (2003) Lattice gas simulation of experimentally studied evacuation dynamics. Phys Rev E 67:067101ADSGoogle Scholar
  17. 17.
    Daamen W, Hoogendoorn SP (2003) Experimental research on pedestrian walking behavior (CDROM). In: Proceedings of the 82nd annual meeting at the transportation research board, Washington DCGoogle Scholar
  18. 18.
    Isobe M, Helbing D, Nagatani T (2004) Experiment, theory, and simulation of the evacuation of a room without visibility Phys Rev E 69:066132Google Scholar
  19. 19.
    Seyfried A, Steffen B, Klingsch W, Boltes M (2005) The fundamental diagram of pedestrian movement revisited. J Stat Mech P10002Google Scholar
  20. 20.
    Kretz T, Wölki M, Schreckenberg M (2006) Characterizing correlations of flow oscillations at bottlenecks. J Stat Mech P02005Google Scholar
  21. 21.
    Henderson LF (1974) On the fluid mechanics of human crowd motion. Transp Res 8:509–515Google Scholar
  22. 22.
    Hughes RL (2002) A continuum theory for the flow of pedestrians. Transp Res B 36:507–535Google Scholar
  23. 23.
    Helbing D (1992) A fluid-dynamic model for the movement of pedestrians. Complex Syst 6:391–415MathSciNetzbMATHGoogle Scholar
  24. 24.
    Hoogendoorn SP, Bovy PHL (2000) Gas-kinetic modelling and simulation of pedestrian flows. Transp Res Rec 1710:28–36Google Scholar
  25. 25.
    Helbing D (1991) A mathematical model for the behavior of pedestrians. Behav Sci 36:298–310Google Scholar
  26. 26.
    Helbing D, Molnár P (1995) Social force model for pedestrian dynamics. Phys Rev E 51:4282–4286Google Scholar
  27. 27.
    Gipps PG, Marksjö B (1985) A micro-simulation model for pedestrian flows. Math Comp Simul 27:95–105Google Scholar
  28. 28.
    Bolay K (1998) Nichtlineare Phänomene in einem fluid-dynamischen Verkehrsmodell. Master's thesis, University of StuttgartGoogle Scholar
  29. 29.
    Blue VJ, Adler JL (1998) Emergent fundamental pedestrian flows from cellular automata microsimulation. Transp Res Rec 1644:29–36Google Scholar
  30. 30.
    Fukui M, Ishibashi Y (1999) Self-organized phase transitions in cellular automaton models for pedestrians. J Phys Soc Japan 68:2861–2863ADSGoogle Scholar
  31. 31.
    Muramatsu M, Irie T, Nagatani T (1999) Jamming transition in pedestrian counter flow. Physica A 267:487–498Google Scholar
  32. 32.
    Klüpfel H, Meyer-König M, Wahle J, Schreckenberg M (2000) Microscopic simulation of evacuation processes on passenger ships. In: Bandini S, Worsch T (eds) Theory and practical issues on cellular automata. Springer, LondonGoogle Scholar
  33. 33.
    Burstedde C, Klauck K, Schadschneider A, Zittartz J (2001) Simulation of pedestrian dynamics using a 2-dimensional cellular automaton. Physica A 295:507–525ADSzbMATHGoogle Scholar
  34. 34.
    Gopal S, Smith TR (1990) NAVIGATOR: An AI-based model of human way-finding in an urban environment. In: Fischer MM, Nijkamp P, Papageorgiou YY (eds) Spatial choices and processes. North-Holland, Amsterdam, pp 169–200Google Scholar
  35. 35.
    Reynolds CW (1994) Evolution of corridor following behavior in a noisy world. In: Cliff D, Husbands P, Meyer J-A, Wilson S (eds) From animals to animats 3: Proceedings of the third international conference on simulation of adaptive behavior. MIT Press, Cambridge, pp 402–410Google Scholar
  36. 36.
    Helbing D (1992) A mathematical model for attitude formation by pair interactions. Behav Sci 37:190–214Google Scholar
  37. 37.
    Helbing D, Molnár P, Farkas I, Bolay K (2001) Self-organizing pedestrian movement. Env Planning B 28:361–383Google Scholar
  38. 38.
    Klockgether J, Schwefel H-P (1970) Two-phase nozzle and hollow core jet experiments. In: Elliott DG (ed) Proceedings of the eleventh symposium on engineering aspects of magnetohydrodynamics. California Institute of Technology, Pasadena, pp 141–148Google Scholar
  39. 39.
    Helbing D (1992) A mathematical model for behavioral changes by pair interactions. In: Haag G, Mueller U, Troitzsch KG (eds) Economic evolution and demographic change. Formal models in social sciences. Springer, Berlin, pp 330–348Google Scholar
  40. 40.
    Miller NE (1944) Experimental studies of conflict. In: Mc Hunt VJ (ed) Personality and the behavior disorders, vol 1. Ronald, New YorkGoogle Scholar
  41. 41.
    Miller NE (1959) Liberalization of basic S-R-concepts: Extension to conflict behavior, motivation, and social learning. In: Koch S (ed) Psychology: A study of science, vol 2. McGraw Hill, New YorkGoogle Scholar
  42. 42.
    Lewin K (1951) Field theory in social science. Harper, New YorkGoogle Scholar
  43. 43.
    Helbing D (1994) A mathematical model for the behavior of individuals in a social field. J Math Sociol 19(3):189–219Google Scholar
  44. 44.
    Hoogendoorn S, Bovy PHL (2003) Simulation of pedestrian flows by optimal control and differential games. Optim Control Appl Meth 24(3):153–172MathSciNetzbMATHGoogle Scholar
  45. 45.
    Johansson A, Helbing D, Shukla PK (2007) Specification of the social force pedestrian model by evolutionary adjustment to video tracking data. Adv Complex Syst 10:271–288MathSciNetzbMATHGoogle Scholar
  46. 46.
    Helbing D, Farkas I, Vicsek T (2000) Simulating dynamical features of escape panic. Nature 407:487–490ADSGoogle Scholar
  47. 47.
    Kerridge J, Chamberlain T (2005) Collecting pedestrian trajectory data in real-time. In: Waldau N, Gattermann P, Knoflacher H, Schreckenberg M (eds) Pedestrian and evacuation dynamics '05. Springer, BerlinGoogle Scholar
  48. 48.
    Hoogendoorn SP, Daamen W, Bovy PHL (2003) Extracting microscopic pedestrian characteristics from video data (CDROM). In: Proceedings of the 82nd annual meeting at the transportation research board. Mira Digital, Washington DCGoogle Scholar
  49. 49.
    Teknomo K (2002) Microscopic pedestrian flow characteristics: Development of an image processing data collection and simulation model. Ph?D thesis, Tohoku University JapanGoogle Scholar
  50. 50.
    Kadanoff LP (1985) Simulating hydrodynamics: A pedestrian model. J Stat Phys 39:267–283MathSciNetADSGoogle Scholar
  51. 51.
    Stanley HE, Ostrowsky N (eds) (1986) On growth and form. Nijhoff, BostonzbMATHGoogle Scholar
  52. 52.
    Arns T (1993) Video films of pedestrian crowds. StuttgartGoogle Scholar
  53. 53.
    Stølum H-H (1996) River meandering as a self-organization process. Nature 271:1710–1713Google Scholar
  54. 54.
    Rodríguez-Iturbe I, Rinaldo A (1997) Fractal river basins: Chance and self-organization. Cambridge University, CambridgeGoogle Scholar
  55. 55.
    Helbing D, Farkas I, Vicsek T (2000) (2000) Freezing by heating in a driven mesoscopic system. Phys Rev Lett 84:1240–1243ADSGoogle Scholar
  56. 56.
    Schelling T (1971) Dynamic models of segregation. J Math Sociol 1:143–186Google Scholar
  57. 57.
    Helbing D, Platkowski T (2000) Self-organization in space and induced by fluctuations. Int J Chaos Theory Appl 5(4):47–62Google Scholar
  58. 58.
    Ando K, Oto H, Aoki T (1988) Forecasting the flow of people. Railw Res Rev 45(8):8–13 (in Japanese)Google Scholar
  59. 59.
    Smith RA, Dickie JF (eds) (1993) Engineering for crowd safety. Elsevier, AmsterdamGoogle Scholar
  60. 60.
    Drager KH, Løvås G, Wiklund J, Soma H, Duong D, Violas A, Lanérés V (1992) EVACSIM – A comprehensive evacuation simulation tool. In: The proceedings of the 1992 Emergency Management and Engineering Conference. Society for Computer Simulation, Orlando, pp 101–108Google Scholar
  61. 61.
    Ebihara M, Ohtsuki A, Iwaki H (1992) A model for simulating human behavior during emergency evacuation based on classificatory reasoning and certainty value handling. Microcomput Civ Engin 7:63–71Google Scholar
  62. 62.
    Ketchell N, Cole S, Webber DM, Marriott CA, Stephens PJ, Brearley IR, Fraser J, Doheny J, Smart J (1993) The EGRESS code for human movement and behaviour in emergency evacuations. In: Smith RA, Dickie JF (eds) Engineering for crowd safety. Elsevier, Amsterdam, pp 361–370Google Scholar
  63. 63.
    Okazaki S, Matsushita S (1993) A study of simulation model for pedestrian movement with evacuation and queuing, In: Smith RA, Dickie JF (eds) Engineering for crowd safety. Elsevier, Amsterdam, pp 271–280Google Scholar
  64. 64.
    Still GK (1993) New computer system can predict human behaviour response to building fires. Fire 84:40–41Google Scholar
  65. 65.
    Still GK (2000) Crowd dynamics. Ph.D. thesis, University of WarwickGoogle Scholar
  66. 66.
    Thompson PA, Marchant EW (1993) Modelling techniques for evacuation. In: Smith RA, Dickie JF (eds) Engineering for crowd safety. Elsevier, Amsterdam, pp 259–269Google Scholar
  67. 67.
    Løvås GG (1998) On the importance of building evacuation system components. IEEE Trans Engin Manag 45:181–191Google Scholar
  68. 68.
    Hamacher HW, Tjandra SA (2001) Mathematical modelling of evacuation problems: A state of the art. In: Schreckenberg M, Sharma SD (eds) Pedestrian and evacuation dynamics. Springer, Berlin, pp 227–266Google Scholar
  69. 69.
    Keating JP (1982) The myth of panic. Fire J 57–61, 147Google Scholar
  70. 70.
    Elliott D, Smith D (1993) Football stadia disasters in the United Kingdom: Learning from tragedy? Ind Env Crisis Q 7(3):205–229Google Scholar
  71. 71.
    Jacobs BD, 't Hart P (1992) Disaster at Hillsborough Stadium: A comparative analysis. In: Parker DJ, Handmer JW (eds) Hazard management and emergency planning, Chapt 10. James and James Science, LondonGoogle Scholar
  72. 72.
    Canter D (ed) (1990) Fires and human behaviour. Fulton, LondonGoogle Scholar
  73. 73.
    Mintz A (1951) Non-adaptive group behavior. J Abnorm Norm Soc Psychol 46:150–159Google Scholar
  74. 74.
    Miller DL (1985) Introduction to collective behavior (Fig. 3.3 and Chap. 9). Wadsworth, BelmontGoogle Scholar
  75. 75.
    Coleman JS (1990) Foundations of social theory, Chaps. 9 and 33. Belkamp, CambridgeGoogle Scholar
  76. 76.
    Johnson NR (1987) Panic at “The Who Concert Stampede”: An empirical assessment. Soc Probl 34(4):362–373Google Scholar
  77. 77.
    LeBon G (1960) The crowd. Viking, New YorkGoogle Scholar
  78. 78.
    Quarantelli E (1957) The behavior of panic participants Sociol Soc Res 41:187–194Google Scholar
  79. 79.
    Smelser NJ (1963) Theory of collective behavior. Free Press, New YorkGoogle Scholar
  80. 80.
    Brown R (1965) Social psychology. Free Press, New YorkGoogle Scholar
  81. 81.
    Turner RH, Killian LM (1987) Collective behavior, 3rd edn. Prentice Hall, Englewood CliffsGoogle Scholar
  82. 82.
    Bryan JL (1985) Convergence clusters. Fire J 27–30, 86–90Google Scholar
  83. 83.
    Axelrod R, Hamilton WD (1981) The evolution of cooperation. Science 211:1390–1396MathSciNetADSzbMATHGoogle Scholar
  84. 84.
    Axelrod R, Dion D (1988) The further evolution of cooperation. Science 242:1385–1390ADSGoogle Scholar
  85. 85.
    Glance NS, Huberman BA (1994) The dynamics of social dilemmas. Scientific American 270:76–81Google Scholar
  86. 86.
    Kelley HH, Condry JC Jr, Dahlke AE, Hill AH (1965) Collective behavior in a simulated panic situation. J Exp Soc Psychol 1:20–54Google Scholar
  87. 87.
    Helbing D, Johansson A, Al-Abideen HZ (2007) The dynamics of crowd disasters: An empirical study. Phys Rev E 75:046109Google Scholar
  88. 88.
    Fruin JJ (1993) The causes and prevention of crowd disasters. In: Smith RA, Dickie JF (eds) Engineering for crowd safety. Elsevier, Amsterdam, pp 99–108Google Scholar
  89. 89.
    Ristow GH, Herrmann HJ (1994) Density patterns in two-dimensional hoppers. Phys Rev E 50:R5–R8ADSGoogle Scholar
  90. 90.
    Wolf DE, Grassberger P (eds) (1997) Friction, arching, contact dynamics. World Scientific, SingaporeGoogle Scholar
  91. 91.
    Helbing D, Johansson A, Mathiesen J, Jensen HM, Hansen A (2006) Analytical approach to continuous and intermittent bottleneck flows. Phys Rev Lett 97:168001ADSGoogle Scholar
  92. 92.
    Ghashghaie S, Breymann W, Peinke J, Talkner P, Dodge Y (1996) Turbulent cascades in foreign exchange markets. Nature 381:767–770ADSGoogle Scholar
  93. 93.
    Peng G, Herrmann HJ (1994) Density waves of granular flow in a pipe using lattice-gas automata. Phys Rev E 49:R1796–R1799ADSGoogle Scholar
  94. 94.
    Radjai F, Roux S (2002) Turbulentlike fluctuations in quasistatic flow of granular media. Phys Rev Lett 89:064302ADSGoogle Scholar
  95. 95.
    Sreenivasan KR (1990) Turbulence and the tube. Nature 344:192–193ADSGoogle Scholar
  96. 96.
    Cates ME, Wittmer JP, Bouchaud J-P, Claudin P (1998) Jamming, force chains, and fragile matter. Phys Rev Lett 81:1841–1844ADSGoogle Scholar
  97. 97.
    Bak P, Christensen K, Danon L, Scanlon T (2002) Unified scaling law for earthquakes. Phys Rev Lett 88:178501ADSGoogle Scholar
  98. 98.
    Johnson PA, Jia X (2005) Nonlinear dynamics, granular media and dynamic earthquake triggering. Nature 437:871–874ADSGoogle Scholar
  99. 99.
    Johansson A, Helbing D (2007) Pedestrian flow optimization with a genetic algorithm based on Boolean grids. In: Waldau N, Gattermann P, Knoflacher H, Schreckenberg M (eds) Pedestrian and evacuation dynamics 2005. Springer, Berlin, pp 267–272Google Scholar
  100. 100.
    Baeck T (1996) Evolutionary algorithms in theory and practice. Oxford University Press, New YorkzbMATHGoogle Scholar

Books and Reviews

  1. 101.
    Decicco PR (ed) (2001) Evacuation from fires. Baywood, AmityvilleGoogle Scholar
  2. 102.
    Helbing D (2001) Traffic and related self-driven many-particle systems. Rev Mod Phys 73:1067–1141ADSGoogle Scholar
  3. 103.
    Helbing D, Molnár P, Farkas I, Bolay K (2001) Self-organizing pedestrian movement. Environ Plan B 28:361–383Google Scholar
  4. 104.
    Helbing D, Buzna L, Johansson A, Werner T (2005) Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions. Transp Sci 39(1):1–24Google Scholar
  5. 105.
    Le Bon G (2002) The Crowd. Dover, New York (1st edn: 1895)Google Scholar
  6. 106.
    Predtechenskii VM, Milinskii AI (1978) Planning for foot traffic flow in buildings. Amerind, New DelhiGoogle Scholar
  7. 107.
    Schreckenberg M, Sharma SD (eds) (2002) Pedestrian and evacuation dynamics. Springer, BerlinzbMATHGoogle Scholar
  8. 108.
    Smith RA, Dickie JF (eds) (1993) Engineering for crowd safety. Elsevier, AmsterdamGoogle Scholar
  9. 109.
    Still GK (2000) Crowd Dynamics. Ph.D thesis, University of WarwickGoogle Scholar
  10. 110.
    Surowiecki J (2005) The Wisdom of Crowds. Anchor, New YorkGoogle Scholar
  11. 111.
    Tubbs J, Meacham B (2007) Egress design solutions: A guide to evacuation and crowd management planning. Wiley, New YorkGoogle Scholar
  12. 112.
    Waldau N, Gattermann P, Knoflacher H (eds) (2006) Pedestrian and evacuation dynamics 2005. Springer, BerlinGoogle Scholar
  13. 113.
    Weidmann U (1993) Transporttechnik der Fußgänger. In: Schriftenreihe des Institut für Verkehrsplanung, Transporttechnik, Straßen- und Eisenbahnbau 90. ETH ZürichGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Dirk Helbing
    • 1
    • 2
  • Anders Johansson
    • 1
  1. 1.ETH ZurichZurichSwitzerland
  2. 2.Institute for Advanced StudyCollegium BudapestBudapestHungary