Abstract
In this chapter we present several concepts and foundations that aim to facilitate and help reading this thesis manuscript, as well as serve as a basis for a better understanding of the next chapters. The content covers crowds and groups of people. This chapter characterizes crowds and their types and presents the concept of proxemics, which deals with interpersonal distances, which may vary across cultures. Also it presents the fundamental diagrams concept, describing the relationship between speed, density, and flow of pedestrians in a crowd, which may also be influenced by cultural aspects.
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Notes
- 1.
Jam effect occurs when the density of people is so high that the crowd stops moving.
References
Albeverio S, Andrey D, Giordano P, Vancheri A (2007) The dynamics of complex urban systems: an interdisciplinary approach. Physica-Verlag. http://books.google.com.br/books?id=WkX176swP0UC
Allain P, Courty N, Corpetti T (2014) Optimal crowd editing. Graph Models 76(1):1–16. https://doi.org/10.1016/j.gmod.2013.09.001, http://www.sciencedirect.com/science/article/pii/S1524070313000271
Benesch H (1995) Atlas de la psychologie. La Pochothèque. Librairie générale française, Paris
Berlonghi AE (1995) Understanding and planning for different spectator crowds. Saf Sci 18(4):239–247. Engineering for Crowd Safety
Bon GL (1986) A Psicologia das Multidões. Presses Universitaires de France, Paris
Bon GL (2012) The crowd: a study of the popular mind. Courier Corporation, Mineola
Chattaraj U, Seyfried A, Chakroborty P (2009) Comparison of pedestrian fundamental diagram across cultures. Adv Complex Syst 12(3):393–405. https://doi.org/10.1142/S0219525909002209
Davidich M, Koster G (2013) Predicting pedestrian flow: a methodology and a proof of concept based on real-life data. PLoS ONE 8(12):833–855
Davies A, Yin JH, Velastin S (1995) Crowd monitoring using image processing. Electron Commun Eng J 7(1):37–47. https://doi.org/10.1049/ecej:19950106
Forsyth D (2010) Group dynamics. Wadsworth/Cengage Learning. https://books.google.com.br/books?id=nwY6PgAACAAJ
Fruin J (1971) Pedestrian planning and design. Metropolitan Association of Urban Designers and Environmental Planners. http://books.google.com.br/books?id=AydSAAAAMAAJ
Goode E (1992) Collective behavior. Saunders College Pub, Fort Worth
Hall ET (1966) The hidden dimension, a doubleday anchor book, vol 609. Doubleday, Garden City
Helbing D (1991) A mathematical model for the behavior of pedestrians. Behav Sci 36(4):298–310. https://doi.org/10.1002/bs.3830360405
Helbing D, Johansson A, Al-Abideen HZ (2007) Dynamics of crowd disasters: an empirical study. Phys Rev E Stat Nonlin Soft Matter Phys 75(4 Pt 2):046109
Henderson LF (1971) The statistics of crowd fluids. Nature 229(5284):381–383
Jacques Junior J, Raupp Musse S, Jung C (2010) Crowd analysis using computer vision techniques. IEEE Signal Process Mag 27(5):66–77. https://doi.org/10.1109/MSP.2010.937394
Jelić A, Appert-Rolland C, Lemercier S, Pettré J (2012) Properties of pedestrians walking in line: fundamental diagrams. Phys Rev E 85:036111. https://doi.org/10.1103/PhysRevE.85.036111
Kapadia M, Shoulson A, Durupinar F, Badler NI (2013) Authoring multi-actor behaviors in crowds with diverse personalities. In: Ali S, Nishino K, Manocha D, Shah M (eds) Modeling, simulation and visual analysis of crowds. The international series in video computing, vol 11. Springer, New York, pp 147–180
Kendall D (2016) Sociology in our times. Cengage Learning, Boston
Li W, Di Z, Allbeck JM (2012) Crowd distribution and location preference. Comput Animat Virtual Worlds 23(3–4):343–351. https://doi.org/10.1002/cav.1447
Moussaid M, Helbing D, Garnier S, Johansson A, Combe M, Theraulaz G (2009) Experimental study of the behavioural mechanisms underlying self-organization in human crowds. Proc Biol Sci 276(1668):2755–2762
Padgham M (2012) Human movement is both diffusive and directed. PLoS ONE 7(5):377–384
Pan X, Han CS, Dauber K, Law KH (2007) A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations. AI Soc 22(2):113–132. https://doi.org/10.1007/s00146-007-0126-1
Sommer R (1979) Personal space. Prentice Hall, Englewood Cliffs
Still GK (2000) Crowd dynamics. Phd thesis, University of Warwick, Coventri
Turner JC (1981) The experimental social psychology of intergroup behavior. In: Turner JC, Giles H (eds) Intergroup behaviour. Unversity of Chicago Press, Chicago, p 66
Vilanova F, Beria FM, Costa AB, Koller SH (2017) Deindividuation: from le bon to the social identity model of deindividuation effects. Cogent Psychol 4:1–21
Weidmann U (1993) Transporttechnik der fussgänger. Technical report, Institut für Verkehrsplanung, ETH Zürich
Wu N (2002) A new approach for modeling of fundamental diagrams. Transp Res Part A Policy Pract 36(10):867–884. https://doi.org/10.1016/S0965-8564(01)00043-X, http://www.sciencedirect.com/science/article/pii/S096585640100043X
Zhang J (2012) Pedestrian fundamental diagrams: comparative analysis of experiments in different geometries. Diss., Dr., Universität Wuppertal, Jülich, universität Wuppertal, 2012
Zhang J, Klingsch W, Schadschneider A, Seyfried A (2012) Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram. J Stat Mech 2012(2):P02002. http://stacks.iop.org/1742-5468/2012/i=02/a=P02002
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Favaretto, R.M., Musse, S.R., Costa, A.B. (2019). Crowds and Groups of People. In: Emotion, Personality and Cultural Aspects in Crowds. Springer, Cham. https://doi.org/10.1007/978-3-030-22078-5_2
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