Cover Image

Placing Large Group Relations into Pedestrian Dynamics: Psychological Crowds in Counterflow

Anne Templeton, John Drury, Andy Philippides

Abstract


Understanding influences on pedestrian movement is important to accurately simulate crowd behaviour, yet little research has explored the psychological factors that influence interactions between large groups in counterflow scenarios. Research from social psychology has demonstrated that social identities can influence the micro-level pedestrian movement of a psychological crowd, yet this has not been extended to explore behaviour when two large psychological groups are co-present. This study investigates how the presence of large groups with different social identities can affect pedestrian behaviour when walking in counterflow. Participants (N = 54) were divided into two groups and primed to have identities as either ‘team A’ or ‘team B’. The trajectories of all participants were tracked to compare the movement of team A when walking alone to when walking in counterflow with team B, based on their i) speed of movement and distance walked, and ii) proximity between participants. In comparison to walking alone, the presence of another group influenced team A to collectively self-organise to reduce their speed and distance walked in order to walk closely together with ingroup members. We discuss the importance of incorporating social identities into pedestrian group dynamics for empirically validated simulations of counterflow scenarios.

Keywords


pedestrians; crowds

Full Text:

PDF

References


Owen, S.: Crowd modelling advice for the london olympics 2012 (2012). URL https://www.movementstrategies.com/case-studies/london-olympics-2012. [Online; accessed 20-04-2017]

Crowdvision: What we offer (2016). URL http://www.crowdvision.com/. [Online; accessed 20-04-2017]

Burrows, P.: Measuring the customer’s journey through london city airport 9(2), 103-108 (2015). URL http://www.crowdvision.com/wp-content/uploads/2016/10/LCY-AIRPORT-MANAGEMENT-VOL-9.pdf

Transport for london. london’s public transport assignment model (railplan) (2014). URL http://content.tfl.gov.uk/london-public-transport-assignment-model.pdf. [Online; accessed 20-04-2017]

Moussaïd, M., Trauernicht, M.: Patterns of cooperation during collective emergencies in the help-or-escape social dilemma 6 (2016). doi:10.1038/srep33417. [Online; accessed 20-04-2017]

Moussaïd, M., Helbing, D., Garnier, S., Johansson, A., Combe, M., Theraulaz, G.: Experimental study of the behavioural mechanisms underlying self-organization in human crowds 276(1668), 2755-62 (2009). doi:10.1098/rspb.2009.0405

Vizzari, G., Manenti, L., Ohtsuka, K., Shimura, K.: An agent-based pedestrian and group dynamics model applied to experimental and real-world scenarios 19(1), 32-45 (2015). doi:10.1080/15472450.2013.856718

Bera, A., Randhavane, T., Manocha, D.: Aggressive, tense or shy? identifying personality traits from crowd videos pp. 112-118 (2017). doi:10.24963/ijcai.2017/17

Zoumpoulaki, A., Avradinis, N., Vosinakis, S.: A multi-agent simulation framework for emergency evacuations incorporating personality and emotions pp. 423-428 (2010). doi:10.1007/978-3-642-12842-4_54

Durupinar, F., Pelechano, N., Allbeck, J., Gudukbay, U., Badler, N.: How the ocean personality model affects the perceptions of crowds 31(3), 21-31 (2011). doi:10.1109/MCG.2009.105

Qu, W., Zhang, H., Zhao, W., Zhang, K., Ge, Y.: The effect of cognitive errors, mindfulness and personality traits on pedestrian behaviour in a chinese sample 41(A), 29-37. (2016). doi:10.1016/j.trf.2016.06.009

Zhan, X., Yang, L., Zhu, K., Kong, X., Rao, P., Zhang, T.: Experimental study of the impact of personality traits on occupant exit choice during building evacuations 62, 548-553. (2013). doi:10.1016/j.proeng.2013.08.099

Bohari, Z., Backok, S., Osman, M.: Simulating the pedestrian movement in the public transport infrastructure 222(23), 791-799. (2016). doi:10.1016/j.sbspro.2016.05.167

Gutierrez, D., Frischer, B., Cerezo, E., Gomez, A., Seron, F.: Ai and virtual crowds: Populating the colosseum 8(2), 176-85 (2007). doi:10.1016/j.culher.2007.01.007

Beloglazov, A., Almashor, M., Abebe, A., Richter, J., Steer, K.: Simulation of wildfire evacuation with dynamic factors and model composition 60, 176-85 (2016). doi:10.1016/j.simpat.2015.10.002

Bode, N., Miller, J., O'Gorman, R., Codling, E.: Increased costs reduce reciprocal helping behaviour of humans in a virtual evacuation experiment 5, 15896- (2014). doi:10.1038/srep15896

Templeton, A., Drury, J., Phillipides, A.: Increased costs reduce reciprocal helping behaviour of humans in a virtual evacuation experiment (2018). doi:10.1098/rsos.180172

Gallup, A., Hale, J., Sumpter, D., Garnier, S., Kacelnik, A., Krebs, J., Couzin, I.: Visual attention and the acquisition of information in human crowds 109(19), 7245-50 (2012). doi:10.1073/pnas.1116141109

Heliövaara, S., Korhonen, T., Hostikka, S., Ehtamo, H.: Counterflow model for agent-based simulation of crowd dynamics 48, 89-100 (2012). doi:10.1016/j.buildenv.2011.08.020

Helbing, D., Farkas, I., Vicsek, T.: Simulating dynamical features of escape panic 407(6803), 487-90 (2000). doi:10.1016/j.buildenv.2011.08.020

Chow, W.: ‘waiting time’ for evacuation in crowded areas 42(10), 3757-61 (2007). doi:10.1016/j.buildenv.2006.08.0010

Purser, D., Bensilum, M.: Quantification of behaviour for engineering design standards and escape time calculations 38(2), 157-182 (2001). doi:10.1016/S0925-7535(00)00066-7

Nilsson, D., Johansson, A.: Social influence during the initial phase of a fire evacuation—analysis of evacuation experiments in a cinema theatre 44(1), 71-9 (2009). doi:10.1016/j.firesaf.2008.03.008

Bode, N., Wagoum, A., Codling, E.: Human responses to multiple sources of directional information in virtual crowd evacuations 11(91), 20130904 (2014). doi:10.1098/rsif.2013.0904

Blue, V., Adler, J.: Cellular automata microsimulation for modelling bi-directional pedestrian walkways 35(3), 293-312. (2001). doi:10.1016/S0191-2615(99)00052-1

Tajima, Y., Takimoto, K., Nagatani, T.: Pattern formation and jamming transition in pedestrian counter flow 313, 709-723 (2002). doi:10.1016/S0378-4371(02)00965-2

Asano, M., Iryo, T., Kuwahara, M.: Microscopic pedestrian simulation model combined with a tactical model for route choice behaviour 18(6), 842-855 (2010). doi:10.1016/j.trc.2010.01.005

Guo, R., Wong, S., Huang, H., Zhang, P., Lam, W.: A microscopic pedestrian-simulation model and its application to intersecting flows 389(3), 515-526 (2010). doi:10.1016/j.physa.2009.10.008

Teknomo, K.: Application of microscopic pedestrian simulation model 9(1), 15-27 (2006). doi:10.1016/j.trf.2005.08.006

Zheng, W., Nakamura, H., Chen, P.: A modified social force model for pedestrian behaviour simulation at signalized crosswalks 138, 521-530 (2014). doi:10.1016/j.sbspro.2014.07.233

Treuille, A., Cooper, S., Popovic, Z.: Continuum crowds 25(3), 1160-1168 (2006)

Helbing, D., Molnár, P., Farkas, I., Bolay, K.: Self-organizing pedestrian movement 28(3), 361-83 (2001)

Reuter, V., Bergner, B., Köster, G., Seitz, M., Treml, F., Hartmann, D.: On modelling groups in crowds: Empirical evidence and simulation results including large groups 28(3), 835-845 (2013). doi:10.1007/978-3-319-02447-9_70

Moussaïd, M., Perozo, N., Garnier, S., Helbing, D., Theraulaz, G.: The walking behaviour of pedestrian social groups and its impact on crowd dynamics 5(4), e10047 (2010). doi:10.1371/journal.pone.0010047

Köster, G., Seitz, M., Treml, F., Hartmann, D., Klein, W.: On modelling the influence of group formations in a crowd 6(3), 397-414 (2011). doi:10.1080/21582041.2011.619867

Reicher, S.: Mass action and mundane reality: An argument for putting crowd analysis at the centre of the social sciences 6(3), 433-449 (2011). doi:10.1080/21582041.2011.619347

Turner, J., Hogg, M., Oakes, P., Reicher, S., Wetherell, M.: Rediscovering the social group: A self-categorization theory (1987)

Turner, J.: Group polarization pp. 48-79 (1991)

Alnabulsi, H., Drury, J.: Social identification moderates the effect of crowd density on safety at the hajj 111(25), 9091-9096 (2014). doi:10.1073/pnas.1404953111

Pandey, K., Stevenson, C., Shankar, S., Hopkins, N., Reicher, S.: Cold comfort at the magh mela: Social identity processes and physical hardship 53(4), 675-90 (2014). doi:10.1111/bjso.12054

Neville, F., Reicher, S.: The experience of collective participation: Shared identity, relatedness and emotionality 6(3), 377-396 (2011). doi:10.1080/21582041.2012.627277

Drury, J., Novelli, D., Stott, C.: Managing to avert disaster: Explaining collective resilience at an outdoor music event 45(4), 533-547 (2015). doi:10.1002/ejsp.2108

Drury, J., Cocking, C., Reicher, S.: The nature of collective resilience: Survivor reactions to the 2005 london bombings 27(1), 66-95 (2009)

Drury, J., Cocking, C., Reicher, S., Burton, A., Schofield, D., Hardwick, A., Graham, D., Langston, P.: Cooperation versus competition in a mass emergency evacuation: A new laboratory simulation and a new theoretical model 41(3), 957-70 (2009). doi:10.3758/BRM.41.3.957

Novelli, D., Drury, J., Reicher, S.: Come together: Two studies concerning the impact of group relations on personal space 49(2), 223-236 (2010). doi:10.1348/014466609X449377

Tajfel, H., Billig, M.G., Bundy, R.P., Flament, C.: Social categorization and intergroup behaviour 1(2), 149-178 (1971). doi:http://dx.10.1002/ejsp.2420010202

Doosje, B., Ellemers, N., Spears, R.: Perceived intragroup variability as a function of group status and identification 31, 410-436 (1995)

Leach, C., van Zomeren, M., Zebel, S., Wick, M., Ouwerkerk, J., Spears, R.: Group-level self-definition and self-investment: A hierarchical (multicomponent) model of in-group identification 95(1), 144-165 (2008). doi:10.1037/0022-3514.95.1.144

Sievers, J.: VoronoiLimit(varargin) (2016). URL https://uk.mathworks.com/matlabcentral/fileexchange/34428-voronoilimit-varargin-?requestedDomain=www.mathworks.com

L., H., PM., B.: Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives 6(1), 1-55 (1999). doi:10.1080/10705519909540118

Curran, P., Obeidat, K., Losardo, D.: Twelve frequently asked questions about growth curve modeling 11(2), 121-36 (2010). doi:10.1080/15248371003699969




DOI: http://dx.doi.org/10.17815/CD.2019.23

Copyright (c) 2019 Anne Templeton

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.