The Conference in Pedestrian and Evacuation Dynamics 2014 (PED2014) Humans do not always act selfishly: social identity and helping in emergency evacuation simulation

To monitor and predict the behaviour of a crowd, it is imperative that the technology used is based on an accurate understanding of crowd psychology. However, most simulations of evacuation scenarios rely on outdated assumptions about the way people behave or only consider the locomotion of pedestrian movement. We present a social model for pedestrian simulation based on self-categorisation processes during an emergency evacuation. We demonstrate the impact of this new model on the behaviour of pedestrians and on evacuation times. In addition to the Optimal Steps Model for locomotion, we add a realistic social model of collective behaviour. c

[1]  Andrew Philippides,et al.  From Mindless Masses to Small Groups: Conceptualizing Collective Behavior in Crowd Modeling , 2015, Review of general psychology : journal of Division 1, of the American Psychological Association.

[2]  B. D. Hankin,et al.  Passenger Flow in Subways , 1958 .

[3]  Wu Zong-zhi,et al.  Research and application on risk assessment DEA model of crowd crushing and trampling accidents in subway stations , 2012 .

[4]  S. Reicher,et al.  The St. Pauls' riot: An explanation of the limits of crowd action in terms of a social identity model. , 1984 .

[5]  Michael A. Hogg,et al.  Blackwell Handbook of Social Psychology: Group Processes , 2001 .

[6]  Wolfram Klein,et al.  On modelling the influence of group formations in a crowd , 2011 .

[7]  J. Turner.  Social categorization and the self-concept: A social cognitive theory of group behavior. , 2010 .

[8]  Damian Schofield,et al.  Cooperation versus competition in a mass emergency evacuation: A new laboratory simulation and a new theoretical model , 2009, Behavior research methods.

[9]  John Drury,et al.  Social identification moderates the effect of crowd density on safety at the Hajj , 2014, Proceedings of the National Academy of Sciences.

[10]  J. Jetten,et al.  Taking the strain: social identity, social support, and the experience of stress. , 2005, The British journal of social psychology.

[11]  William H. K. Lam,et al.  PEDESTRIAN FLOW CHARACTERISTICS IN HONG KONG , 1995 .

[12]  Nan Dong,et al.  Multi-part sparse representation in random crowded scenes tracking , 2013, Pattern Recognit. Lett..

[13]  John Drury,et al.  Everyone for themselves? A comparative study of crowd solidarity among emergency survivors. , 2009, The British journal of social psychology.

[14]  Mohcine Chraibi,et al.  Generalized centrifugal-force model for pedestrian dynamics. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  S. Worchel,et al.  Psychology of intergroup relations , 1986 .

[16]  Martin L. Leibowitz,et al.  Cooperation versus Competition , 2000 .

[17]  Hongyong Yuan,et al.  Empirical study of a unidirectional dense crowd during a real mass event , 2013 .

[18]  R. Bailey,et al.  The Social Determinants of Mental Health , 2015 .

[19]  Roberto González,et al.  Emergent social identity and observing social support predict social support provided by survivors in a disaster: solidarity in the 2010 Chile earthquake , 2016 .

[20]  Henry Hexmoor,et al.  Exploiting the Imperialist Competition Algorithm to determine exit door efficacy for public buildings , 2014, Simul..

[21]  Paul Langston,et al.  Crowd dynamics discrete element multi-circle model , 2006 .

[22]  Ulrich Weidmann,et al.  Transporttechnik der Fussgänger , 1992 .

[23]  Armin Seyfried,et al.  Microscopic insights into pedestrian motion through a bottleneck, resolving spatial and temporal variations , 2011, Collective Dynamics.

[24]  David V. Canter,et al.  Fires and human behaviour , 1980 .

[25]  Dirk Helbing,et al.  Simulating dynamical features of escape panic , 2000, Nature.

[26]  Paul Champsaur.  Cooperation versus competition , 1975 .

[27]  Xiao Zhi Gao,et al.  Influences of intelligent evacuation guidance system on crowd evacuation in building fire , 2014 .

[28]  Haibo Chen,et al.  Geometry-constrained crowd formation animation , 2014, Comput. Graph..

[29]  Gerta Köster,et al.  Natural discretization of pedestrian movement in continuous space. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  H. Tajfel,et al.  An integrative theory of intergroup conflict. , 1979 .

[31]  Christopher Cocking,et al.  The Nature of Collective Resilience: Survivor Reactions to the 2005 London Bombings , 2009, International Journal of Mass Emergencies & Disasters.

[32]  Robert Plomin,et al.  Genetics of Callous-Unemotional Behavior in Children , 2013, PloS one.

[33]  Vikas Agrawal,et al.  An agent-based simulation system for concert venue crowd evacuation modeling in the presence of a fire disaster , 2014, Expert Syst. Appl..

[34]  Edward Lester,et al.  Modelling contra-flow in crowd dynamics DEM simulation. , 2009 .

[35]  B. Aguirre,et al.  Contributions of social science to agent-based models of building evacuation , 2011 .

[36]  Chimay J. Anumba,et al.  Computer simulations vs. building guidance to enhance evacuation performance of buildings during emergency events , 2011, Simul. Model. Pract. Theory.

[37]  Dirk Helbing,et al.  How simple rules determine pedestrian behavior and crowd disasters , 2011, Proceedings of the National Academy of Sciences.

[38]  S. Reicher,et al.  The experience of collective participation: shared identity, relatedness and emotionality , 2011 .

[39]  Maria Davidich,et al.  Predicting Pedestrian Flow: A Methodology and a Proof of Concept Based on Real-Life Data , 2013, PloS one.

[40]  Robson dos S. Franca,et al.  Proposing a cognitive multi-agent model for the panic in crowds phenomenon , 2009, 2009 Second International Conference on the Applications of Digital Information and Web Technologies.

[41]  Bernhard Steffen,et al.  New Insights into Pedestrian Flow Through Bottlenecks , 2009, Transp. Sci..

[42]  F. Reid.  Rediscovering the Social Group: A Self-Categorization Theory , 1987 .