Modelling Social Identification and Helping in Evacuation Simulation

Social scientists have criticized computer models of pedestrian streams for their treatment of psychological crowds as mere aggregations of individuals. Indeed most models for evacuation dynamics use analogies from physics where pedestrians are considered as particles. Although this ensures that the results of the simulation match important physical phenomena, such as the deceleration of the crowd with increasing density, social phenomena such as group processes are ignored. In particular, people in a crowd have social identities and share those social identities with the others in the crowd. The process of self-categorization determines norms within the crowd and influences how people will behave in evacuation situations. The authors formulate the application of social identity in pedestrian simulation algorithmically. The goal is to examine whether it is possible to carry over the psychological model to computer models of pedestrian motion so that simulation results correspond to observations from crowd psychology. That is, the authors quantify and formalize empirical research on and verbal descriptions of the effect of group identity on behavior. They use uncertainty quantification to analyze the model’s behavior when crucial model parameters are varied. In this first approach the authors restrict themselves to a specific scenario that was thoroughly investigated by crowd psychologists and where some quantitative data is available: the bombing and subsequent evacuation of a London underground tube carriage on July 7th 2005.


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  • Accession Number: 01607988
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 25 2016 11:03AM