From Mindless Masses to Small Groups: Conceptualizing Collective Behavior in Crowd Modeling

Abstract

Computer simulations are increasingly used to monitor and predict behavior at large crowd events, such as mass gatherings, festivals and evacuations. We critically examine the crowd modeling literature and call for future simulations of crowd behavior to be based more closely on findings from current social psychological research. A systematic review was conducted on the crowd modeling literature (N = 140 articles) to identify the assumptions about crowd behavior that modelers use in their simulations. Articles were coded according to the way in which crowd structure was modeled. It was found that 2 broad types are used: mass approaches and small group approaches. However, neither the mass nor the small group approaches can accurately simulate the large collective behavior that has been found in extensive empirical research on crowd events. We argue that to model crowd behavior realistically, simulations must use methods which allow crowd members to identify with each other, as suggested by self-categorization theory.

Age and Group-driven Pedestrian Behaviour: from Observations to Simulations

“…Analyses of pedestrian dynamics not considering this aspect have a reduced accuracy since grouping was found to negatively impact speed, flow rate and evacuation time [14]. In particular, elements such as the level of density, the presence of obstacles and the geometry of the environment, can create difficulties in movement coordination among group members, depending on: the need to maintain spatial cohesion to communicate while walking (proxemic behaviour) [15] and/or the urgency to evacuate together in case of emergency (affiliative behaviour) [16].…”

Parsimony versus Reductionism: How Can Crowd Psychology be Introduced into Computer Simulation?

“…Over the past decade, there has been increased recognition that the concept of a shared social identity is necessary for more realistic simulation of human collective behaviour (Aguirre et al, 2011;Köster et al, 2011;Langston, Masling, & Asmar, 2006;Smith et al, 2009;Templeton et al, 2015). The ability of self-categorisation theory to explain collective behaviour in numerous contexts indicates that computer simulations could benefit from applying this theory to adequately reproduce a broad variety of collective behaviour scenarios.…”

“…On the other hand, there are psychological crowds where the members of a crowd share a group identity, which affects their behaviour . Hence, in order to accurately simulate different types of crowds, While the importance of crowd psychology for engineering has been noted (Aguirre, El-Tawil, Best, Gill, & Fedorov, 2011;Sime, 1995), theories of crowd psychology have only been minimally incorporated into mathematical modelling and computer simulations, and from a psychological point of view, these are out-dated (Templeton, Drury, & Philippides, 2015). A more promising direction of research are proxemics (Baum & Paulus, 1987;Hall, 1966), which describe the social distances individuals keep from one another and has been used for the study of crowd behaviour (Costa, 2010;von Sivers & Köster, 2015;Zanlungo, Ikeda, & Kanda, 2014).…”

“…A more promising direction of research are proxemics (Baum & Paulus, 1987;Hall, 1966), which describe the social distances individuals keep from one another and has been used for the study of crowd behaviour (Costa, 2010;von Sivers & Köster, 2015;Zanlungo, Ikeda, & Kanda, 2014). Although there have been some attempts to introduce small groups within the larger crowd behaviour to simulation models such as families, friends or other predefined groups (Köster, Seitz, Treml, Hartmann, & Klein, 2011;Moussaïd, Perozo, Garnier, Helbing, & Theraulaz, 2010;Singh et al, 2009;Yang, Zhao, Li, & Fang, 2005), these models do not consider the social structure or dynamic of the whole crowd (for a comprehensive review, see (Templeton et al, 2015)). For example, concepts such as "contagion" between individuals are still referred to in recent literature (e.g., Fridman & Kaminka, 2007;Helbing, Farkas, Molnár, & Vicsek, 2002).…”

Towards Detecting the Crowd Involved in Social Events

“…von Krüchten and Schadschneider [7] performed an empirical study on investigating the impact of social groups on evacuations. However, a computational way to model certain psychological features of a crowd from a large-scale (e.g., national level) still lacks [8], which is also crucial for better understanding the way people live, work and play in cities-human activity patterns.…”