Templeton Anne, Drury John, Philippides Andrew
School of Psychology, University of Sussex.
Department of Informatics, Centre for Computational Neuroscience and Robotics, University of Sussex.
Rev Gen Psychol. 2015 Sep;19(3):215-229. doi: 10.1037/gpr0000032. Epub 2015 Aug 17.
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 ( = 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.
计算机模拟越来越多地用于监测和预测大型人群活动中的行为,如群众集会、节日活动和疏散情况。我们审慎地审视了人群建模文献,并呼吁未来的人群行为模拟要更紧密地基于当前社会心理学研究的结果。我们对人群建模文献(共140篇文章)进行了系统综述,以确定建模者在模拟中使用的关于人群行为的假设。文章根据人群结构建模的方式进行编码。结果发现,使用了两种主要类型:整体方法和小群体方法。然而,无论是整体方法还是小群体方法,都无法准确模拟在关于人群活动的大量实证研究中发现的大型集体行为。我们认为,要逼真地模拟人群行为,模拟必须采用自我分类理论所建议的方法,使人群成员能够相互认同。