From individual characters to large crowds: augmenting the believability of open-world games through exploring social emotion in pedestrian groups

Crowds of non-player characters improve the game-play experiences of open-world video-games. Grouping is a common phenomenon of crowds and plays an important role in crowd behaviour. Recent crowd simulation research focuses on group modelling in pedestrian crowds and game-designers have argued that the design of non-player characters should capture and exploit the relationship between characters. The concepts of social groups and inter-character relationships are not new in social psychology, and on-going work addresses the social life of emotions and its behavioural consequences on individuals and groups alike. The aim of this paper is to provide an overview of current research in social psychology, and to use the findings as a source of inspiration to design a social network of non-player characters, with application to the problem of group modelling in simulated crowds in computer games

Group emotion modelling and the use of middleware for virtual crowds in video-games

In this paper we discuss the use of crowd simulation in video-games to augment their realism. Using previous works on emotion modelling and virtual crowds we define a game world in an urban context. To achieve that, we explore a biologically inspired human emotion model, investigate the formation of groups in crowds, and examine the use of physics middleware for crowds. Furthermore, we assess the realism and computational performance of the proposed approach. Our system runs at interactive frame-rate and can generate large crowds which demonstrate complex behaviour

Towards agent-based crowd simulation in airports using games technology

We adapt popular video games technology for an agent-based crowd simulation in an airport terminal. To achieve this, we investigate the unique traits of airports and implement a virtual crowd by exploiting a scalable layered intelligence technique in combination with physics middleware and a socialforces approach. Our experiments show that the framework runs at interactive frame-rate and evaluate the scalability with increasing number of agents demonstrating navigation behaviour

Placing large group relations into pedestrian dynamics: psychological crowds in counterflow

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