Crowd simulation is the process of simulating the movement (or dynamics) of a large number of entities or characters. It is commonly used to create virtual scenes for visual media like films and video games, and is also used in crisis training, architecture and urban planning, and evacuation simulation.

In games and applications intended to replicate real-life human crowd movement, like in evacuation simulations, simulated agents may need to navigate towards a goal, avoid collisions, and exhibit other human-like behavior. Many crowd steering algorithms have been developed to lead simulated crowds to their goals realistically. Some more general systems are researched that can support different kinds of agents (like cars and pedestrians), different levels of abstraction (like individual and continuum), agents interacting with smart objects, and more complex physical and social dynamics.

There has always been a deep-seated interest in the understanding and gaining control of motional and behavior of crowds of people. Much major advancement has taken place since the beginnings of research within the realm of crowd simulation. Evidently many new findings are continually made and published following these which improve the scalability, flexibility, applicability, and realism of simulations.

Correlating and building off of the findings proposed in his work with Musse, Thalmann, working alongside Bratislava Ulicny and Pablo de Heras Ciechomski, proposed a new model which allowed for interactive authoring of agents at the level of an individual, a group of agents and the entirety of a crowd. A brush metaphor is introduced to distribute, model and control crowd members in real-time with immediate feedback.

Flow-based Approach

Flow based crowd simulations focus on the crowd as a whole rather than its components. As such individuals do not have any distinctive behaviors that occur due to input from their surroundings and behavioral factors are largely reduced.

Entity-based Approach

Models that implement a set of physical, predefined, and global laws meant to simulate social/psychological factors that occur in individuals that are a part of a crowd fall under this category. Entities in this case do not have the capacity to, in a sense, think for themselves. All movements are determined by the global laws being enforced on them.

Agent-based Approach

Characterized by autonomous, interacting individuals. Each agent of a crowd in this approach is given a degree of intelligence; they can react to each situation on their own based on a set of decision rules. Information used to decide on an action is obtained locally from the agent's surroundings.

Regards
Sarah Rose
Managing Editor
International Journal of Swarm Intelligence and Evolutionary Computation