Crowd simulation

[1] It is commonly used to create virtual scenes for visual media like films and video games, and is also used in crisis training,[2] architecture and urban planning,[3] and evacuation simulation.

Evidently many new findings are continually made and published following these which enhance the scalability, flexibility, applicability, and realism of simulations: In 1987, behavioral animation was introduced and developed by Craig Reynolds.

The theorization and study set forth by Reynolds was improved and built upon in 1994 by Xiaoyuan Tu, Demetri Terzopoulos and Radek Grzeszczuk.

[13] The realistic quality of simulation was engaged with as the individual agents were equipped with synthetic vision and a general view of the environment within which they resided, allowing for a perceptual awareness within their dynamic habitats.

Initial research in the field of crowd simulation began in 1997 with Daniel Thalmann's supervision of Soraia Raupp Musse's PhD thesis.

Building off of the advanced work of Reynolds, Musse and Thalmann began to study the modeling of real time simulations of these crowds, and their applications to human behavior.

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.

For example, researching social questions such as how ideologies are spread amongst a population will result in a much longer running simulation since such an event can span up to months or years.

Generally, this means each agent is assigned some set of variables that measure various traits or statuses such as stress, personality, or different goals.

Gaining insight into natural human behavior under varying types of stressful situations will allow better models to be created which can be used to develop crowd controlling strategies, often in public safety planning.

Emergency response teams such as policemen, the National Guard, military and even volunteers must undergo some type of crowd control training.

Military programs are looking more towards simulated training involving emergency responses due to their cost-effective technology, as well as how effective the learning can be transferred to the real world.

Modeling techniques of crowds vary from holistic or network approaches to understanding individualistic or behavioral aspects of each agent.

Although this is a good model, there are always different types of people present in the crowd and they each have their own individual characteristics as well as how they act in a group structure.

When evaluating the speed of the agent, it is clear that if the value of the dependence factor, DE, is equal to one, then the person would be fully disabled making him unable to move.

[citation needed] In learning AI, virtual characters behave in ways that have been tested to help them achieve their goals.

[citation needed] If this approach is used, along with a large number of possible behaviors and a complex environment agents will act in a realistic and unpredictable fashion.

[37] Variations in appearance, body shape and size, accessories and behavior (social or cultural) exist in real crowds, and lack of variety affects the realism of visual simulations.

[6] Crowd simulations have been used widely across films as a cost-effective and realistic alternative from hiring actors and capturing shots that would otherwise be unrealistic.

One of the most glaring problems for the production team in the initial stages were large-scale battles, as the author of the novels, J. R. R. Tolkien, envisioned them to have at least 50,000 participants.

The Human Logic Engine based Maya plugin for crowd simulation, Miarmy, was used for the development of these sequences.

Based on sight, hearing, and touch parameters generated from the simulation, agents would react uniquely to each situation.

Whereas the traditional method of urban planning relies on maps and abstract sketches, a digital simulation is more capable of conveying both form and intent of design from architect to pedestrian.

For example, street signs and traffic lights are localized visual cues that influence pedestrians to move and behave accordingly.

In a broader sense, bus systems and roadside restaurants serve a spatial purpose in their locations through an understanding of human movement patterns.

Simulated realistic crowds can be used in training for riots handling, architecture, safety science (evacuation planning).

Crowd modeling is essential in police and military simulation in order to train officers and soldiers to deal with mass gatherings of people.

Not only do offensive combatants prove to be difficult for these individuals to handle, but noncombatant crowds play significant roles in making these aggressive situations more out of control.

The social behaviors of people within these constructs have been of interest for many years, and the sociological concepts which underpin these interactions are constantly studied.

The simulation of crowds in different situations allows for sociological study of real life gatherings in a variety of arrangements and locations.