Density Distribution and local behaviour for realistic crowd simulation

Virtual crowds are rapidly becoming a standard feature of large scale virtual environments. The incorporation of a virtual population enhances the realism of these environments. Effective algorithms have been formulated to govern the movement of individual avatars to give the crowds some semblance of intelligence, but often cover only one part of the simulation: collision detection, navigation or local interaction. In this paper we introduce a system that combines all three aspects. The navigation follows density principles suggested by the space syntax methods (9). Our navigation system can also be tuned to simulate evacuations. The simulation is non deterministic in the sense that agents do not follow the same path, but the overall simulated density distribution is consistent. Also, local behaviour is simulated in the form of points of attraction and small-group (pair) formation which provides more a realistic visualization. Our system runs in real time allowing interactive visualization. Virtual Environments have recently become a very popular field, as they are used for various applications, such as architecture, medicine and entertainment. The need to populate these environments with virtual humans, who successfully replicate human behaviour, is a key problem that needs to be solved. However, it is a very difficult one where different steps need to be followed such as authoring, high-level behaviour and low-level behaviour simulation. Most approaches chose one of two types: the simulation of an exact replica of a measured reality or a locally realistic simulation that gives an idea of the environment if it were populated. Often the first type requires expensive simulation, in term of memory and CPU usage, building on artificial intelligence and path planning methods, while the second type offers an interactive simulation of a large number of agents but valid only for a visual interest. In this paper we are interested in reducing the gap between the two different approaches. We use a simple real-time approach to modelling large crowds, using models to represent both indoor and outdoor environments. Building on an existing system with a simple collision detection and avoidance, we extend the crowd behaviour further by contributing with different methods of group behaviour, attractors, and evacuation, as well as by proposing authoring via 2D information stored in images, callbacks, and attraction points. As a result our simulation runs in real time for large crowds of more than a thousand individuals visiting or evacuating an environment, interacting with local features (such as pedestrian crossings or sites of interest), and walking in pairs. We illustrate our method with a simulation in a museum of visitors attracted by museum items. We show that the applied rules lead to density matching space syntax measures (9). The same method can be applied to simulate evacuation with flow of people reaching the exits of the museum. In a second simulation we show a city simulation with people walking in pairs and stopping at a pedestrian crossing. The simulation runs in real time for up to several thousands of individuals. An illustration of the system is shown in Figure 1.