Intuitive crowd behavior in dense urban environments using local laws

Abstract

In games, entertainment, medical and architectural applications, the creation of populated virtual city environments has recently become widespread. In this paper we want to provide a technique that allows the simulation of up to 10,000 pedestrians walking in real-time. Simulation for such environments is difficult as a trade off needs to be found between realism and real-time simulation. This paper presents a pedestrian crowd simulation method aiming at improving the local and global reactions of the pedestrians. The method uses a subdivision of space into a 2D (two-dimensional) grid for pedestrian-to-pedestrian collision avoidance, while assigning goals to pedestrians to make their trajectories smoother and coherent. Goals are computed automatically and connected into a graph that reflects the structure of the city and triggers a spatial repartition of the density of pedestrians. In order to create realistic reactions when areas become crowded, local directions are stored and updated in real-time, allowing the apparition of pedestrian streams. Combining the different methods contributes to a more realistic model, while keeping a real-time frame rate for up to 10,000 simulated pedestrians.