A Crowd Simulation Using Individual-Knowledge- Merge based Path Construction and Smoothed Particle Hydrodynamics

Abstract

Previous researches on crowd simulation are often based on pre-computed path planning to reduce computational time; however, the pattern of the crowd locomotion is usually unrealistic and the simulation itself is also inflexible. This paper presents a novel technique to model an interactive time crowd simulation by using automatic path construction and Smoothed Particle Hydrodynamics (SPH) in order that each individual can automatically search for the destination without path pre-computation. Two alternating stages approaches are used in our simulation. Firstly, the environment and crowd are set up, and crowd is then moved in accordance with SPH in order to achieve smooth locomotion without fixed pattern. Each agent from a group of crowd can create a map that contains the knowledge of local environment that it gains from perceptions. The local path can be extended and shared corresponding to the new environment or knowledge sharing with other agents. An automatic path determination is done in the next stage by using the potential field. The result from path selection is then used to set the direction of external force in SPH model. By using our method, natural crowd locomotion under a variety of conditions, such as forming and separating lane, obstacles avoidance and escape from unknown area can be represented in interactive time.