A Hybrid Pedestrian Motion Modeling Approach for Crowd Simulation

Crowd simulation are widely studied in computer graphics, games, public safety and emergency treatment fields, playing an important role in simulating crowd movement behavior and guiding crowd evacuation. The existing agent-based crowd simulation approaches usually require large amount of calculation, and the real-time performance is poor. Crowd simulation based on cellular automaton (CA) model need less calculation relatively and has good real-time performance, but each individual is not autonomous, they cannot make decisions by themselves. In view of the above problems, this manuscript presents a hybrid pedestrian motion modeling approach called HACA, which is the hybrid of agent and CA model and integrates the advantages of the two modeling approaches. Through experimental validation, HACA can effectively simulate the real crowd behavior and achieve about 12% performance improvement compared with CA model in terms of simulation running time. Besides, each pedestrian is modeled as an agent and they can make decisions according to their own state and surrounding environment.