Figure 1: Our method can generate dynamic group behaviors along with coherent and collision free navigation. We highlight the performance in a street-crossing scenario, where different groups are shown with different colors. Our approach can automatically adapt to the environment and the number, shape, and size of the groups can change dynamically. We present a new algorithm to simulate dynamic group behaviors for interactive multi-agent crowd simulation. Our approach is general and makes no assumption about the environment, shape, or size of the groups. We use the least effort principle to perform coherent group navigation and present efficient inter-group and intragroup maintenance techniques. We extend the reciprocal collision avoidance scheme to perform agent-group and group-group collision avoidance that can generate collision-free as well as coherent and trajectories. The additional overhead of dynamic group simulation is relatively small. We highlight its interactive performance on complex scenarios with hundreds of agents and compare the trajectory behaviors with real-world videos.
REF simulated dynamic group behaviors based on the least e ort principle.
Dynamic Group Behaviors for Interactive Crowd Simulation
ArXiv
ArXiv
Computer Science