Simulating human collision avoidance using a velocity-based approach

We present a velocity-based model for realistic collision avoidance among virtual characters. Our approach is elaborated from existing experimental data and is based on the simple hypothesis that an individual tries to resolve collisions long in advance by slightly adapting its motion. We have evaluated our model by testing it against a wide range of challenging scenarios. In all of our simulations, the characters exhibit smooth and visually convincing motions, avoiding all collisions with minimal effort. The method reproduces emergent behaviour, like lane formation, that have been observed in real crowds. It is relatively easy to implement and and is fast, allowing the simulation of crowds of thousands of characters in real time.