by Avneesh Sud, Russell Gayle, Stephen Guy, Erik Andersen, Ming Lin, and Dinesh Manocha.

Paper1, Paper2
Video

We present a real-time algorithm for simulating heterogeneous crowds with potentially distinct individual behavior characteristics and goals. Our approach combines global motion planning with a generalized pedestrian dynamics model to synthesize motion for numerous groups of people in complex dynamic environments. Inspired by self-organization phenomena in crowds, we introduce "Pedestrian Levels of Detail" to accelerate large-scale simulation of individual agents, while preserving natural collective behaviors observed in real crowds. We highlight the performance of our algorithm on heterogeneous crowds in highly populated urban scenes.

Publication