University of North Carolina, Chapel Hill


Real World Data Real World Data

We present a practical approach for interactive crowd simulation based on elliptical agents. Our formulation uses a biomechanically accurate pedestrian representation to simulate different local interactions, including backpedaling, side-stepping, and shoulder-twisting. We present an efficient algorithm for local navigation and collision avoidance among multiple elliptical agents using velocity obstacles. Furthermore, we describe techniques to link the orientation of each ellip- tical agent to its velocity to automatically generate turning and lateral movements. In practice, our approach can simulate dense crowds of hundreds of pedestrians at interactive rates on a single CPU core. We highlight the performance in complex scenarios and validate our simulation results by comparing with real-world crowd videos and experiments.



Narang, S., Best, A., & Manocha, D. (2017). Interactive simulation of local interactions in dense crowds using elliptical agents. Journal of Statistical Mechanics: Theory and Experiment, Volume 3, 2017.

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Best, A., Narang, S., & Manocha, D. (2016). Real-time Reciprocal Collision Avoidance with Elliptical Agents. In IEEE International Conference on Robotics and Automation (ICRA) pp. 298-305. IEEE, 2016.

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GAMMA Research Group
UNC Dept. of Computer Science