Fast Simulation of Crowd Collision Avoidance

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Abstract

Real-time large-scale crowd simulations with realistic behavior, are important for many application areas. On CPUs, the ORCA pedestrian steering model is often used for agent-based pedestrian simulations. This paper introduces a technique for running the ORCA pedestrian steering model on the GPU. Performance improvements of up to 30 times greater than a multi-core CPU model are demonstrated. This improvement is achieved through a specialized linear program solver on the GPU and spatial partitioning of information sharing. This allows over 100,000 people to be simulated in real time (60 frames per second).

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Charlton, J., Gonzalez, L. R. M., Maddock, S., & Richmond, P. (2019). Fast Simulation of Crowd Collision Avoidance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11542 LNCS, pp. 266–277). Springer Verlag. https://doi.org/10.1007/978-3-030-22514-8_22

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