Fast simulation of crowd collision avoidance

• Main Authors: Charlton, J., Gonzalez, L.R.M., Maddock, S., Richmond, P.
• Other Authors: Gavrilova, M., Chang, J., Thalmann, N.M., Hitzer, E., Ishikawa, H.
• Format: Report
• Language: English
• Published: Springer 2019
• Subjects: Orca
• Online Access: https://eprints.whiterose.ac.uk/150111/; https://eprints.whiterose.ac.uk/150111/1/_John_Charlton____ORCA_GPU_Paper.pdf

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).