Charlton, J. orcid.org/0000-0001-8402-6723, Gonzalez, L.R.M., Maddock, S. orcid.org/0000-0003-3179-0263 et al. (1 more author) (2019) Fast simulation of crowd collision avoidance. In: Gavrilova, M., Chang, J., Thalmann, N.M., Hitzer, E. and Ishikawa, H., (eds.) Advances in Computer Graphics. 36th Computer Graphics International Conference (CGI 2019), 17-20 Jun 2019, Calgary, AB, Canada. Lecture Notes in Computer Science (11542). Springer , pp. 266-277. ISBN 9783030225131
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).
Metadata
Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Springer Nature. This is an author-produced version of a paper subsequently published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Pedestrian simulation; Real-time rendering; GPU-computing |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 27 Aug 2019 09:37 |
Last Modified: | 12 Jun 2020 00:43 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | https://doi.org/10.1007/978-3-030-22514-8_22 |