2019/01/01 by John P. Charlton, John Charlton, Luis Rene Montana Gonzalez +2 · 6 citations
Computer Science · Engineering · #Collision #Collision avoidance #Computer graphics (images) #Computer science #Evacuation and Crowd Dynamics #Pedestrian #Pedestrian detection #Real-time computing #Scale (ratio) #Simulation #Solver #Traffic Prediction and Management Techniques #Traffic control and management #cs.RO
paper · pdf · doi:10.1007/978-3-030-22514-8_22
published in Lecture notes in computer science, 266-277 (Springer Science+Business Media) · 12 pages, 6 figures, 36th Computer Graphics International Conference (CGI 2019)
openalex publication_date 2019/01/01 · arxiv created 2019/08/27 · arxiv updated 2019/08/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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).