A confluence of technologies has made the simulation of large-scale pattern of life possible to support real time applications. Ubiquitous cloud computing, new generation application scalability frameworks, advanced crowd modelling software, geospatial data production tools and high fidelity/high performance visualization all contribute to the capability not only to simulate city and country sized populations but also do it in real time to support visual simulation applications.
Our work focuses on simulating population mobility, specifically pedestrian movement, as they go about their daily lives but also with the ability to interject events that would cause visible changes in their behaviour. Our objective is to go beyond simple clutter with performance and fidelity requirements that includes (i) a persistent population size of 100K – 1M+ independent agents and a minimum crowd size of 50K (ii) obeyance of walking areas and avoidance of other moving entities and (iii) a simultaneous visualization of the entire population and a game quality street level visualization of any area in the city. We believe this capability can contribute to any simulation and training application that can benefit from a realistically populated city, especially one that may require human interactivity. Specific examples include emergency evacuation scenarios, large crowd protests and military operations in urban terrain.
This paper begins by reviewing the significant existing work in this field that has inspired our methodology. It then reports on the design, implementation and integration of the various components that allowed us to achieve our overall objectives. Finally, it discusses the lessons learned and also looks to the future in this rapidly advancing field.
Keywords
PATTERN OF LIFE,REAL-TIME,SCALABILITY
Additional Keywords