Explicit Modeling of Personal Space for Improved Local Dynamics in Simulated Crowds

Abstract

Crowd simulation demands careful consideration in regard to the classic trade-off between accuracy and efficiency. Particle-based methods have seen success in various applications in architecture, military, urban planning, and entertainment. This method focuses on local dynamics of individuals in large crowds, with a focus on serious games and entertainment. The technique uses an area-based penalty force that captures the infringement of each entity's personal space. This method does not need a costly nearest-neighbor search and allows for an inherently data-parallel implementation capable of simulating thousands of entities at interactive frame rates. The algorithm reproduces personal space compression around motion barriers for moving crowds and around points of interest for static crowds.

Predictive Agent-Based Crowd Model Design Using Decentralized Control Systems

“…This feature leverages the JADE scaling ability by distributing the workload across multiple networked hosts, e.g., for computationally intensive simulations of larger, multistory buildings. We compared our results with [62] (p. 23, Table I, Columns 1 and 2), using the same type of GPU, Nvidia GeForce GTX 1060. We obtained on average 120.7 fps compared to 125 fps in [62], for a) 254 agents in our model (including pedestrians with deliberative-reactive architecture, static agents, and the two controller agents); and b) 250 particle-based pedestrian agents in [62].…”

“…We compared our results with [62] (p. 23, Table I, Columns 1 and 2), using the same type of GPU, Nvidia GeForce GTX 1060. We obtained on average 120.7 fps compared to 125 fps in [62], for a) 254 agents in our model (including pedestrians with deliberative-reactive architecture, static agents, and the two controller agents); and b) 250 particle-based pedestrian agents in [62]. In our case, as opposed to [62], the model also includes the building itself (walls and rooms), rendering for fire and sprinklers, control and collision logic, smoke computation with discrete differential equations, and the interaction between pedestrians and smoke.…”