Preserving the Motion Features in Nonavoiding Collision Crowds

Abstract

In current games, entire cities can be rendered in real time into massive virtual worlds. In addition to the enormous details of geometry, rendering, effects (e.g., particles), sound effects, and so on, nonplayable characters must also be animated and rendered, and they must interact with the environment and among themselves. Indeed, the computation time of all such data is expensive. Consequently, game designers should define priorities so that more resources can be allocated to generate better graphics, setting aside behavioral aspects. In huge environments, some of the actions/behaviors that should be processed can be nonvisible to the players (occluded) or even visible but far away. Normally, in such cases, the common decision is to turn off such processing. However, hidden enemy behaviors that are not processed can result in nonrealistic feedback to the player. In this article, we aim to provide a method to preserve the motion of nonvisible characters while maintaining a compromise with the needed computational time of background behaviors. We apply this idea specifically in crowd collision behavior, proposing nonavoiding collision crowds. Such crowds do not have collision avoidance behaviors but preserve their motion as typical crowds. We propose a mathematical technique to describe how people are affected by others, so collision avoidance methods are not necessarily computed (they can be turned off, which leads to a reduction in the required computational time). Results show that our method replicates the behavior well (velocities, densities, and time) when compared to a free-of-collision method.