人群仿真目前在工业、建筑、交通等多种领域中应用广泛。实现复杂场景中的人群运动实时仿真,效率是亟待解决的关键性问题,而提高仿真效率所必须面临的挑战主要有人群的渲染、位置及状态的实时更新和碰撞检测。提出一种基于场的方法来实现人群运动的实时仿真,通过构建导航场和密度场引导人群运动。导航场能够引导人群按最优可行路径到达其目标位置;而密度场通过对人群运动速度的影响,再与基于GPU的碰撞检测方法结合,有效地避免了人群碰撞。应用基于场的方法,搭建了人群运动实时仿真系统,在复杂的场馆中对几千人规模的人群进行了实验,成功地对人群进行疏散。实验结果表明,本文方法能够获得良好的渲染效果和仿真效率。

Crowd simulation has been widely used in industry, architecture, transportation, and many other fields. To implement real-time crowd simulation in complex environments, efficiency is a pivotal problem to resolve. We meet a lot of challenges, such as rendering of large crowds, the update of crowd’s locations and states, as well as collision avoidance. We propose a field-based approach to implement real-time crowd simulation. This approach guides the crowd movements by constructing a navigation field and a density field. The navigation field can make the crowd choose the optimal path to reach the desired destinations. The density field can affect the velocity of the crowd to help avoid collisions, combined with a GPU-based collision avoidance method. Using our approach, we have constructed a real-time crowd simulation system and tested the performance in a large venue with thousands of agents. We succeed in simulating the evacuation of crowds with excellent rendering and high efficiency.