视觉信息在行人群体仿真中的应用

传统群体仿真技术常把群体看成若干个体的组合,但事实上群体是由若干具有相似行为的个体组成的群组所构成的.针对大多数现有群体仿真技术由于没有考虑到上述因素,导致仿真结果和真实生活中的群体行为存在一定差异的问题,并结合群体是由不同小群组构成的特点,提出一种基于视觉信息指导并考虑行人动态寻路和局部碰撞避免的方法.仿真结果显示,该方法在仿真群体时能够获得较为自然的自组织现象,与现有的几种方法相比,这种现象在复杂环境或者高密度情况下会更加明显.

Visually-Guided Pedestrian Crowd Simulation

Traditional studies on crowd simulation usually regard crowds as the combinations of individuals,but in fact,crowds consist of different small groups of individuals with similar behaviors.Most of the traditional crowd simulation methods ignored this property,and thus,produced unreal results.To overcome this problem,after considering the fact that a crowd consists of different small groups,this paper proposed a novel visually-guided approach containing both collision avoidance and dynamic navigation for simulating crowds.The simulation results show natural-looking self-organized phenomena which are more obvious and appealing in high density or complex situations compared with existing classical models.