Shepherding Behaviors with Single Shepherd in Crowd Management

Crowd management is to systematically plan and supervise the orderly movement and assembly of a crowd. Shepherding behaviors are a class of flocking behaviors in which one or more external agents (called shepherds ) try to control the motion of another group of agents (called a flock ), it has a leading application in influencing the behavior and activities of a potentially hostile crowd and bringing a mob engaged in a riot under control. In this paper, we focus on investigating shepherding behaviors with single shepherd in normal situation. In our approach, we use a global dynamic planning algorithm which is the multi-agent planning algorithm in dynamic environment to update the next region occasionally where the flock will be steered to. Also, in order to cope with unexpected events in emergency situation, we combine shepherding behaviors with behavior selection mechanisms which are implemented in rules. The simulation results show that our approach which is validated in an urban circumstance is effective and feasible.