In this paper, we integrate a cellular automaton model with game theory to simulate crowd evacuation from a room with consideration of obstacle removal. The room has one or more exits, one of which is blocked by obstacles. The obstacles at the exit can be removed by volunteers. We investigate the cooperative and defective behaviors of pedestrians during evacuation. The yielder game and volunteer's dilemma game are employed to resolve interpedestrian conflict. An anticipation floor field is proposed to guide the pedestrians to avoid obstacles that are being removed. We conducted experiments to determine how a variety of conditions affect overall crowd evacuation and volunteer evacuation times. The conditions were the start time of obstacle removal, number of obstacles, placement of obstacles, time spent in obstacle removal, strength of the anticipation floor field, and obstacle visibility distance. We demonstrate how reciprocity can be achieved among pedestrians and increases the efficiency of the entire evacuation process.

Navigation fields are a popular data structure for directing the movement of virtual crowds. However, the congestion problem may occur at the corners of objects in using a navigation field because the agents move quite closely to each other. The agents may congest at the corners even though there is room for the agents to move away from the congested regions. In this paper, we propose to place crowd monitors at the corners to collect the data such as the movement direction of crowds and crowd densities. Then the navigation field is adjusted dynamically so that the crowds are led to move away from the congested regions. We also propose a simple data structure for speeding up the collision detection process between agents and objects.Experimental results show that our approach successfully alleviates the congestion problem at the corners.

No abstract

No abstract

No abstract