Crowd evacuation simulation approach based on navigation knowledge and two-layer control mechanism.

This paper presents a crowd evacuation simulation approach that is based on navigation knowledge and two-layer control mechanism. In this approach, using the multi-population cultural algorithm framework, the control mechanism of the crowd evacuation simulation is divided into two parts, namely, the belief and population spaces. The population space is divided into groups (sub-populations), and a leader is selected in each group according to a fitness value. The belief space comprises multiple agents and a knowledge base. Each navigation agent corresponds to a group leader. A navigation agent obtains a leader's position through the acceptance function and later passes the information to the knowledge base. On the basis of the position, the obstacles, and the congestion situation provided by the navigation agent, the knowledge base management agent dynamically plans the path and provides the navigation agent the next position along the path. The navigation agent later passes the information to the leader through the affection function. The individuals in the group follow the leader through the social force model in moving to the location provided by the navigation agent. The entire process is repeated until the exit is reached. The path information that successfully reached the exit is recorded, and the knowledge base is updated. This method establishes the relationship between the population and the navigation agent with knowledge and transforms a blindly moving crowd into a guided evacuation as the mass evacuation simulation problem is decomposed into a sub-problem of moving blocks. This approach effectively solves the problem of microscopic models because each individual calculates the path and resolves the slow speed problem. The simulation results illustrate the effectiveness of this method. [ABSTRACT FROM AUTHOR]