Implementing real-time grouping for fast egress in emergency

Mass events such as the Olympic games or popular entertainment gathering often attract hundreds of thousands of people. If an abrupt event (e.g., fire, bomb threat) prompts people to rush to exits, stampedes may occur, creating secondary damages. Thus quickly dispersing crowd population to safe places in the least time while managing to avoid congestion and/or stampede is an important task with the occurrence of such events. This study presents an optimal evacuation model to meet this goal. By identifying some key themes that contribute to crowd disasters, the model implements a real-time concurrent grouping to ensure at-risk people are guided to safe places in the least time. The underlying rationale of the strategy is to advocate that competition should be replaced with coherence, and people should coordinate and collaborate to move out in an orderly way through scientifically using multiple routes. In doing so, each person receives an equal opportunity to exit the incident site, and the general effectiveness of performing an evacuation is achieved to an optimal level.To verify the proposed method, we conduct a simulation in which we compare our method with two benchmark cases: random self-evacuation and herding behavior. The results demonstrate that the proposed strategy can rescue people at risk much faster and more safely than two benchmark cases. We implement the proposed model through a web-based wireless decision support system, which provides a useful tool to both first responders and people affected for time-based crowd management in response to an ongoing crowd incident.

► Propose a real-time grouping theorem to disperse an assembly in the least time.
► The proposed method ensures a minimum possibility of crowd crush.
► Use formal mathematics to demonstrate the effectiveness of the method.
► Better performance compared to random self-evacuation and herding behavior.
► Provide a useful tool to both first responders and evacuees.