Abstract. Simulation of building evacuations can be a powerful tool for predicting evacuation outcomes, but for this prediction to be useful it must be produced in a timely manner. The building evacuation outcomes are dependent on the movement decisions of the occupants, but simulating all possible combinations of occupant decisions is infeasible. Our contribution is a novel technique using building structure knowledge in the form of a Network Flow Graph to determine where and when occupants might interact with one another. We decompose the problem into non-interacting groups, to be simulated separately, which leads to a significant simulation workload reduction.Keywords: evacuation monitoring, multi-agent simulation, distributed simulation, network flow graph, problem decomposition
IntroductionSimulation of building evacuation during emergencies is a powerful tool for evaluating building safety and prediction of evacuation outcomes [1]. Simulating the movement of evacuating pedestrians can provide useful information to building designers and to fire safety officials, including evacuation time estimates and locations at risk of traffic congestion or evacuee injury [1][2][3][4][5][6][7]. We make use of a 2D vector-space pedestrian simulator to simulate the individual movements of pedestrians in the building. This simulator provides a realistic model of pedestrian movement but is computationally intensive compared to simpler models such as Cellular Automata [2,4,10] or Graph-based simulations [5]. The usefulness of any prediction information is contingent on both the timeliness and the accuracy of the simulation that generated it. Since a real evacuation involves autonomous human actors and uncertain hazard spread, to ensure that the simulations cover likely scenarios we must run many different scenarios. The more we can reduce the simulation time, the more scenarios we can consider, and the more useful the results will be. In this paper, we investigate the problem of how to cover a wide range of scenarios without an excessive increase in computation time.We assume that clusters of individuals in an evacuation will behave as a group, and once they have formed a group all members will follow the same route out of the building. We reduce the amount of simulation by limiting our attention to the most likely routes for each initial group. However, different groups may meet during the evacuation and cause congestion, and may form into larger groups to continue the evacuation. Since congestion slows down the evacuation, and puts the participants at risk, we must investigate the interaction of the different groups. Even for small numbers of likely routes, this group interaction quickly produces an excessively large simulation space. We reduce the complexity of the problem by quickly generating possible group interactions using Network-Flow Graph analysis, identifying groups and routes which do not interact, distributing the simulation of those local scenarios to different processors, and then combining the results to pro...