A survey of dynamic network flows
Annals of Operations Research
Contraflow network reconfiguration for evacuation planning: a summary of results
Proceedings of the 13th annual ACM international workshop on Geographic information systems
Modeling and simulation of multi-agent systems for emergency scenarios
Modeling and simulation of multi-agent systems for emergency scenarios
Emergency response simulation using wireless sensor networks
Proceedings of the 1st international conference on Ambient media and systems
Proceedings of the 10th international conference on Human computer interaction with mobile devices and services
LifeBelt: Silent Directional Guidance for Crowd Evacuation
ISWC '09 Proceedings of the 2009 International Symposium on Wearable Computers
A Fuzzy-Based Approach for Smart Building Evacuation Modeling
ICICIC '09 Proceedings of the 2009 Fourth International Conference on Innovative Computing, Information and Control
Evacuation Simulation Based on Cognitive Decision Making Model in a Socio-Technical System
DS-RT '11 Proceedings of the 2011 IEEE/ACM 15th International Symposium on Distributed Simulation and Real Time Applications
Real-Time Pedestrian Evacuation Planning during Emergency
ICTAI '11 Proceedings of the 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence
Efficient and validated simulation of crowds for an evacuation assistant
Computer Animation and Virtual Worlds
The EvacSim pedestrian evacuation agent model: development and validation
Proceedings of the 2013 Summer Computer Simulation Conference
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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.