Multi-Agent Simulation for Crisis Management
KMN '02 Proceedings of the IEEE Workshop on Knowledge Media Networking
Developing Intelligent Agent Systems: A Practical Guide
Developing Intelligent Agent Systems: A Practical Guide
Modeling Crowd and Trained Leader Behavior during Building Evacuation
IEEE Computer Graphics and Applications
Cognition, Technology and Work
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Computational Intelligence and Neuroscience
| Hi-index | 0.00 |
Human factors play a significant part in the time taken to evacuate due to an emergency. An agent-based simulation, using the Prometheus methodology (SEEP 1.5), has been developed to study the complex behavior of human (the `agents') in high-rise building evacuations. In the case of hostel evacuations, simulation results show that pre-evacuation phase takes 60.4% of Total Evacuation Time (TET). The movement phase (including queuing time) only takes 39.6% of TET. From sensitivity analysis, it can be shown that a reduction in TET by 41.2% can be achieved by improving the recognition phase. Emergency exit signs have been used as smart agents. Modified Ant Colony Optimization (ACO) was used to determine the feasibility of the evacuation routes. Both wayfinding methods, the `familiarity of environment', which is the most natural method, and the ACO method have been simulated and comparisons were made. In scenario 1, where there were no obstacles, both methods achieved the same TET. However, in scenario 2, where an obstacle was present, the TET for the ACO wayfinding method was 21.6% shorter than the one for the `familiarity' wayfinding method.