TY - GEN
T1 - Using agent-based simulation of human behavior to reduce evacuation time
AU - Rahman, Arief
AU - Mahmood, Ahmad Kamil
AU - Schneider, Etienne
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
KW - Ant colony optimization
KW - Cognitive behavior
KW - Evacuation planning
KW - Multi-agent simulation
KW - Prometheus methodology
UR - http://www.scopus.com/inward/record.url?scp=58449113033&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-89674-6_40
DO - 10.1007/978-3-540-89674-6_40
M3 - Conference contribution
AN - SCOPUS:58449113033
SN - 3540896732
SN - 9783540896739
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 357
EP - 369
BT - Intelligent Agents and Multi-Agent Systems - 11th Pacific Rim International Conference on Multi-Agents, PRIMA 2008, Proceedings
T2 - 11th Pacific Rim International Conference on Multi-Agents, PRIMA 2008
Y2 - 15 December 2008 through 16 December 2008
ER -