Simulation study on evacuation
scenarios has gained tremendous attention in recent years. Two major research
challenges remain along this direction (1) how to portray the effect of
individuals’ adaptive behaviors under various situations in the evacuation
procedures and (2) how to simulate complex evacuation scenarios involving huge
crowds at the individual level due to the ultrahigh complexity of these
scenarios. In this study, a simulation framework for general evacuation
scenarios has been developed. Each individual in the scenario is modeled as an
adaptable and autonomous agent driven by a weight-based decision-making
mechanism. The simulation is intended to characterize the individuals’
adaptable behaviors, the interactions among individuals, among small groups of
individuals, and between the individuals and the environment. To handle the
second challenge, this study adopts GPGPU to sustain massively parallel
modeling and simulation of an evacuation scenario. An efficient scheme has been
proposed to minimize the overhead to access the global system state of the
simulation process maintained by the GPU platform. The simulation results
indicate that the “adaptability” in individual behaviors has a significant
influence on the evacuation procedure. The experimental results also exhibit
the proposed approach’s capability to sustain complex scenarios involving a
huge crowd consisting of tens of thousands of individuals.
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