Provide New Discomfort Indices at Fire Time Using Results of Agent-Based Geosimulation (Case Study: Hafte-Tir Subway Station)

Abstract:
Commensurate with the complexity of human behavior, social systems are complicated. Population management in these systems are crucial and need to spend too much cost. Because of the interaction between humans and the environment and then the impact of these interactions on social systems in the process of population movements, there is a need to identify and study these interactions, especially in emergency situations.
In this study, the results of agent based geosimulation of pedestrian movements and fire simulation at Hafte-Tir subway station were used to investigate the behavior of individuals and the environment during fire. Then, the discomfort indices, including environmental and human-environmental indicators, were calculated to examine the effect of the environment and agents on the movement process. This research has introduced two new discomfort indices i.e. environmental index AM1 and environmental-humanity index AM2 to evaluate the behavior of individuals and the environment during the fire. The innovation of these indices relates to the integration of the results of the agent based simulation and the fire simulation in the environment and after that using of visibility, in addition to the interactions of individuals with each other and their interactions with the physical components of the environment. Calculating results of indices and the results of people movement’s simulation in the station represented an inverse relationship between the level of discomfort and speed of crowd in the station. Also, the discomfort induces in the successful environmental scenario shows a reduction in the discomfort in hot spots rather than current situation scenario. The use of agent based geosimulations and the result of discomfort indices in different periods of crisis, can contribute population management strategies and emergency evacuation.
Language:
Persian
Published:
Iranian Journal of Remote Sencing & GIS, Volume:9 Issue: 1, 2017
Pages:
17 to 36
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