Graduate Thesis Or Dissertation


An Agent-based Evacuation Modeling of Underground Fire Emergency Public Deposited

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  • Increasingly congested surface transportation network in urban areas and growingland values make underground transportation systems more attractive for highways(i.e., tunnels) and metro system compared to other options [1]. An undergroundtransportation system can preserve the land above for recreational parks, commercialbuildings, residential homes, or other purposes while providing an efficient, cost-effective underground corridor to move people and goods by separating from the surfacesystem [1]. However, the underground transportation systems present safety andoperational challenges as well if incidents (e.g., fire, flood, terrorist attacks) occur.Major tunnel incidents since 1995 have killed 713 people worldwide [1]. From 1999 to2001, several tunnel fires with multiple deaths occurred in Europe. For example, 39people died in the fire in the Mont Blanc Tunnel between France and Italy in March1999, 12 people died in the fire in the Tauern Tunnel in Austria in May 1999, and11 people died in the fire in the Gotthard Tunnel in Switzerland in October 2001 inwhich the temperature reached 1,000 degrees Celsius (°C) (1,832 degrees Fahrenheit(°F)) within a few minutes [1]. These incidents caused significant safety concernsregarding underground transportation system safety. This problem is complex formultiple reasons: (1) how people will react in tunnel emergencies is unpredictable, (2) fixed entrances and exits, (3) evacuation is likely to be self-initiated, (4) high-densitypresence of pedestrians, and (5) difficult to access for first responders and emergencyvehicles.The objective of this thesis is to present an interdisciplinary agent-based evacuationmodeling framework for emergencies in underground transportation systems.Through this established framework, we will identify and validate the critical factorswhich a effect life safety in underground emergency scenarios. The identification of thecritical factors is validated by empirical data from historic underground tunnel accidents.The evacuation model is built through an agent-based platform: Anylogic.Then, a multi-discipline framework is introduced to analyse and identify problemsrelated to evacuation in underground transportation systems. Finally, we study indetail and simulate the effects of ticket gate type, walking speed, gender, group size,pedestrian's density, and smoke on evacuation time. The research results from thisthesis will provide decision-making support and guidance for government decision-makers, design engineers, and agency professionals to optimize underground stationdesign. The experiment results indicate that the proposed agent-based undergroundtransportation emergency evacuation modeling framework in this thesis is effective atevaluating the impacts of the identified critical factors on evacuation efficiency andlife safety.
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