Degree

Doctor of Philosophy (PhD)

Department

Civil and Environmental Engineering

Document Type

Dissertation

Abstract

Over the past 40 years, a range of tools and techniques have been employed to assess traffic and travel conditions associated with evacuation events. These tools provide key insights into the temporal-spatial conditions of traffic during an evacuation. The representation of an evacuation in a traffic simulation model requires a number of assumptions about the input and modeling parameters needed to capture relevant aspects of such event. Therefore, a key aspect to ensure appropriate estimations of evacuation clearance times and overall efficacy of emergency planning is to better understand the influence and the importance that simulation modeling parameters have on simulation outputs and on the evacuation process. Based on this idea, various parameters related to traffic demand, network supply, and simulation process were investigated herein. More specifically, this research focused on model settings and input parameters that were thought to be particularly influential on the computation of evacuation time estimates (ETEs) or “clearance times” in different areas having a range of population sizes and network topologies. Overall, the results revealed a number of key facts related to ETEs, evacuations as well as simulation modeling, more broadly. The first and perhaps most important of these was the importance of the physical topology and, most critically, capacity constraints within individual evacuation road networks. Consistent findings emerged suggesting that not only does the overall configuration of a network render it susceptible to the influence of input parameters, but that even more so are the variation, arrangement, and characteristics of individual link capacities within a single specific study area. Although this research was focused on evacuations associated with nuclear power plant (NPP) emergencies, it is assumed that these findings are directly applicable to other emergencies and non-emergency scenarios where unbalanced surges in demand occur.

Date

1-3-2019

Committee Chair

Wolshon, Brian

DOI

10.31390/gradschool_dissertations.4789

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