Title:
An architecture model of the U.S. air transportation network
An architecture model of the U.S. air transportation network
Author(s)
Song, Kisun
Advisor(s)
Mavris, Dimitri N.
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Abstract
For almost a century, the U.S. Air Transportation Network (ATN) has continuously and successfully adapted to its changing environment as if it were a living organism. Today, the complexity of the network encompasses various exogenous as well as endogenous factors: fuel price, socioeconomic and political climates, atmospheric conditions, varying interests of stakeholders, and growing dependence on technology, to name a few. Its sophisticated interactions among diverse factors affecting the ATN have captivated many network researchers. Some researchers have attempted to retrieve an order out of seemingly chaotic constructions, while others have analyzed historical variations in its properties to understand the ATN’s behavioral mechanisms.
However, its mathematical representation led by the known components and rules is yet to be developed. Thus, this thesis develops an architecture model of the ATN that mathematically represents the components and rules with realism. In the model, the network evolves in a virtual environment comprising three time-variant components – demand, airport, and aircraft technology – built upon extensive realistic datasets. Then the network is constructed by the active agents – airlines – performing multi-tiered network evolutionary processes and evolves into a strong hub-and-spoke (H&S) structure network that mimics the function of its reference: real-world ATN. The validated model provides various opportunities to conduct extensive analyses and studies on the past, current, and future of the ATN.
Finally, a case study has been performed: forecasting the future ATN disruption caused by the technological revolution of civil supersonic transports. It provided an opportunity to experience the exploratory and interpretative capability of the architecture model, which shed light on performing future researches with better realism.
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Date Issued
2019-11-26
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Text
Resource Subtype
Dissertation