Scalability and Evolutionary Dynamics of Air Transportation Networks in the United States
Author(s)
Bonnefoy, Philippe; Hansman, R. John
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With the growing demand for air transportation and the limited ability to increase capacity at key points in the air transportation system, there are concerns that, in the future, the system will not scale to meet demand. This situation will result in the generation and the propagation of delays throughout the system, impacting passengers’ quality of travel and more broadly the economy. There is therefore the need to investigate the mechanisms by
which the air transportation system scaled to meet demand in the past and will do so in the
future. In order to investigate limits to scale of current air transportation networks, theories of scale free and scalable networks were used. It was found that the U.S. air transportation network is not scalable at the airport level due to capacity constraints. However, the results of a case study analysis of multi-airport systems that led to the aggregation of these multiple airports into single nodes and the analysis of this network showed that the air transportation network was scalable at the regional level. In order to understand how the network evolves,
an analysis of the scaling dynamics that influence the structure of the network was
conducted. Initially the air transportation network scales according to airport level
mechanisms –through the addition of capacity and the improvement of efficiency- but as
infrastructure constraints are reached; higher level scaling mechanisms such as the
emergence of secondary airports and the construction of new high capacity airports are
triggered. These findings suggest that, given current and future limitations on the ability to
add capacity at certain airports, regional level scaling mechanisms will be key to
accommodating future needs for air transportation.
Date issued
2007-09-21Citation
7th AIAA Aviation Technology, Integration and Operations Conference (ATIO)
Keywords
Air Transportation, delays, networks, dynamics, scale