Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty

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Title: Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty
Author(s): Sidiropoulos, S
Han, K
Majumdar, A
Ochieng, W
Item Type: Journal Article
Abstract: Multi-Airport Systems (MAS), or Metroplexes, serve air traffic demand in cities with two or more airports. Due to the spatial proximity and operational interdependency of the airports, Metroplex airspaces are characterized by high complexity, and current system structures fail to provide satisfactory utilization of the available airspace resources. In order to support system-level design and management towards increased operational efficiency in such systems, an accurate depiction of major demand patterns is a prerequisite. This paper proposes a framework for the robust identification of significant air traffic flow patterns in Metroplex systems, which is aligned with the dynamic route service policy for the effective management of Metroplex operations. We first characterize deterministic demand through a spatio-temporal clustering algorithm that takes into account changes in the traffic flows over the planning horizon. Then, in order to handle uncertainties in the demand, a Distributionally Robust Optimization (DRO) approach is proposed, which takes into account demand variations and prediction errors in a robust way to ensure the reliability of the demand identification. The DRO-based approach is applied on pre-tactical (i.e. one-day planning) as well as operational levels (i.e. 2-h rolling horizon). The framework is applied to Time Based Flow Management (TBFM) data from the New York Metroplex. The framework and results are validated by Subject Matter Experts (SMEs).
Publication Date: 30-Dec-2016
Date of Acceptance: 18-Dec-2016
URI: http://hdl.handle.net/10044/1/43272
DOI: https://dx.doi.org/10.1016/j.trc.2016.12.011
ISSN: 0968-090X
Publisher: Elsevier
Start Page: 212
End Page: 227
Journal / Book Title: Transportation Research Part C - Emerging Technologies
Volume: 75
Copyright Statement: © 2016 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Copyright Statement: © 2016 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords: Science & Technology
Technology
Transportation Science & Technology
Transportation
Multi-airport system
Terminal area operation
Air traffic demand
Air traffic management
Distributionally robust optimization
Multi-airport system
terminal area operation
air traffic demand
air traffic management
distributionally robust optimization
Logistics & Transportation
09 Engineering
08 Information And Computing Sciences
15 Commerce, Management, Tourism And Services
Publication Status: Published
Article Number: TRC1684
Appears in Collections:Faculty of Engineering
Civil and Environmental Engineering



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