Flight trajectory data analytics for characterization of air traffic flows : A comparative analysis of terminal area operations between New York, Hong Kong and Sao Paulo

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)324-347
Journal / PublicationTransportation Research Part C: Emerging Technologies
Volume97
Online published9 Nov 2018
Publication statusPublished - Dec 2018

Abstract

Future Air Traffic Management systems can benefit from innovative approaches that leverage theincreasing availability of operational data to facilitate the development of new performanceassessment and decision-support capabilities. This paper presents a data analytics framework forhigh-fidelity characterization of air traffic flows from large-scale flight tracking data. Machinelearning methods are used to exploit spatiotemporal patterns in aircraft movement towards theidentification of trajectory patterns and traffic flow patterns. The outcomes and potential impactsof this framework are demonstrated with a comparative analysis of terminal area operations inthree representative multi-airport (metroplex) systems of the global air transportation system:New York, Hong Kong and Sao Paulo. As a descriptive tool for systematic analysis of the flowbehavior, the framework allows for cross-metroplex comparisons of terminal airspace design,utilization and traffic performance. Novel quantitative metrics are created to summarize me-troplex efficiency, capacity and predictability. The results reveal several structural, operationaland performance differences between the multi-airport systems analyzed. Our findings show thatNew York presents the most complex airspace design, with considerably higher number of routesand interactions between them, as well as more dynamic changes in the terminal area flowstructure during the day, in part driven by the presence of flow dependencies. Interestingly, itexhibits the best levels of traffic flow efficiency on average, both spatially and temporally, yet thehighest variability in metroplex configuration performance, with more pronounced performancedegradation during inclement weather.

Research Area(s)

  • Air traffic flows, Machine learning, Multi-airport systems, Terminal area, Trajectory data analytics

Citation Format(s)

Flight trajectory data analytics for characterization of air traffic flows : A comparative analysis of terminal area operations between New York, Hong Kong and Sao Paulo. / Murça, Mayara Condé Rocha; Hansman, R. John; Li, Lishuai; Ren, Pan.

In: Transportation Research Part C: Emerging Technologies, Vol. 97, 12.2018, p. 324-347.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review