Data-driven planning for ground delay programs

Alexander Estes, Michael Ball

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

This paper provides a model-based approach to planning ground delay programs. Previous research on automated planning of ground delay programs has involved the use of mathematical programming techniques. This paper proposes a data-driven method that models the problem of choosing a traffic management initiative by using the framework of the multiarmed bandit decision problem. This approach makes greater use of the available data, and suggestions made by this procedure can be shown along with data that informed the decision. This combination of tools allows decision makers to more easily evaluate suggested decisions. The paper also provides simulations of the procedure on the basis of data from Newark (New Jersey) International Airport to evaluate its effectiveness.

Original languageEnglish (US)
Title of host publicationTransportation Research Record
PublisherNational Research Council
Pages13-20
Number of pages8
ISBN (Electronic)9780309441490
DOIs
StatePublished - Mar 1 2017

Publication series

NameTransportation Research Record
Volume2603
ISSN (Print)0361-1981

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  • Cite this

    Estes, A., & Ball, M. (2017). Data-driven planning for ground delay programs. In Transportation Research Record (pp. 13-20). (Transportation Research Record; Vol. 2603). National Research Council. https://doi.org/10.3141/2603-02