The runway configuration is a key driver of airport capacity at any time. Several factors, such as wind speed, wind direction, visibility, traffic demand, air traffic controller workload, and the coordination of flows with neighboring airports influence the selection of the runway configuration. This paper identifies a discrete-choice model of the configuration selection process from empirical data. The model reflects the importance of various factors in terms of a utility function. Given the weather, traffic demand and the current runway configuration, the model provides a probabilistic forecast of the runway configuration at the next 15-minute interval. This prediction is then extended to obtain the probabilistic forecast of runway configuration on time horizons up to 6 hours. Case studies for Newark (EWR), John F. Kennedy (JFK), LaGuardia (LGA), and San-Francisco (SFO) airports are completed with this approach, first by assuming perfect knowledge of future weather and demand, and then using the Terminal Aerodrome Forecasts (TAFs). The results show that given the actual traffic demand and weather conditions 3 hours in advance, the models predict the correct runway configuration at EWR, JFK, LGA, and SFO with accuracies 79.5%, 63.8%, 81.3% and 82.8% respectively. Given the forecast weather and scheduled demand 3 hours in advance, the models predict the correct runway configuration at EWR, LGA, and SFO with accuracies 78.9%, 78.9% and 80.8% respectively. Finally, the discrete-choice method is applied to the entire New York Metroplex using two different methodologies and is shown to predict the Metroplex configuration with accuracies of 69.0% on a 3 hour prediction horizon.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Data-driven modeling of the airport runway configuration selection process using maximum likelihood discrete-choice models


    Beteiligte:

    Erscheinungsdatum :

    2016


    Format / Umfang :

    106 pages


    Anmerkungen:

    Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016.
    Cataloged from PDF version of thesis.
    Includes bibliographical references (pages 103-106).


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Predicting Airport Runway Configuration: A Discrete-Choice Modeling Approach

    Avery, Jacob Bryan / Balakrishnan, Hamsa | DSpace@MIT | 2015

    Freier Zugriff

    Airport energy conservation and runway configuration

    Li Xiong / Chen Xiaoqing | DOAJ | 2024

    Freier Zugriff

    Adaptive decision-making method for airport runway configuration

    ZENG WEILI / WANG SHASHA / JIANG HAO et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    Newark Airport Runway

    King, Gayle / Rowe, Geoffrey / Reinke, Gerry | Transportation Research Record | 2013


    Airport Runway Brooms

    SAE Technical Papers | 2016