Citation
Varun Ramanujam, Hamsa Balakrishnan. "Data-Driven Modeling of the Airport Configuration Selection Process". IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 45(4):490-499, August 2015.

Abstract
The runway configuration is the set of the runways at an airport that are used for arrivals and departures at any time. While many factors, including weather, expected demand, environmental considerations, and coordination of flows with neighboring airports, influence the choice of runway configuration, the actual selection decision is made by air traffic controllers in the airport tower. As a result, the capacity of an airport at any time is dependent on the behavior of human decision makers. This paper develops a statistical model to characterize the configuration selection decision process using empirical observations. The proposed approach, based on the discrete-choicemodeling framework, identifies the influence of various factors in terms of the utility function of the decision maker. The parameters of the utility functions are estimated through likelihood maximization. Correlations between different alternatives are captured using a multinomial nested logit model. A key novelty of this study is the quantitative assessment of the effect of inertia, or the resistance to configuration changes, on the configuration selection process. The developed models are used to predict the runway configuration 3 h ahead of time, given operating conditions such as wind, visibility, and demand. Case studies based on data from Newark (EWR) and La-Guardia (LGA) airports show that the proposed model predicts runway configuration choices significantly better than a baseline model that only considers the historical frequencies of occurrence of different configurations.

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• Ramanujam_Balakrishnan.pdf · application/pdf · 574 kbytes

• HTML

  Varun Ramanujam, Hamsa Balakrishnan. <a
  href="http://www.cps-forces.org/pubs/130.html"
  >Data-Driven Modeling of the Airport Configuration
  Selection Process</a>, <i>IEEE TRANSACTIONS ON
  HUMAN-MACHINE SYSTEMS</i>, 45(4):490-499, August 2015.

• Plain text

  Varun Ramanujam, Hamsa Balakrishnan. "Data-Driven
  Modeling of the Airport Configuration Selection
  Process". <i>IEEE TRANSACTIONS ON HUMAN-MACHINE
  SYSTEMS</i>, 45(4):490-499, August 2015.

• BibTeX

  @article{RamanujamBalakrishnan15_DataDrivenModelingOfAirportConfigurationSelectionProcess,
      author = {Varun Ramanujam and Hamsa Balakrishnan},
      title = {Data-Driven Modeling of the Airport Configuration
                Selection Process},
      journal = {IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS},
      volume = {45},
      number = {4},
      pages = {490-499},
      month = {August},
      year = {2015},
      abstract = {The runway configuration is the set of the runways
                at an airport that are used for arrivals and
                departures at any time. While many factors,
                including weather, expected demand, environmental
                considerations, and coordination of flows with
                neighboring airports, influence the choice of
                runway configuration, the actual selection
                decision is made by air traffic controllers in the
                airport tower. As a result, the capacity of an
                airport at any time is dependent on the behavior
                of human decision makers. This paper develops a
                statistical model to characterize the
                configuration selection decision process using
                empirical observations. The proposed approach,
                based on the discrete-choicemodeling framework,
                identifies the influence of various factors in
                terms of the utility function of the decision
                maker. The parameters of the utility functions are
                estimated through likelihood maximization.
                Correlations between different alternatives are
                captured using a multinomial nested logit model. A
                key novelty of this study is the quantitative
                assessment of the effect of inertia, or the
                resistance to configuration changes, on the
                configuration selection process. The developed
                models are used to predict the runway
                configuration 3 h ahead of time, given operating
                conditions such as wind, visibility, and demand.
                Case studies based on data from Newark (EWR) and
                La-Guardia (LGA) airports show that the proposed
                model predicts runway configuration choices
                significantly better than a baseline model that
                only considers the historical frequencies of
                occurrence of different configurations.},
      URL = {http://cps-forces.org/pubs/130.html}
  }
  

Posted by Saurabh Amin on 15 Apr 2016.
Groups: forces
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