Optimizing aircraft flows at airports using data driven predicted capabilities
Abstract
A method for safe and efficient use of airport runway capacity includes receiving, at an air traffic control system at an airport, airport data related to movement areas of the airport, time data related to a time period, aircraft data related to a plurality of aircraft expected to operate into and out of the airport during the time period, and environmental data related to environmental conditions predicted for the airport during the time period. The method further includes computing a probability distribution for inter-aircraft spacing by applying the airport data, the time data, the aircraft data, and the environmental data to a trained Bayesian network, producing the probability distribution for the inter-aircraft spacing as an output observation of the trained Bayesian network, and, using the probability distribution and a confidence value, identifying an inter-aircraft spacing value for the plurality of aircraft expected to operate into and out of the airport during the time period.
- Inventors:
- Issue Date:
- Research Org.:
- Architecture Technology Corporation, Minneapolis, MN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1986813
- Patent Number(s):
- 11501039
- Application Number:
- 17/012,332
- Assignee:
- Architecture Technology Corporation (Minneapolis, MN)
- DOE Contract Number:
- 80NSSC18C0036; NNX17CL38P
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 09/04/2020
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Sweet, Douglas, Timar, Sebastian, and Stillerman, Matthew. Optimizing aircraft flows at airports using data driven predicted capabilities. United States: N. p., 2022.
Web.
Sweet, Douglas, Timar, Sebastian, & Stillerman, Matthew. Optimizing aircraft flows at airports using data driven predicted capabilities. United States.
Sweet, Douglas, Timar, Sebastian, and Stillerman, Matthew. Tue .
"Optimizing aircraft flows at airports using data driven predicted capabilities". United States. https://www.osti.gov/servlets/purl/1986813.
@article{osti_1986813,
title = {Optimizing aircraft flows at airports using data driven predicted capabilities},
author = {Sweet, Douglas and Timar, Sebastian and Stillerman, Matthew},
abstractNote = {A method for safe and efficient use of airport runway capacity includes receiving, at an air traffic control system at an airport, airport data related to movement areas of the airport, time data related to a time period, aircraft data related to a plurality of aircraft expected to operate into and out of the airport during the time period, and environmental data related to environmental conditions predicted for the airport during the time period. The method further includes computing a probability distribution for inter-aircraft spacing by applying the airport data, the time data, the aircraft data, and the environmental data to a trained Bayesian network, producing the probability distribution for the inter-aircraft spacing as an output observation of the trained Bayesian network, and, using the probability distribution and a confidence value, identifying an inter-aircraft spacing value for the plurality of aircraft expected to operate into and out of the airport during the time period.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2022},
month = {11}
}
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