On the Statistics and Predictability of Go-Arounds
This paper takes an empirical approach to identify operational factors at busy airports that may predate go-around maneuvers. Using four years of data from San Francisco International Airport, we begin our investigation with a statistical approach to investigate which features of airborne, ground op...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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2015
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| Online Access: | http://hdl.handle.net/1721.1/96937 https://orcid.org/0000-0002-0505-1400 |
| _version_ | 1826211941185486848 |
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| author | Gariel, Maxime Spieser, Kevin Frazzoli, Emilio |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Gariel, Maxime Spieser, Kevin Frazzoli, Emilio |
| author_sort | Gariel, Maxime |
| collection | MIT |
| description | This paper takes an empirical approach to identify operational factors at busy airports that may predate go-around maneuvers. Using four years of data from San Francisco International Airport, we begin our investigation with a statistical approach to investigate which features of airborne, ground operations (e.g., number of inbound aircraft, number of aircraft taxiing from gate, etc.) or weather are most likely to fluctuate, relative to nominal operations, in the minutes immediately preceding a missed approach. We analyze these findings both in terms of their implication on current airport operations and discuss how the antecedent factors may affect NextGen. Finally, as a means to assist air traffic controllers, we draw upon techniques from the machine learning community to develop a preliminary alert system for go-around prediction. |
| first_indexed | 2024-09-23T15:13:50Z |
| format | Article |
| id | mit-1721.1/96937 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:13:50Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | mit-1721.1/969372022-10-02T01:29:25Z On the Statistics and Predictability of Go-Arounds Gariel, Maxime Spieser, Kevin Frazzoli, Emilio Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Massachusetts Institute of Technology. Laboratory for Information and Decision Systems Gariel, Maxime Spieser, Kevin Frazzoli, Emilio This paper takes an empirical approach to identify operational factors at busy airports that may predate go-around maneuvers. Using four years of data from San Francisco International Airport, we begin our investigation with a statistical approach to investigate which features of airborne, ground operations (e.g., number of inbound aircraft, number of aircraft taxiing from gate, etc.) or weather are most likely to fluctuate, relative to nominal operations, in the minutes immediately preceding a missed approach. We analyze these findings both in terms of their implication on current airport operations and discuss how the antecedent factors may affect NextGen. Finally, as a means to assist air traffic controllers, we draw upon techniques from the machine learning community to develop a preliminary alert system for go-around prediction. United States. National Aeronautics and Space Administration (Grant NNX08AY52A)) 2015-05-08T14:36:04Z 2015-05-08T14:36:04Z 2011-10 Article http://purl.org/eprint/type/ConferencePaper http://hdl.handle.net/1721.1/96937 Gariel, Maxime, Kevin Spieser, and Emilio Frazzoli. "On the Statistics and Predictability of Go-Arounds." 2011 Conference on Intelligent Data Understanding, October 19-21, 2011. https://orcid.org/0000-0002-0505-1400 en_US https://c3.nasa.gov/dashlink/static/media/other/CIDU_Proceedings2011.pdf Proceedings of the 2011 Conference on Intelligent Data Understanding Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf arXiv |
| spellingShingle | Gariel, Maxime Spieser, Kevin Frazzoli, Emilio On the Statistics and Predictability of Go-Arounds |
| title | On the Statistics and Predictability of Go-Arounds |
| title_full | On the Statistics and Predictability of Go-Arounds |
| title_fullStr | On the Statistics and Predictability of Go-Arounds |
| title_full_unstemmed | On the Statistics and Predictability of Go-Arounds |
| title_short | On the Statistics and Predictability of Go-Arounds |
| title_sort | on the statistics and predictability of go arounds |
| url | http://hdl.handle.net/1721.1/96937 https://orcid.org/0000-0002-0505-1400 |
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