Dragon-v: Detection and recognition of airplane goals with navigational visualization

Christabel Wayllace; Sunwoo Ha; Yuchen Han; Jiaming Hu; Shayan Monadjemi; William Yeoh; Alvitta Ottley

Dragon-v: Detection and recognition of airplane goals with navigational visualization

Christabel Wayllace
, Sunwoo Ha
, Yuchen Han
, Jiaming Hu
, Shayan Monadjemi
, William Yeoh
, Alvitta Ottley

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

We introduce Detection and Recognition of Airplane GOals with Navigational Visualization (DRAGON-V), a visualization system that uses probabilistic goal recognition to infer and display the most probable airport runway that a pilot is approaching. DRAGON-V is especially useful in cases of miscommunication, low visibility, or lack of airport familiarity which may result in a pilot deviating from the assigned taxiing route. The visualization system conveys relevant information, and updates according to the airplane's current geolocation. DRAGON-V aims to assist air traffic controllers in reducing incidents of runway incursions at airports.

Original language	English
Title of host publication	AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
Publisher	AAAI Press
Pages	13642-13643
Number of pages	2
ISBN (Electronic)	9781577358350
State	Published - 2020
Externally published	Yes
Event	34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States Duration: Feb 7 2020 → Feb 12 2020

Publication series

Name	AAAI 2020 - 34th AAAI Conference on Artificial Intelligence

Conference

Conference	34th AAAI Conference on Artificial Intelligence, AAAI 2020
Country/Territory	United States
City	New York
Period	02/7/20 → 02/12/20

Funding

We would like to thank the reviewers for their constructive comments and suggestions. This research is partially supported by Boeing under award 2018-BRT-PA-332 and by NSF under awards 1812619 and 1838364.

Cite this

@inproceedings{84e95fafdd3b481e933a268fdf6ea978,

title = "Dragon-v: Detection and recognition of airplane goals with navigational visualization",

abstract = "We introduce Detection and Recognition of Airplane GOals with Navigational Visualization (DRAGON-V), a visualization system that uses probabilistic goal recognition to infer and display the most probable airport runway that a pilot is approaching. DRAGON-V is especially useful in cases of miscommunication, low visibility, or lack of airport familiarity which may result in a pilot deviating from the assigned taxiing route. The visualization system conveys relevant information, and updates according to the airplane's current geolocation. DRAGON-V aims to assist air traffic controllers in reducing incidents of runway incursions at airports.",

author = "Christabel Wayllace and Sunwoo Ha and Yuchen Han and Jiaming Hu and Shayan Monadjemi and William Yeoh and Alvitta Ottley",

note = "Publisher Copyright: {\textcopyright} 2020, Association for the Advancement of Artificial Intelligence.; 34th AAAI Conference on Artificial Intelligence, AAAI 2020 ; Conference date: 07-02-2020 Through 12-02-2020",

year = "2020",

language = "English",

series = "AAAI 2020 - 34th AAAI Conference on Artificial Intelligence",

publisher = "AAAI Press",

pages = "13642--13643",

booktitle = "AAAI 2020 - 34th AAAI Conference on Artificial Intelligence",

}

Wayllace, C, Ha, S, Han, Y, Hu, J, Monadjemi, S, Yeoh, W & Ottley, A 2020, Dragon-v: Detection and recognition of airplane goals with navigational visualization. in AAAI 2020 - 34th AAAI Conference on Artificial Intelligence. AAAI 2020 - 34th AAAI Conference on Artificial Intelligence, AAAI Press, pp. 13642-13643, 34th AAAI Conference on Artificial Intelligence, AAAI 2020, New York, United States, 02/7/20.

Dragon-v: Detection and recognition of airplane goals with navigational visualization. / Wayllace, Christabel; Ha, Sunwoo; Han, Yuchen et al.
AAAI 2020 - 34th AAAI Conference on Artificial Intelligence. AAAI Press, 2020. p. 13642-13643 (AAAI 2020 - 34th AAAI Conference on Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Dragon-v

T2 - 34th AAAI Conference on Artificial Intelligence, AAAI 2020

AU - Wayllace, Christabel

AU - Ha, Sunwoo

AU - Han, Yuchen

AU - Hu, Jiaming

AU - Monadjemi, Shayan

AU - Yeoh, William

AU - Ottley, Alvitta

PY - 2020

Y1 - 2020

N2 - We introduce Detection and Recognition of Airplane GOals with Navigational Visualization (DRAGON-V), a visualization system that uses probabilistic goal recognition to infer and display the most probable airport runway that a pilot is approaching. DRAGON-V is especially useful in cases of miscommunication, low visibility, or lack of airport familiarity which may result in a pilot deviating from the assigned taxiing route. The visualization system conveys relevant information, and updates according to the airplane's current geolocation. DRAGON-V aims to assist air traffic controllers in reducing incidents of runway incursions at airports.

AB - We introduce Detection and Recognition of Airplane GOals with Navigational Visualization (DRAGON-V), a visualization system that uses probabilistic goal recognition to infer and display the most probable airport runway that a pilot is approaching. DRAGON-V is especially useful in cases of miscommunication, low visibility, or lack of airport familiarity which may result in a pilot deviating from the assigned taxiing route. The visualization system conveys relevant information, and updates according to the airplane's current geolocation. DRAGON-V aims to assist air traffic controllers in reducing incidents of runway incursions at airports.

UR - https://www.scopus.com/pages/publications/85101009165

M3 - Conference contribution

AN - SCOPUS:85101009165

T3 - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence

SP - 13642

EP - 13643

BT - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence

PB - AAAI Press

Y2 - 7 February 2020 through 12 February 2020

ER -

Dragon-v: Detection and recognition of airplane goals with navigational visualization

Abstract

Publication series

Conference

Funding

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