Advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance

While favored by air traffic controllers (ATCOs), ATCO- conformal conflict resolution often lacks operational efficiency due to such potential issues as excessive aircraft deviations and higher separation buffers. This study investigated the potential of advancing beyond conformal conflict r...

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Main Authors: Guleria, Yash, Pham, Duc-Thinh, Alam, Sameer
Other Authors: 11th International Conference on Research in Air transportation (ICRAT 2024)
Format: Conference or Workshop Item
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/179379
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1793792024-08-06T15:30:52Z Advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance Guleria, Yash Pham, Duc-Thinh Alam, Sameer 11th International Conference on Research in Air transportation (ICRAT 2024) Air Traffic Management Research Institute Computer and Information Science Engineering Air traffic conflict resolution Machine learning Supervised learning Air traffic controllers Conformal automation Human-AI teaming While favored by air traffic controllers (ATCOs), ATCO- conformal conflict resolution often lacks operational efficiency due to such potential issues as excessive aircraft deviations and higher separation buffers. This study investigated the potential of advancing beyond conformal conflict resolution advisories in en- route air traffic control by balancing optimality and conformance of the advisories to bridge the gap between ATCO conformance and maneuver efficiency. Firstly, a machine learning (ML) approach is proposed to generate various conflict resolution advisories, includ- ing balanced options. Then, initial human-in-the-loop experiments with 6 experienced ATCOs were conducted, wherein ATCOs were required to rank conflict resolution advisories based on their preferences, for the presented conflict scenarios. Given the trade-off between conformance and efficiency of the conflict resolution ma- neuvers, this research investigated the ATCOs’ preferences among the resolution options provided, for the conflict scenarios. Results indicated a strong preference for conformal conflict resolution in 70 of 114 scenarios collected, with a significant inclination towards balanced resolutions in 62 scenarios, suggesting a move towards more efficient strategies without compromising conformance. Cu- mulatively, conformal and balanced conflict resolutions were the most favorable and second most favorable choices for 77.19% and 75.4% of the scenarios, respectively. ATCO feedback also indicated that such a conflict resolution advisory mechanism could prove useful in improving controller decision-making. These findings highlighted the need for further research into adaptive conflict resolution models that can potentially better balance the tradeoffs between optimal- and conformal resolution models. Civil Aviation Authority of Singapore (CAAS) National Research Foundation (NRF) Submitted/Accepted version This work is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme 2024-07-31T02:14:01Z 2024-07-31T02:14:01Z 2024 Conference Paper Guleria, Y., Pham, D. & Alam, S. (2024). Advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance. 11th International Conference on Research in Air transportation (ICRAT 2024). https://hdl.handle.net/10356/179379 en © 2024 ICRAT. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. The Version of Record is available online at https://www.icrat.org/upcoming-conference/papers/. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
Engineering
Air traffic conflict resolution
Machine learning
Supervised learning
Air traffic controllers
Conformal automation
Human-AI teaming
spellingShingle Computer and Information Science
Engineering
Air traffic conflict resolution
Machine learning
Supervised learning
Air traffic controllers
Conformal automation
Human-AI teaming
Guleria, Yash
Pham, Duc-Thinh
Alam, Sameer
Advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance
description While favored by air traffic controllers (ATCOs), ATCO- conformal conflict resolution often lacks operational efficiency due to such potential issues as excessive aircraft deviations and higher separation buffers. This study investigated the potential of advancing beyond conformal conflict resolution advisories in en- route air traffic control by balancing optimality and conformance of the advisories to bridge the gap between ATCO conformance and maneuver efficiency. Firstly, a machine learning (ML) approach is proposed to generate various conflict resolution advisories, includ- ing balanced options. Then, initial human-in-the-loop experiments with 6 experienced ATCOs were conducted, wherein ATCOs were required to rank conflict resolution advisories based on their preferences, for the presented conflict scenarios. Given the trade-off between conformance and efficiency of the conflict resolution ma- neuvers, this research investigated the ATCOs’ preferences among the resolution options provided, for the conflict scenarios. Results indicated a strong preference for conformal conflict resolution in 70 of 114 scenarios collected, with a significant inclination towards balanced resolutions in 62 scenarios, suggesting a move towards more efficient strategies without compromising conformance. Cu- mulatively, conformal and balanced conflict resolutions were the most favorable and second most favorable choices for 77.19% and 75.4% of the scenarios, respectively. ATCO feedback also indicated that such a conflict resolution advisory mechanism could prove useful in improving controller decision-making. These findings highlighted the need for further research into adaptive conflict resolution models that can potentially better balance the tradeoffs between optimal- and conformal resolution models.
author2 11th International Conference on Research in Air transportation (ICRAT 2024)
author_facet 11th International Conference on Research in Air transportation (ICRAT 2024)
Guleria, Yash
Pham, Duc-Thinh
Alam, Sameer
format Conference or Workshop Item
author Guleria, Yash
Pham, Duc-Thinh
Alam, Sameer
author_sort Guleria, Yash
title Advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance
title_short Advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance
title_full Advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance
title_fullStr Advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance
title_full_unstemmed Advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance
title_sort advancing beyond conformal conflict resolution in air traffic control: balancing efficiency and conformance
publishDate 2024
url https://hdl.handle.net/10356/179379
_version_ 1814047203349495808