A holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems

In a complex system, a heterogeneous team with diverse expertise should coordinate to solve complex problems. However, goal differences and various information systems have been identified as causing operational disconnects and resource competition between agents. This research, based on Changi Airp...

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Main Author: Lai, Hsueh-Yi
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/154067
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1540672022-02-14T08:26:43Z A holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems Lai, Hsueh-Yi School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Air Traffic Control Landing System In a complex system, a heterogeneous team with diverse expertise should coordinate to solve complex problems. However, goal differences and various information systems have been identified as causing operational disconnects and resource competition between agents. This research, based on Changi Airport, Singapore, investigates the relationship among information sharing, two types of interactions, and system outcomes by performing agent-based modeling (ABM) to obtain practical strategies for avoiding conflicts related to resource competition in heterogeneous teams. Simulation results are assessed by considering reliability and efficiency. The system with improved implicit interactions reduces fuel consumption by up to 13%. Simultaneously, both types of interactions partially improve system reliability by reducing the need for go-arounds and facilitate system efficiency by improving the overall mobility of air traffic flow. The system with a mixing pattern of interactions achieves optimal improvements. To fully leverage the potential benefits, both types of interactions should be considered integrally. Accordingly, information that reveals the onset of nonroutine scenarios should be monitored by both parties to connect implicit and explicit interactions. Nanyang Technological University Published version This work was supported in part by the Air Traffic Management Research Institute (ATMRI) under Grant ATMRI:2014-R5-CHEN. 2022-02-14T08:26:43Z 2022-02-14T08:26:43Z 2021 Journal Article Lai, H. (2021). A holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems. IEEE Access, 9, 108513-108526. https://dx.doi.org/10.1109/ACCESS.2021.3101215 2169-3536 https://hdl.handle.net/10356/154067 10.1109/ACCESS.2021.3101215 2-s2.0-85112617405 9 108513 108526 en ATMRI:2014-R5-CHEN. IEEE Access © 2021 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Air Traffic Control
Landing System
spellingShingle Engineering::Mechanical engineering
Air Traffic Control
Landing System
Lai, Hsueh-Yi
A holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems
description In a complex system, a heterogeneous team with diverse expertise should coordinate to solve complex problems. However, goal differences and various information systems have been identified as causing operational disconnects and resource competition between agents. This research, based on Changi Airport, Singapore, investigates the relationship among information sharing, two types of interactions, and system outcomes by performing agent-based modeling (ABM) to obtain practical strategies for avoiding conflicts related to resource competition in heterogeneous teams. Simulation results are assessed by considering reliability and efficiency. The system with improved implicit interactions reduces fuel consumption by up to 13%. Simultaneously, both types of interactions partially improve system reliability by reducing the need for go-arounds and facilitate system efficiency by improving the overall mobility of air traffic flow. The system with a mixing pattern of interactions achieves optimal improvements. To fully leverage the potential benefits, both types of interactions should be considered integrally. Accordingly, information that reveals the onset of nonroutine scenarios should be monitored by both parties to connect implicit and explicit interactions.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Lai, Hsueh-Yi
format Article
author Lai, Hsueh-Yi
author_sort Lai, Hsueh-Yi
title A holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems
title_short A holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems
title_full A holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems
title_fullStr A holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems
title_full_unstemmed A holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems
title_sort holistic team cognition with better information transparency : a mixing pattern of team interaction in landing systems
publishDate 2022
url https://hdl.handle.net/10356/154067
_version_ 1725985570454241280