Investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model

Unstable approach is an adverse aviation event, and it is strongly related to the interaction between pilots and air traffic controllers (ATCOs). Mental model disconnects among team members can be a major cause of possible interaction conflicts and defective team cognition. Therefore, to study the n...

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Main Authors: Lai, Hsueh-Yi, Chen, Chun-Hsien, Zheng, Pai, Khoo, Li Pheng
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/161117
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1611172022-08-16T05:49:24Z Investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model Lai, Hsueh-Yi Chen, Chun-Hsien Zheng, Pai Khoo, Li Pheng School of Mechanical and Aerospace Engineering Engineering::Aeronautical engineering Agent-Based Model Landing Safety Unstable approach is an adverse aviation event, and it is strongly related to the interaction between pilots and air traffic controllers (ATCOs). Mental model disconnects among team members can be a major cause of possible interaction conflicts and defective team cognition. Therefore, to study the negative effects of various mental model disconnects, a framework of evolving team cognition (FETC) is proposed to examine the evolving context of an accident. An agent-based model (ABM) is developed to simulate how mental model disconnects are involved in evolving landing scenarios. The results of a simulation conducted with the ABM indicate that mental model disconnects occur more frequently as an aircraft approaches the terminal area. For landing scenarios in the outer area between 100 and 50 nautical miles (Nm), task-related mental model disconnects occur more frequently, causing incompatibility between parties. The incompatibility reveals the necessity of extra coordination to prevent the potential occurrence of system errors. As for the scenarios around the terminal area (30–15 Nm), the team-related mental model disconnects prevail, leading to passive information dissemination regarding changing conditions and late initiation of urgent coordination. The combination of these factors causes a team to miss the window for preventing an adverse event. Nanyang Technological University This work was supported by the Air Traffic Management Research Institute, Nanyang Technological University, Singapore [grant number ATMRI:2014-R5-CHEN]. 2022-08-16T05:49:24Z 2022-08-16T05:49:24Z 2020 Journal Article Lai, H., Chen, C., Zheng, P. & Khoo, L. P. (2020). Investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model. Reliability Engineering and System Safety, 193, 106657-. https://dx.doi.org/10.1016/j.ress.2019.106657 0951-8320 https://hdl.handle.net/10356/161117 10.1016/j.ress.2019.106657 2-s2.0-85072706288 193 106657 en ATMRI:2014-R5-CHEN Reliability Engineering and System Safety © 2019 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Aeronautical engineering
Agent-Based Model
Landing Safety
spellingShingle Engineering::Aeronautical engineering
Agent-Based Model
Landing Safety
Lai, Hsueh-Yi
Chen, Chun-Hsien
Zheng, Pai
Khoo, Li Pheng
Investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model
description Unstable approach is an adverse aviation event, and it is strongly related to the interaction between pilots and air traffic controllers (ATCOs). Mental model disconnects among team members can be a major cause of possible interaction conflicts and defective team cognition. Therefore, to study the negative effects of various mental model disconnects, a framework of evolving team cognition (FETC) is proposed to examine the evolving context of an accident. An agent-based model (ABM) is developed to simulate how mental model disconnects are involved in evolving landing scenarios. The results of a simulation conducted with the ABM indicate that mental model disconnects occur more frequently as an aircraft approaches the terminal area. For landing scenarios in the outer area between 100 and 50 nautical miles (Nm), task-related mental model disconnects occur more frequently, causing incompatibility between parties. The incompatibility reveals the necessity of extra coordination to prevent the potential occurrence of system errors. As for the scenarios around the terminal area (30–15 Nm), the team-related mental model disconnects prevail, leading to passive information dissemination regarding changing conditions and late initiation of urgent coordination. The combination of these factors causes a team to miss the window for preventing an adverse event.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Lai, Hsueh-Yi
Chen, Chun-Hsien
Zheng, Pai
Khoo, Li Pheng
format Article
author Lai, Hsueh-Yi
Chen, Chun-Hsien
Zheng, Pai
Khoo, Li Pheng
author_sort Lai, Hsueh-Yi
title Investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model
title_short Investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model
title_full Investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model
title_fullStr Investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model
title_full_unstemmed Investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model
title_sort investigating the evolving context of an unstable approach in aviation from mental model disconnects with an agent-based model
publishDate 2022
url https://hdl.handle.net/10356/161117
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