IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v237y2023ics0951832023002703.html
   My bibliography  Save this article

Breakdowns in team resilience during aircraft landing due to mental model disconnects as identified through machine learning

Author

Listed:
  • Lai, Hsueh-Yi

Abstract

Landing system in aviation is a representative sociotechnical system; such systems often require seamless teamwork among experts. Resilience is critical for the ability of a team to adapt to sudden changes, overcome challenges, and return to normalcy. However, team heterogeneity can result in cognitive misalignment, known as mental model disconnects (MMDs). MMDs can cause interaction conflcits, which compromise team resilience. This study aimed to use machine learning to identify breakdowns in team resilience during aircraft landing. The results showed that the MMDs in the terminal area had the greatest influence on missed approaches; in particular, the late intervention of air traffic controllers’ (ATCOs) in an improper landing state was the major breakdown identified. This result highlights the importance of ATCO initiative in preventing landing incidents. The mechanism was determined to be ineffective information dissemination in nonroutine scenarios, which unravels the necessity for improving future information systems.

Suggested Citation

  • Lai, Hsueh-Yi, 2023. "Breakdowns in team resilience during aircraft landing due to mental model disconnects as identified through machine learning," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
  • Handle: RePEc:eee:reensy:v:237:y:2023:i:c:s0951832023002703
    DOI: 10.1016/j.ress.2023.109356
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023002703
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2023.109356?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lai, Hsueh-Yi & Chen, Chun-Hsien & Khoo, Li-Pheng & Zheng, Pai, 2019. "Unstable approach in aviation: Mental model disconnects between pilots and air traffic controllers and interaction conflicts," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 383-391.
    2. Foster, Craig J. & Plant, Katherine L. & Stanton, Neville A., 2021. "A very temporary operating instruction: Uncovering emergence and adaptation in air traffic control," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    3. Zhang, Xiaoge & Mahadevan, Sankaran, 2021. "Bayesian network modeling of accident investigation reports for aviation safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    4. Dabin Xue & Kam K. H. Ng & Li-Ta Hsu, 2020. "Multi-Objective Flight Altitude Decision Considering Contrails, Fuel Consumption and Flight Time," Sustainability, MDPI, vol. 12(15), pages 1-20, August.
    5. Moriarty, David & Jarvis, Steve, 2014. "A systems perspective on the unstable approach in commercial aviation," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 197-202.
    6. Schultz, Michael & Rosenow, Judith & Olive, Xavier, 2022. "Data-driven airport management enabled by operational milestones derived from ADS-B messages," Journal of Air Transport Management, Elsevier, vol. 99(C).
    7. Lai, Hsueh-Yi & Chen, Chun-Hsien & Zheng, Pai & Khoo, Li Pheng, 2019. "Towards better information transparency in the air traffic landing system: A novel agent-based model with implicit interactions," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    8. Ham, Dong-Han & Jung, Won-Jun & Park, Jinkyun, 2021. "Identifying key factors affecting the performance of team decision-making based on the analysis of investigation reports issued from diverse industries," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    9. Marie-Sklaerder Vié & Nicolas Zufferey & Roel Leus, 2022. "Aircraft landing planning under uncertain conditions," Journal of Scheduling, Springer, vol. 25(2), pages 203-228, April.
    10. Lai, Hsueh-Yi & Chen, Chun-Hsien & Zheng, Pai & Khoo, Li Pheng, 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, Elsevier, vol. 193(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xue, Dabin & Liu, Zhizhao & Wang, Bing & Yang, Jian, 2021. "Impacts of COVID-19 on aircraft usage and fuel consumption: A case study on four Chinese international airports," Journal of Air Transport Management, Elsevier, vol. 95(C).
    2. Lai, Hsueh-Yi & Chen, Chun-Hsien & Zheng, Pai & Khoo, Li Pheng, 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, Elsevier, vol. 193(C).
    3. Lai, Hsueh-Yi & Chen, Chun-Hsien & Zheng, Pai & Khoo, Li Pheng, 2019. "Towards better information transparency in the air traffic landing system: A novel agent-based model with implicit interactions," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    4. Wen, Tao & Gao, Qiuya & Chen, Yu-wang & Cheong, Kang Hao, 2022. "Exploring the vulnerability of transportation networks by entropy: A case study of Asia–Europe maritime transportation network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    5. Ayoub, Ali & Stankovski, Andrej & Kröger, Wolfgang & Sornette, Didier, 2021. "Precursors and startling lessons: Statistical analysis of 1250 events with safety significance from the civil nuclear sector," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    6. Thowayeb H. Hassan & Abu Elnasr E. Sobaih & Amany E. Salem, 2021. "Factors Affecting the Rate of Fuel Consumption in Aircrafts," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    7. Yazdi, Mohammad & Khan, Faisal & Abbassi, Rouzbeh & Quddus, Noor & Castaneda-Lopez, Homero, 2022. "A review of risk-based decision-making models for microbiologically influenced corrosion (MIC) in offshore pipelines," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    8. Bhuyan, Kasturi & Sharma, Hrishikesh, 2022. "Reliability analysis & performance-based code calibration for slabs/walls of protective structures subject to air blast loading," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    9. Zhou, Di & Zhuang, Xiao & Zuo, Hongfu & Cai, Jing & Zhao, Xufeng & Xiang, Jiawei, 2022. "A model fusion strategy for identifying aircraft risk using CNN and Att-BiLSTM," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    10. Rose, Rodrigo L. & Mugi, Sohan R. & Saleh, Joseph Homer, 2023. "Accident investigation and lessons not learned: AcciMap analysis of successive tailings dam collapses in Brazil," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    11. Zhou, Taotao & Zhang, Xiaoge & Droguett, Enrique Lopez & Mosleh, Ali, 2023. "A generic physics-informed neural network-based framework for reliability assessment of multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    12. Sezer, Sukru Ilke & Camliyurt, Gokhan & Aydin, Muhmmet & Akyuz, Emre & Gardoni, Paolo, 2023. "A bow-tie extended D-S evidence-HEART modelling for risk analysis of cargo tank cracks on oil/chemical tanker," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    13. Liu, Jianqiao & Zou, Yanhua & Wang, Wei & Zio, Enrico & Yuan, Chengwei & Wang, Taorui & Jiang, Jianjun, 2022. "A Bayesian belief network framework for nuclear power plant human reliability analysis accounting for dependencies among performance shaping factors," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    14. Tian-yuan, Ye & Lin-lin, Liu & He-wei, Pang & Yuan-zi, Zhou, 2023. "Bayesian Networks based approach to enhance GO methodology for reliability modeling of multi-state consecutive-k-out-of-n: F system," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    15. Yang, Hui-Hua & Chang, Yu-Hern & Chou, Yi-Hui, 2023. "Subjective measures of communication errors between pilots and air traffic controllers," Journal of Air Transport Management, Elsevier, vol. 112(C).
    16. Lai, Hsueh-Yi & Chen, Chun-Hsien & Khoo, Li-Pheng & Zheng, Pai, 2019. "Unstable approach in aviation: Mental model disconnects between pilots and air traffic controllers and interaction conflicts," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 383-391.
    17. Gangolu, Jaswanth & Kumar, Ajay & Bhuyan, Kasturi & Sharma, Hrishikesh, 2022. "Probabilistic demand models and performance-based fragility estimates for concrete protective structures subjected to missile impact," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    18. Ballester-Ripoll, Rafael & Leonelli, Manuele, 2022. "Computing Sobol indices in probabilistic graphical models," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    19. Dabin Xue & Kam K. H. Ng & Li-Ta Hsu, 2020. "Multi-Objective Flight Altitude Decision Considering Contrails, Fuel Consumption and Flight Time," Sustainability, MDPI, vol. 12(15), pages 1-20, August.
    20. Zhou, Jian-Lan & Yu, Ze-Tai & Xiao, Ren-Bin, 2022. "A large-scale group Success Likelihood Index Method to estimate human error probabilities in the railway driving process," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:237:y:2023:i:c:s0951832023002703. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.