IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v40y2020i6p1258-1278.html

Human Error in Autonomous Underwater Vehicle Deployment: A System Dynamics Approach

Author

Listed:
  • Tzu Yang Loh
  • Mario P. Brito
  • Neil Bose
  • Jingjing Xu
  • Kiril Tenekedjiev

Abstract

The use of autonomous underwater vehicles (AUVs) for various applications have grown with maturing technology and improved accessibility. The deployment of AUVs for under‐ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extremities in the Antarctic. A thorough analysis of risks is therefore crucial for formulating effective risk control policies and achieving a lower risk of loss. Existing risk analysis approaches focused predominantly on the technical aspects, as well as identifying static cause and effect relationships in the chain of events leading to AUV loss. Comparatively, the complex interrelationships between risk variables and other aspects of risk such as human errors have received much lesser attention. In this article, a systems‐based risk analysis framework facilitated by system dynamics methodology is proposed to overcome existing shortfalls. To demonstrate usefulness of the framework, it is applied on an actual AUV program to examine the occurrence of human error during Antarctic deployment. Simulation of the resultant risk model showed an overall decline in human error incident rate with the increase in experience of the AUV team. Scenario analysis based on the example provided policy recommendations in areas of training, practice runs, recruitment policy, and setting of risk tolerance level. The proposed risk analysis framework is pragmatically useful for risk analysis of future AUV programs to ensure the sustainability of operations, facilitating both better control and monitoring of risk.

Suggested Citation

  • Tzu Yang Loh & Mario P. Brito & Neil Bose & Jingjing Xu & Kiril Tenekedjiev, 2020. "Human Error in Autonomous Underwater Vehicle Deployment: A System Dynamics Approach," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1258-1278, June.
  • Handle: RePEc:wly:riskan:v:40:y:2020:i:6:p:1258-1278
    DOI: 10.1111/risa.13467
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/risa.13467
    Download Restriction: no

    File URL: https://libkey.io/10.1111/risa.13467?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
    ---><---

    References listed on IDEAS

    as
    1. Brito, Mario & Griffiths, Gwyn, 2016. "A Bayesian approach for predicting risk of autonomous underwater vehicle loss during their missions," Reliability Engineering and System Safety, Elsevier, vol. 146(C), pages 55-67.
    2. Mario Paulo Brito & Gwyn Griffiths & Peter Challenor, 2010. "Risk Analysis for Autonomous Underwater Vehicle Operations in Extreme Environments," Risk Analysis, John Wiley & Sons, vol. 30(12), pages 1771-1788, December.
    3. Yacov Y. Haimes, 2009. "On the Complex Definition of Risk: A Systems‐Based Approach," Risk Analysis, John Wiley & Sons, vol. 29(12), pages 1647-1654, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xi Zhang & Te Zhang & Xin Wei & Zhanpeng Xiao & Weiwen Zhang, 2024. "Reducing potential dual-use risks in synthetic biology laboratory research: a dynamic model of analysis," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    2. Chen, Xi & Bose, Neil & Brito, Mario & Khan, Faisal & Thanyamanta, Bo & Zou, Ting, 2021. "A Review of Risk Analysis Research for the Operations of Autonomous Underwater Vehicles," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

    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. Tzu Yang Loh & Mario P. Brito & Neil Bose & Jingjing Xu & Kiril Tenekedjiev, 2020. "Fuzzy System Dynamics Risk Analysis (FuSDRA) of Autonomous Underwater Vehicle Operations in the Antarctic," Risk Analysis, John Wiley & Sons, vol. 40(4), pages 818-841, April.
    2. Chen, Xi & Bose, Neil & Brito, Mario & Khan, Faisal & Thanyamanta, Bo & Zou, Ting, 2021. "A Review of Risk Analysis Research for the Operations of Autonomous Underwater Vehicles," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    3. Christoph Alexander Thieme & Ingrid Bouwer Utne, 2017. "A risk model for autonomous marine systems and operation focusing on human–autonomy collaboration," Journal of Risk and Reliability, , vol. 231(4), pages 446-464, August.
    4. Mario P. Brito & Ian G. J. Dawson, 2020. "Predicting the Validity of Expert Judgments in Assessing the Impact of Risk Mitigation Through Failure Prevention and Correction," Risk Analysis, John Wiley & Sons, vol. 40(10), pages 1928-1943, October.
    5. Luca Allodi & Fabio Massacci, 2017. "Security Events and Vulnerability Data for Cybersecurity Risk Estimation," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1606-1627, August.
    6. Yacov Y. Haimes, 2011. "Responses to Terje Aven's Paper: On Some Recent Definitions and Analysis Frameworks for Risk, Vulnerability, and Resilience," Risk Analysis, John Wiley & Sons, vol. 31(5), pages 689-692, May.
    7. Corinne Curt & Jean‐Marc Tacnet, 2018. "Resilience of Critical Infrastructures: Review and Analysis of Current Approaches," Risk Analysis, John Wiley & Sons, vol. 38(11), pages 2441-2458, November.
    8. Thieme, Christoph A. & Utne, Ingrid B., 2017. "Safety performance monitoring of autonomous marine systems," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 264-275.
    9. Tzu Yang Loh & Mario P. Brito & Neil Bose & Jingjing Xu & Kiril Tenekedjiev, 2019. "A Fuzzy‐Based Risk Assessment Framework for Autonomous Underwater Vehicle Under‐Ice Missions," Risk Analysis, John Wiley & Sons, vol. 39(12), pages 2744-2765, December.
    10. Wadström, Christoffer & Hedström, Axel, 2025. "Assessing the quantile dependence and interconnectedness of electricity utilisation across Swedish industrial sectors," Energy, Elsevier, vol. 320(C).
    11. Manan Vyas & M. Mija'il Mart'inez-Ramos & Parisa Majari & Thomas H. Seligman, 2025. "From sectorial coarse graining to extreme coarse graining of S&P 500 correlation matrices," Papers 2511.05463, arXiv.org.
    12. Xue, Gang & Gong, Daqing & Ren, Long & Cui, Ziruo, 2026. "Modeling expert risk assessments in utility tunnels with deep learning," Reliability Engineering and System Safety, Elsevier, vol. 265(PA).
    13. Almutairi, Ayedh & Collier, Zachary A. & Hendrickson, Daniel & Palma-Oliveira, José M. & Polmateer, Thomas L. & Lambert, James H., 2019. "Stakeholder mapping and disruption scenarios with application to resilience of a container port," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 219-232.
    14. Bruno Martinho & João Reis, 2022. "United Nations (UN) Disaster Risk Reduction Framework: Case Study of the Portuguese Army on UN Challenges in the Context of Sustainable Risk Mitigation," Sustainability, MDPI, vol. 14(3), pages 1-17, February.
    15. Chun-Hsien Lai & Pi-Ching Liao & Szu-Hung Chen & Yung-Chieh Wang & Chingwen Cheng & Chen-Fa Wu, 2021. "Risk Perception and Adaptation of Climate Change: An Assessment of Community Resilience in Rural Taiwan," Sustainability, MDPI, vol. 13(7), pages 1-15, March.
    16. BahooToroody, Ahmad & Abaei, Mohammad Mahdi & Banda, Osiris Valdez & Kujala, Pentti & De Carlo, Filippo & Abbassi, Rouzbeh, 2022. "Prognostic health management of repairable ship systems through different autonomy degree; From current condition to fully autonomous ship," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    17. T. Anderson & J. S. Busby & M. Rouncefield, 2020. "Understanding the Ecological Validity of Relying Practice as a Basis for Risk Identification," Risk Analysis, John Wiley & Sons, vol. 40(7), pages 1383-1398, July.
    18. Michael Greenberg & Karen Lowrie, 2010. "From the Editors," Risk Analysis, John Wiley & Sons, vol. 30(7), pages 1017-1018, July.
    19. Yacov Y. Haimes, 2011. "On the Complex Quantification of Risk: Systems‐Based Perspective on Terrorism," Risk Analysis, John Wiley & Sons, vol. 31(8), pages 1175-1186, August.
    20. Michael Francis D. Benjamin & Aristotle T. Ubando & Luis F. Razon & Raymond R. Tan, 2015. "Analyzing the disruption resilience of bioenergy parks using dynamic inoperability input–output modeling," Environment Systems and Decisions, Springer, vol. 35(3), pages 351-362, September.

    More about this item

    Statistics

    Access and download statistics

    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:wly:riskan:v:40:y:2020:i:6:p:1258-1278. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    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.