IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v146y2016icp55-67.html
   My bibliography  Save this article

A Bayesian approach for predicting risk of autonomous underwater vehicle loss during their missions

Author

Listed:
  • Brito, Mario
  • Griffiths, Gwyn

Abstract

Autonomous Underwater Vehicles (AUVs) are effective platforms for science research and monitoring, and for military and commercial data-gathering purposes. However, there is an inevitable risk of loss during any mission. Quantifying the risk of loss is complex, due to the combination of vehicle reliability and environmental factors, and cannot be determined through analytical means alone. An alternative approach – formal expert judgment – is a time-consuming process; consequently a method is needed to broaden the applicability of judgments beyond the narrow confines of an elicitation for a defined environment. We propose and explore a solution founded on a Bayesian Belief Network (BBN), where the results of the expert judgment elicitation are taken as the initial prior probability of loss due to failure. The network topology captures the causal effects of the environment separately on the vehicle and on the support platform, and combines these to produce an updated probability of loss due to failure. An extended version of the Kaplan–Meier estimator is then used to update the mission risk profile with travelled distance. Sensitivity analysis of the BBN is presented and a case study of Autosub3 AUV deployment in the Amundsen Sea is discussed in detail.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:146:y:2016:i:c:p:55-67
    DOI: 10.1016/j.ress.2015.10.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832015002860
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2015.10.004?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. Matellini, D.B. & Wall, A.D. & Jenkinson, I.D. & Wang, J. & Pritchard, R., 2013. "Modelling dwelling fire development and occupancy escape using Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 75-91.
    2. Hänninen, Maria & Kujala, Pentti, 2012. "Influences of variables on ship collision probability in a Bayesian belief network model," Reliability Engineering and System Safety, Elsevier, vol. 102(C), pages 27-40.
    3. Harry Otway & Detlof von Winterfeldt, 1992. "Expert Judgment in Risk Analysis and Management: Process, Context, and Pitfalls," Risk Analysis, John Wiley & Sons, vol. 12(1), pages 83-93, March.
    4. Mary Kynn, 2008. "The ‘heuristics and biases’ bias in expert elicitation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 239-264, January.
    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. 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. 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.
    3. Utne, Ingrid Bouwer & Rokseth, Børge & Sørensen, Asgeir J. & Vinnem, Jan Erik, 2020. "Towards supervisory risk control of autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    4. 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).
    5. 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).
    6. 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.
    7. Johansen, Thomas & Blindheim, Simon & Torben, Tobias Rye & Utne, Ingrid Bouwer & Johansen, Tor Arne & Sørensen, Asgeir J., 2023. "Development and testing of a risk-based control system for autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    8. 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.
    9. 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.
    10. 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.
    11. Hegde, Jeevith & Utne, Ingrid Bouwer & Schjølberg, Ingrid & Thorkildsen, Brede, 2018. "A Bayesian approach to risk modeling of autonomous subsea intervention operations," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 142-159.

    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. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.
    2. Wu, Jiansong & Zhang, Linlin & Bai, Yiping & Reniers, Genserik, 2022. "A safety investment optimization model for power grid enterprises based on System Dynamics and Bayesian network theory," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    3. Roland W. Scholz & Ralf Hansmann, 2007. "Combining Experts' Risk Judgments on Technology Performance of Phytoremediation: Self‐Confidence Ratings, Averaging Procedures, and Formative Consensus Building," Risk Analysis, John Wiley & Sons, vol. 27(1), pages 225-240, February.
    4. Carine Dominguez-Péry & Lakshmi Narasimha Raju Vuddaraju & Isabelle Corbett-Etchevers & Rana Tassabehji, 2021. "Reducing maritime accidents in ships by tackling human error: a bibliometric review and research agenda," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-32, December.
    5. Zhang, Yang & Sun, Xukai & Chen, Jihong & Cheng, Cheng, 2021. "Spatial patterns and characteristics of global maritime accidents," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    6. Li, Huanhuan & Çelik, Cihad & Bashir, Musa & Zou, Lu & Yang, Zaili, 2024. "Incorporation of a global perspective into data-driven analysis of maritime collision accident risk," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    7. Zhiwei Shen & Martin Odening & Ostap Okhrin, 2016. "Can expert knowledge compensate for data scarcity in crop insurance pricing?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(2), pages 237-269.
    8. Sotiralis, P. & Ventikos, N.P. & Hamann, R. & Golyshev, P. & Teixeira, A.P., 2016. "Incorporation of human factors into ship collision risk models focusing on human centred design aspects," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 210-227.
    9. Yuan Chen & Zhijie Zhou & Lihao Yang & Guanyu Hu & Xiaoxia Han & Shuaiwen Tang, 2022. "A novel structural safety assessment method of large liquid tank based on the belief rule base and finite element method," Journal of Risk and Reliability, , vol. 236(3), pages 458-476, June.
    10. Ine H. J. Van Der Fels‐Klerx & Louis H. J. Goossens & Helmut W. Saatkamp & Suzan H. S. Horst, 2002. "Elicitation of Quantitative Data from a Heterogeneous Expert Panel: Formal Process and Application in Animal Health," Risk Analysis, John Wiley & Sons, vol. 22(1), pages 67-81, February.
    11. Guizhen Zhang & Vinh V. Thai & Adrian Wing‐Keung Law & Kum Fai Yuen & Hui Shan Loh & Qingji Zhou, 2020. "Quantitative Risk Assessment of Seafarers’ Nonfatal Injuries Due to Occupational Accidents Based on Bayesian Network Modeling," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 8-23, January.
    12. Cai, Mingyou & Zhang, Jinfen & Zhang, Di & Yuan, Xiaoli & Soares, C. Guedes, 2021. "Collision risk analysis on ferry ships in Jiangsu Section of the Yangtze River based on AIS data," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    13. Wang, Likun & Yang, Zaili, 2018. "Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 277-289.
    14. Bing Wu & Huibin Tian & Xinping Yan & C. Guedes Soares, 2020. "A probabilistic consequence estimation model for collision accidents in the downstream of Yangtze River using Bayesian Networks," Journal of Risk and Reliability, , vol. 234(2), pages 422-436, April.
    15. Weiliang Qiao & Yu Liu & Xiaoxue Ma & Yang Liu, 2020. "Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network," Risk Analysis, John Wiley & Sons, vol. 40(5), pages 957-980, May.
    16. Fredrik Carlsson & Dinky Daruvala & Henrik Jaldell, 2012. "Do administrators have the same priorities for risk reductions as the general public?," Journal of Risk and Uncertainty, Springer, vol. 45(1), pages 79-95, August.
    17. repec:hum:wpaper:sfb649dp2013-030 is not listed on IDEAS
    18. 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.
    19. Radboud J. Duintjer Tebbens & Mark A. Pallansch & Konstantin M. Chumakov & Neal A. Halsey & Tapani Hovi & Philip D. Minor & John F. Modlin & Peter A. Patriarca & Roland W. Sutter & Peter F. Wright & S, 2013. "Review and Assessment of Poliovirus Immunity and Transmission: Synthesis of Knowledge Gaps and Identification of Research Needs," Risk Analysis, John Wiley & Sons, vol. 33(4), pages 606-646, April.
    20. Wang, Xinjian & Liu, Zhengjiang & Loughney, Sean & Yang, Zaili & Wang, Yanfu & Wang, Jin, 2022. "Numerical analysis and staircase layout optimisation for a Ro-Ro passenger ship during emergency evacuation," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    21. Fan, Shiqi & Blanco-Davis, Eduardo & Yang, Zaili & Zhang, Jinfen & Yan, Xinping, 2020. "Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 203(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:146:y:2016:i:c:p:55-67. 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.