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A fuzzy-based risk assessment framework for autonomous underwater vehicle under-ice missions

Loh, Tzu Yang; Brito, Mario P.; Bose, Neil; Xu, Jingjing; Tenekedjiev, Kiril


Tzu Yang Loh

Mario P. Brito

Neil Bose

Jingjing Xu

Kiril Tenekedjiev


© 2019 Society for Risk Analysis The use of autonomous underwater vehicles (AUVs) for various scientific, commercial, and military applications has become more common with maturing technology and improved accessibility. One relatively new development lies in the use of AUVs for under-ice marine science research in the Antarctic. The extreme environment, ice cover, and inaccessibility as compared to open-water missions can result in a higher risk of loss. Therefore, having an effective assessment of risks before undertaking any Antarctic under-ice missions is crucial to ensure an AUV's survival. Existing risk assessment approaches predominantly focused on the use of historical fault log data of an AUV and elicitation of experts’ opinions for probabilistic quantification. However, an AUV program in its early phases lacks historical data and any assessment of risk may be vague and ambiguous. In this article, a fuzzy-based risk assessment framework is proposed for quantifying the risk of AUV loss under ice. The framework uses the knowledge, prior experience of available subject matter experts, and the widely used semiquantitative risk assessment matrix, albeit in a new form. A well-developed example based on an upcoming mission by an ISE-explorer class AUV is presented to demonstrate the application and effectiveness of the proposed framework. The example demonstrates that the proposed fuzzy-based risk assessment framework is pragmatically useful for future under-ice AUV deployments. Sensitivity analysis demonstrates the validity of the proposed method.


Loh, T. Y., Brito, M. P., Bose, N., Xu, J., & Tenekedjiev, K. (2019). A fuzzy-based risk assessment framework for autonomous underwater vehicle under-ice missions. Risk Analysis, 39(12), 2744-2765.

Journal Article Type Article
Acceptance Date Jun 12, 2019
Online Publication Date Jul 18, 2019
Publication Date Dec 1, 2019
Deposit Date Mar 7, 2020
Journal Risk Analysis
Print ISSN 0272-4332
Electronic ISSN 1539-6924
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 39
Issue 12
Pages 2744-2765
Keywords Physiology (medical); Safety, Risk, Reliability and Quality
Public URL
Related Public URLs
Additional Information Received: 2018-02-11; Accepted: 2019-06-12; Published: 2019-07-18