A Fuzzy‐Based Risk Assessment Framework for Autonomous Underwater Vehicle Under‐Ice Missions

• Published in: Risk Analysis
• Main Authors: Loh, Tzu Yang, Brito, Mario P., Bose, Neil, Xu, Jingjing, Tenekedjiev, Kiril
• Other Authors: Australian Research Council
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2019
• Subjects: Antarc*; Antarctic
• Online Access: http://dx.doi.org/10.1111/risa.13376; https://onlinelibrary.wiley.com/doi/pdf/10.1111/risa.13376; https://onlinelibrary.wiley.com/doi/full-xml/10.1111/risa.13376; https://onlinelibrary.wiley.com/doi/am-pdf/10.1111/risa.13376

Abstract 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.