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Fuzzy system dynamics risk analysis (FuSDRA) of autonomous underwater vehicle operations in the Antarctic


Loh, TY and Brito, MP and Bose, N and Xu, J and Tenekedjiev, K, Fuzzy system dynamics risk analysis (FuSDRA) of autonomous underwater vehicle operations in the Antarctic, Risk Analysis, 40, (4) pp. 818-841. ISSN 0272-4332 (2020) [Refereed Article]

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Copyright 2019 Society for Risk Analysis

DOI: doi:10.1111/risa.13429


With the maturing of autonomous technology and better accessibility, there has been a growing interest in the use of autonomous underwater vehicles (AUVs). 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 extreme operating environment. To control the risk of loss, existing risk analyses approaches tend to focus more on the AUVís technical aspects and neglect the role of soft factors, such as organizational and human influences. In addition, the dynamic and complex interrelationships of risk variables are also often overlooked due to uncertainties and challenges in quantification. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. In the FuSDRA framework, system dynamics models the interrelationships between risk variables from different dimensions and considers the time-dependent nature of risk while fuzzy logic accounts for uncertainties. To demonstrate its application, an example based on an actual Antarctic AUV program is presented. Focusing on funding and experience of the AUV team, simulation of the FuSDRA risk model shows a declining risk of loss from 0.293 in the early years of the Antarctic AUV program, reaching a minimum of 0.206 before increasing again in later years. Risk control policy recommendations were then derived from the analysis. The example demonstrated how FuSDRA can be applied to inform funding and risk management strategies, or broader application both within the AUV domain and on other complex technological systems.

Item Details

Item Type:Refereed Article
Keywords:autonomous underwater vehicle, fuzzy set theory, risk analysis, system dynamics
Research Division:Engineering
Research Group:Control engineering, mechatronics and robotics
Research Field:Autonomous vehicle systems
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Loh, TY (Mr Tzu Yang Loh)
UTAS Author:Bose, N (Professor Neil Bose)
UTAS Author:Tenekedjiev, K (Professor Kiril Tenekedjiev)
ID Code:136004
Year Published:2020
Web of Science® Times Cited:8
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2019-11-25
Last Modified:2021-08-04
Downloads:8 View Download Statistics

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