A Review of Risk Analysis Research for the Operations of Autonomous Underwater Vehicles
A Review of Risk Analysis Research for the Operations of Autonomous Underwater Vehicles
Risk analysis for autonomous underwater vehicles (AUVs) is essential to assist decision making for safer operations. This study aims to provide a systematic review of risk analysis research to enhance the safety performance of AUVs. Forty-two domain articles were retrieved and analyzed. Critical risk factors and causal relationships of AUV operations were identified. A comparative analysis of evolving methods and models was performed by categorizing them as qualitative, semi-quantitative, and quantitative. Future trends of research in this field were also outlined. The study observes that as AUV technologies gradually mature, environmental factors, human factors, and their interactive impacts are gathering more attention. Quantitative risk analysis methods have recently played a key role in improving the accuracy and handling the uncertainties of risk estimation. The study recommends devoting efforts to dynamic risk analysis, addressing limited historical data, intelligent risk analysis, and multi-vehicles risk analysis for future works. This study is expected to help AUV stakeholders gain comprehensive insights into fundamental concepts and evolving methods for risk analysis of AUVs. At the same time, it is expected to highlight future directions to bridge existing gaps.
AUV safety, Autonomous underwater vehicles, Literature review, Marine safety, Risk analysis
1
Chen, Xi
8bdb9873-52cb-4688-8cae-b4da945e0662
Bose, Neil
37b8d6e4-fd93-4bbe-827c-f060e0ce0851
Brito, Mario
82e798e7-e032-4841-992e-81c6f13a9e6c
Khan, Faisal
e3810728-8747-4b3c-aa95-eae12d7e1759
Thanyamanta, Bo
55d6d540-1996-434b-a0c1-5d16980d2561
Zou, Ting
98db3c2e-72a9-479d-8af9-a44dc89f13f1
December 2021
Chen, Xi
8bdb9873-52cb-4688-8cae-b4da945e0662
Bose, Neil
37b8d6e4-fd93-4bbe-827c-f060e0ce0851
Brito, Mario
82e798e7-e032-4841-992e-81c6f13a9e6c
Khan, Faisal
e3810728-8747-4b3c-aa95-eae12d7e1759
Thanyamanta, Bo
55d6d540-1996-434b-a0c1-5d16980d2561
Zou, Ting
98db3c2e-72a9-479d-8af9-a44dc89f13f1
Chen, Xi, Bose, Neil, Brito, Mario, Khan, Faisal, Thanyamanta, Bo and Zou, Ting
(2021)
A Review of Risk Analysis Research for the Operations of Autonomous Underwater Vehicles.
Reliability Engineering and System Safety, 216, , [108011].
(doi:10.1016/j.ress.2021.108011).
Abstract
Risk analysis for autonomous underwater vehicles (AUVs) is essential to assist decision making for safer operations. This study aims to provide a systematic review of risk analysis research to enhance the safety performance of AUVs. Forty-two domain articles were retrieved and analyzed. Critical risk factors and causal relationships of AUV operations were identified. A comparative analysis of evolving methods and models was performed by categorizing them as qualitative, semi-quantitative, and quantitative. Future trends of research in this field were also outlined. The study observes that as AUV technologies gradually mature, environmental factors, human factors, and their interactive impacts are gathering more attention. Quantitative risk analysis methods have recently played a key role in improving the accuracy and handling the uncertainties of risk estimation. The study recommends devoting efforts to dynamic risk analysis, addressing limited historical data, intelligent risk analysis, and multi-vehicles risk analysis for future works. This study is expected to help AUV stakeholders gain comprehensive insights into fundamental concepts and evolving methods for risk analysis of AUVs. At the same time, it is expected to highlight future directions to bridge existing gaps.
Text
A Review of Risk Analysis Research for the Operation of Autonomous Underwater Vehicles_revised_13th Jan no markup rev1
- Accepted Manuscript
More information
Accepted/In Press date: 26 August 2021
e-pub ahead of print date: 1 September 2021
Published date: December 2021
Additional Information:
Funding Information:
This work is funded by Fisheries and Oceans Canada through the Multi-partner Oil Spill Research Initiative (MPRI) 1.03: Oil Spill Reconnaissance and Delineation through Robotic Autonomous Underwater Vehicle Technology in Open and Iced Waters. Coauthor, Faisal Khan, wishes to acknowledge the financial support provided by the Canada Research Chair (Tier 1) program on Offshore Safety and Risk Engineering.
Publisher Copyright:
© 2021 Elsevier Ltd
Keywords:
AUV safety, Autonomous underwater vehicles, Literature review, Marine safety, Risk analysis
Identifiers
Local EPrints ID: 451143
URI: http://eprints.soton.ac.uk/id/eprint/451143
ISSN: 0951-8320
PURE UUID: 2716c917-c41e-49ef-95cf-ac0ac77f283f
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Date deposited: 14 Sep 2021 15:23
Last modified: 17 Mar 2024 06:49
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Contributors
Author:
Xi Chen
Author:
Neil Bose
Author:
Faisal Khan
Author:
Bo Thanyamanta
Author:
Ting Zou
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