Human error in autonomous underwater vehicle deployment: a system dynamics approach

• Published in: Risk Analysis
• Main Authors: Loh, TY, Brito, MP, Bose, N, Xu, J, Tenekedjiev, K
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley-Blackwell Publishing Ltd 2020
• Subjects: Engineering; Maritime engineering; Ocean engineering; Antarctic; The Antarctic; Antarc*
• Online Access: https://doi.org/10.1111/risa.13467; http://www.ncbi.nlm.nih.gov/pubmed/32144834; http://ecite.utas.edu.au/141973

The use of autonomous underwater vehicles (AUVs) for various applications have grown with maturing technology and improved accessibility. 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 extremities in the Antarctic. A thorough analysis of risks is therefore crucial for formulating effective risk control policies and achieving a lower risk of loss. Existing risk analysis approaches focused predominantly on the technical aspects, as well as identifying static cause and effect relationships in the chain of events leading to AUV loss. Comparatively, the complex interrelationships between risk variables and other aspects of risk such as human errors have received much lesser attention. In this article, a systems-based risk analysis framework facilitated by system dynamics methodology is proposed to overcome existing shortfalls. To demonstrate usefulness of the framework, it is applied on an actual AUV program to examine the occurrence of human error during Antarctic deployment. Simulation of the resultant risk model showed an overall decline in human error incident rate with the increase in experience of the AUV team. Scenario analysis based on the example provided policy recommendations in areas of training, practice runs, recruitment policy, and setting of risk tolerance level. The proposed risk analysis framework is pragmatically useful for risk analysis of future AUV programs to ensure the sustainability of operations, facilitating both better control and monitoring of risk.