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The University of Southampton
Centre for Risk Research

Graphical Probabilistic Models for Autonomous Underwater Vehicles Risk Estimation Event

Dr Mario Brito
13:00 - 14:00
10 November 2015
Room 1003 Building 58 Highfield Campus University of Southampton

For more information regarding this event, please email Dr Ian G.J. Dawson at .

Event details

Autonomous Underwater Vehicles (AUVs) are effective platforms for science research and monitoring, and for military and commercial data-gathering purposes. However, there is an inevitable risk of loss during any mission. Quantifying the risk of loss is complex, due to the combination of vehicle reliability and environmental factors, and cannot be determined through analytical means alone. An alternative approach – formal expert judgment – is a time-consuming process; consequently a method is needed to broaden the applicability of judgments beyond the narrow confines of an elicitation for a defined environment. We propose and explore a solution founded on Graphical Probability Models (GPMs), where the results of the expert judgment elicitation are taken as the initial prior probability of loss due to failure. The network topology captures the causal effects of the environment separately on the vehicle and on the support platform, and combines these to produce an updated probability of loss due to failure. An extended version of the Kaplan–Meier estimator is then used to update the mission risk profile with travelled distance. Sensitivity analysis of the BBN is presented and a case study of Autosub3 AUV deployment in the Amundsen Sea is discussed in detail. Dr Brito is a Lecturer in Risk Analysis and Risk Management at Southampton Business School. He was formerly Head of Risk for the Marine Autonomous Underwater Vehicle group at the National Oceanographic Centre (NOC) in Southampton. At NOC, Dr Brito had been responsible for analysing the risk of losing unmanned underwater vehicles in some of the world’s most dangerous locations, including the Arctic and Antarctica. His role involved assessing and calculating the risk of vehicle failure and environmental damage, and working to ensure that innovation was not stifled so that state-of-the-art technologies could be deployed to gather important new evidence about the dynamic features of the world’s oceans.

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