In this study, a risk assessment model for ship collisions is proposed according to the guidelines for Formal Safety Assessment (FSA) approved by IMO in 2002. The analysis is applied to ship collisions between fishing and cargo vessels owing to their high frequency and enormous damage. Bayesian network theory for risk analysis has been applied to reveal a causal relationship on human factors. A trial evaluation of Risk Control Options (RCOs) for collisions is attempted through the calculation of the dominance index. Finally, a trial cost benefit analysis for RCOs is considered through Gross Cost of Averting Fatality (GCAF) in FSA.

Keywords:
freight & logistics services, artificial intelligence, risk management, machine learning, risk and uncertainty assessment, probability value, detection, ship collision, bayesian inference, existence probability
Subjects:
Safety, Risk Management and Decision-Making, Information Management and Systems, Risk, uncertainty, and risk assessment, Artificial intelligence
This content is only available via PDF.
2015. The Society of Naval Architects and Marine Engineers
You can access this article if you purchase or spend a download.