Risk-informed collision avoidance system design for maritime autonomous surface ships

Paul Lee, Gerasimos Theotokatos, Evangelos Boulougouris, Victor Bolbot

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
82 Downloads (Pure)

Abstract

The maritime industry is paving the way towards developing Maritime Autonomous Surface Ships (MASSs) through the adoption of key enabling technologies for safety-critical operations, which are associated with new challenges, especially at their early design phase. This study aims to develop a methodology to conduct the risk-informed design for the Collision Avoidance System (CAS) of MASSs. Pertinent regulatory instruments are reviewed to identify functional and system requirements and develop a baseline CAS configuration at the component level. Quantitative Fault Tree Analysis is performed to derive risk metrics, such as probability of failure, Importance measures, and Minimal Cut Sets, whereas criticality analysis is conducted to recommend risk-reducing measures. A Short Sea Shipping case study is investigated considering four operating modes based on various weather and illumination conditions. Results demonstrate that the developed Fault Tree diagram provides a robust representation of the CAS failure. The most critical components are found to be related to the Intention Communication and Situation Awareness Systems, the redundancy of which leads to 91% reduction of the CAS probability of failure. This study contributes towards the risk-informed design of safety-critical systems required for the development of MASSs.
Original languageEnglish
Article number113750
Number of pages20
JournalOcean Engineering
Volume279
DOIs
Publication statusPublished - 1 Jul 2023
MoE publication typeA1 Journal article-refereed

Keywords

  • Maritime Autonomous Surface Ship
  • Collision Avoidance System
  • Quantitative Fault Tree Analysis
  • Risk analysis
  • Risk metrics
  • Risk-informed design

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