TY - JOUR
T1 - Risk-informed collision avoidance system design for maritime autonomous surface ships
AU - Lee, Paul
AU - Theotokatos, Gerasimos
AU - Boulougouris, Evangelos
AU - Bolbot, Victor
PY - 2023/7/1
Y1 - 2023/7/1
N2 - 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.
AB - 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.
KW - Maritime Autonomous Surface Ship
KW - Collision Avoidance System
KW - Quantitative Fault Tree Analysis
KW - Risk analysis
KW - Risk metrics
KW - Risk-informed design
UR - https://doi.org/10.1016/j.oceaneng.2023.113750
U2 - 10.1016/j.oceaneng.2023.113750
DO - 10.1016/j.oceaneng.2023.113750
M3 - Article
SN - 0029-8018
VL - 279
JO - Ocean Engineering
JF - Ocean Engineering
M1 - 113750
ER -