A risk comparison framework for autonomous ships navigation

Maritime autonomous surface ships (MASS) may operate in three predefined operational modes (OM): manual, remote, or autonomous control. Determining the appropriate OM for MASS is important for operators and competent authorities that monitor and regulate maritime traffic in given areas. However, a science-based approach to this respect is currently unavailable. To assist the selection of the proper OM, this study presents a risk-based framework to compare risks in a given situation. To determine the risk level for a given OM, this framework utilizes expected failure modes (FM) related to people, organization, vessel, environment, and technology. FMs and associated accident scenarios (AS) were identified from conventional ship accidents, operating in manual control, in a coastal area in China, based on an extended 24Model. To expand these FMs to other OMs, experts’ knowledge elicitation sessions were carried out. Subsequently, a metric for navigation risk of MASS in given OMs was introduced and estimated for the expected AS, using interval-based risk prioritization numbers to convey inherent uncertainty. Finally, by ranking interval-valued metrics in the three OMs, a risk picture was obtained. The feasibility of the proposed framework for risk comparison was verified using grounding in coastal areas where accident data were collected.

• Record URL:
  https://doi.org/10.1016/j.ress.2022.108709
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0951832022003349
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09518320
• Supplemental Notes:
  • © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Fan, Cunlong
  • Montewka, Jakub
  • 0000-0002-6817-8628
  • Zhang, Di
• Publication Date: 2022-10

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: 108709
• Serial:
  • Reliability Engineering & System Safety
  • Volume: 226
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0951-8320
  • Serial URL: https://www.sciencedirect.com/journal/reliability-engineering-and-system-safety

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Groundings (Maritime crashes); Remote control; Risk analysis; Ship operations; Ship pilotage
• Geographic Terms: China
• Subject Areas: Data and Information Technology; Marine Transportation; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01855841
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 24 2022 3:05PM