skip to main content
10.1145/3597512.3597521acmotherconferencesArticle/Chapter ViewAbstractPublication PagestasConference Proceedingsconference-collections
extended-abstract

Investigating decision-making in the operation of Maritime Autonomous Surface Ships using the Schema World Action Research Method

Authors Info & Claims
Published:11 July 2023Publication History

ABSTRACT

Maritime Autonomous Surface Ships (MASS) are expected to improve safety by removing the need for onboard operators so that they can operate uncrewed. However, this may make decision-making for MASS operators more difficult as they will be relocated from onboard to a Remote Control Centre (RCC), therefore they will lack proximity to the ship they are operating and may have reduced situational awareness. In addition, there will potentially be issues surrounding supporting the operator to develop appropriate levels of trust in the automated systems onboard the MASS, which may also influence how MASS operators will make decisions. The Schema World Action Research Method (SWARM) will be used to explore the decision-making process of MASS operators and the challenges associated with operating uncrewed platforms, including questions on how trust may influence the operators’ decision-making processes. The results of the analysis will be used to suggest design requirements for future MASS systems to better support an operator's decision-making process by ensuring that they have the necessary information to make informed decisions.

References

  1. Ahvenjärvi, S., The human element and autonomous ships. TransNav: International Journal on Marine Navigation and Safety of Sea Transportation, 2016. 10(3).Google ScholarGoogle ScholarCross RefCross Ref
  2. Mallam, S.C., S. Nazir, and A. Sharma, The human element in future Maritime Operations – perceived impact of autonomous shipping. Ergonomics, 2020. 63(3): p. 334-345.Google ScholarGoogle Scholar
  3. International Maritime Organisation, Report of the Maritime Safety Committee on its 103rd session, M.S. Committee, Editor. 2021.Google ScholarGoogle Scholar
  4. Maritime UK, Maritime Autonomous Ship Systems (MASS) UK Industry Conduct Principles and Code of Practice: A Voluntary Code Version 4, M. UK, Editor. 2020: London, UK.Google ScholarGoogle Scholar
  5. Dybvik, H., E. Veitch, and M. Steinert, EXPLORING CHALLENGES WITH DESIGNING AND DEVELOPING SHORE CONTROL CENTERS (SCC) FOR AUTONOMOUS SHIPS. Proceedings of the Design Society: DESIGN Conference, 2020. 1: p. 847-856.Google ScholarGoogle ScholarCross RefCross Ref
  6. Hoem, Å., , At least as safe as manned shipping? Autonomous shipping, safety and “human error”. 2018.Google ScholarGoogle Scholar
  7. Ramos, M., I. Utne, and A. Mosleh, Collision avoidance on maritime autonomous surface ships: Operators' tasks and human failure events. Safety Science, 2019. 116: p. 33-44.Google ScholarGoogle Scholar
  8. Størkersen, K.V., Safety management in remotely controlled vessel operations. Marine Policy, 2021. 130: p. 104349.Google ScholarGoogle Scholar
  9. Man, Y., M. Lundh, and T. Porathe, Seeking harmony in shore-based unmanned ship handling: From the perspective of human factors, what is the difference we need to focus on from being onboard to onshore?, in Human Factors in Transportation: Social and Technological Evolution Across Maritime, Road, Rail, and Aviation Domains. 2016. p. 61-70.Google ScholarGoogle Scholar
  10. Wahlström, M., , Human Factors Challenges in Unmanned Ship Operations – Insights from Other Domains. Procedia Manufacturing, 2015. 3: p. 1038 – 1045.Google ScholarGoogle Scholar
  11. Dreyer, L. and H. Oltedal. Safety Challenges for Maritime Autonomous Surface Ships: A Systematic Review. in The Third Conference on Maritime Human Factors. Haugesund. 2019.Google ScholarGoogle Scholar
  12. Mackinnon, S.N., Command and control of unmanned vessels: Keeping shore based operators in-the-loop. in 18th International Conference on Ships and Shipping Research, NAV 2015. 2015.Google ScholarGoogle Scholar
  13. Plant, K.L. and N.A. Stanton, The development of the Schema-Action-World (SAW) taxonomy for understanding decision making in aeronautical critical incidents. Safety Science, 2016. 99: p. 23-35.Google ScholarGoogle Scholar
  14. Parnell, K.J., , Trustworthy UAV Relationships: Applying the Schema Action World Taxonomy to UAVs and UAV Swarm Operations. International Journal of Human–Computer Interaction, 2022: p. 1-17.Google ScholarGoogle Scholar
  15. Neisser, U., Cognition and Reality. 1976, San Fransico: W.H. Freeman and Company.Google ScholarGoogle Scholar
  16. Simpson, P.A., Naturalistic decision making in aviation environments. 2001.Google ScholarGoogle Scholar
  17. Jenkins, D.P., , Using the decision-ladder to add a formative element to naturalistic decision-making research. International Journal of Human-Computer Interaction, 2010. 26(2-3): p. 132-146.Google ScholarGoogle Scholar
  18. Strauch, B., Decision Errors and Accidents:Applying Naturalistic Decision Making to Accident Investigations. Journal of Cognitive Engineering and Decision Making, 2016. 10(3): p. 281-290.Google ScholarGoogle Scholar
  19. Plant, K.L. and N.A. Stanton, Why did the pilots shut down the wrong engine? Explaining errors in context using Schema Theory and the Perceptual Cycle Model. Safety Science, 2012. 50(2): p. 300-315.Google ScholarGoogle Scholar
  20. Banks, V.A., , Using the Perceptual Cycle Model and Schema World Action Research Method to generate design requirements for new avionic systems. Human Factors and Ergonomics in Manufacturing & Service Industries, 2021. 31(1): p. 66-75.Google ScholarGoogle Scholar
  21. Parnell, K.J., , Generating Design Requirements for Flight Deck Applications: Applying the Perceptual Cycle Model to Engine Failures on Take-off. International Journal of Human–Computer Interaction, 2021. 37(7): p. 611-629.Google ScholarGoogle Scholar

Index Terms

  1. Investigating decision-making in the operation of Maritime Autonomous Surface Ships using the Schema World Action Research Method
          Index terms have been assigned to the content through auto-classification.

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in
          • Published in

            cover image ACM Other conferences
            TAS '23: Proceedings of the First International Symposium on Trustworthy Autonomous Systems
            July 2023
            426 pages
            ISBN:9798400707346
            DOI:10.1145/3597512

            Copyright © 2023 Owner/Author

            Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 11 July 2023

            Check for updates

            Qualifiers

            • extended-abstract
            • Research
            • Refereed limited
          • Article Metrics

            • Downloads (Last 12 months)32
            • Downloads (Last 6 weeks)6

            Other Metrics

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader

          HTML Format

          View this article in HTML Format .

          View HTML Format