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Multi-attribute decision-making method for prioritizing maritime traffic safety influencing factors of autonomous ships' maneuvering decisions using grey and fuzzy theories
Xue, J.; van Gelder, P.H.A.J.M.; Reniers, G.; Papadimitriou, E.; Wu, C. (2019). Multi-attribute decision-making method for prioritizing maritime traffic safety influencing factors of autonomous ships' maneuvering decisions using grey and fuzzy theories. Safety Science 120: 323-340. https://dx.doi.org/10.1016/j.ssci.2019.07.019
In: Safety Science. Elsevier. ISSN 0925-7535; e-ISSN 1879-1042, more
Peer reviewed article  

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Keyword
    Marine/Coastal
Author keywords
    Maritime safety; Grey relational analysis; Fuzzy logic; Autonomousships; Decision-making; Quantitative assessment

Authors  Top 
  • Xue, J.
  • van Gelder, P.H.A.J.M., more
  • Reniers, G., more
  • Papadimitriou, E.
  • Wu, C.

Abstract
    Ship maneuvering decisions are influenced by several factors, and it is essential to prioritize the main influencing factors for efficient selection of the corresponding maneuvering decisions. Meanwhile, the autonomous ship maneuvering decision-making influencing factors constitute a typical grey system, which is suitable for research by grey relational analysis. Furthermore, in the fuzzy approach, linguistic assessment of factors is evaluated to obtain priorities numbers. Therefore, this study mainly focuses on the concept of human-like maneuvering for autonomous ships. Based on experimental data of experienced seafarers and using a simulation platform under the scenario of the Shanghai Waigaoqiao wharf, an inference model utilizing grey and fuzzy theories is proposed. The proposed model combined with expert linguistic terms in order to select the ship maneuvering decisionmaking main influencing factors from multi-source influencing factors (in overall and separated categories of natural environment, ship motion, force parameters, draft, and position), and to study the decision-making prioritization for maritime traffic safety for specific ship maneuvering scenarios. This method can prioritize the main factors which affect maneuvering decisions as well as guide an autonomous ship-assisted or automatic maneuvering evaluation system for the research of human-like maneuvering behavior. This study provides a new perspective on the identification of main ship maneuvering decision-making influencing factors in theory and in practice. It can be utilized for better decision-making concerning maritime traffic safety of autonomous ship maneuvering, which in turn makes shipping safer and promote the application and spreading of autonomous ships.

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