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Constructing Knowledge Maps for Situation Awareness of Maritime Autonomous Surface Ships

EasyChair Preprint no. 9234

11 pagesDate: November 3, 2022


Many projects related to maritime autonomous surface ships (MASS) have been proceeding to date, promoting the commercialization of MASS. It is anticipated that ships with different degrees of autonomy will coexist in a waterborne transport system (WTS) shortly, forming a mixed waterborne transport system (MWTS). To ensure navigational safety, the ship needs to be well aware of the situation in real time. As such, it is essential to unify the SA framework for MASS to eliminate the inconsistency with human operators. It is challenging but necessary for a MASS to accomplish the process of situation awareness involving perception, comprehension, and projection. Especially the part of comprehension is the core element that needs to be addressed well and enhanced further. One possible way to reach it is to integrate the information given by the perception layer, projection layer, as well as additional domain knowledge like navigational rules to conduct further analysis. Accordingly, the current paper proposes a method for knowledge integration of SA for the MASS. For that purpose, the paper takes two steps: (i) constructing a SA framework for MASS, in which the entities related to SA are classified to different categories. (ii) proposing an ontology-based SA comprehension model where the information of entities are integrated together and then the SA can be depicted for MASS in real time. A case study is provided to present how the model can be applied in maritime domain, in which a MASS is approaching a port executing its tasks. As a result, the proposed method can relate the information provided by both the perception and projection layers, and domain knowledge in the form of a knowledge graph to depict the real-time situation. The results show that the method is feasible to provide potentials to the MASS to be aware of the situation in real time considering domain knowledge.

Keyphrases: knowledge integration, mass, MWTS, Ontology, situation awareness

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Rongxin Song and Eleonora Papadimitriou and Rudy Negenborn and Pieter van Gelder},
  title = {Constructing Knowledge Maps for Situation Awareness of Maritime Autonomous Surface Ships},
  howpublished = {EasyChair Preprint no. 9234},

  year = {EasyChair, 2022}}
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