000010722 001__ 10722
000010722 005__ 20240627122958.0
000010722 0247_ $$2doi$$a10.24868/10722
000010722 245__ $$aConstructing Knowledge Maps for Situation Awareness of Maritime Autonomous Surface Ships
000010722 269__ $$a2022-10-13
000010722 336__ $$aConference Proceedings
000010722 520__ $$aMany projects related to maritime autonomous surface ships (MASS) have been proceeding to date, which promotes the commercialization of MASS. It is anticipated that there will be ships with different degrees of autonomy coexisting in a waterborne transport system (WTS) in the near future, forming a mixed waterborne transport system (MWTS). To ensure navigational safety, the ship needs to be well aware of the situation in real time, i.e. be able to exhibit situation awareness. The inconsistency of comprehension within SA of the same situation could occur in the MWTS, leading to a potentially dangerous situation. 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. The method realizes four capabilities of SA to satisfy relevant requirements in maritime domain: a general map, risk assessment enrichment, temporal and dynamic features, as well as a supplement of domain knowledge. 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 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. The method can be applied to MASS for the information fusion of situation awareness, which also can be supplied to Maritime Safety and Security (MSS) organizations for traffic surveillance of WTS.
000010722 542__ $$fCC-BY
000010722 6531_ $$aMASS
000010722 6531_ $$aMWTS
000010722 6531_ $$aSituation Awareness
000010722 6531_ $$aKnowledge Integration
000010722 6531_ $$aOntology
000010722 7001_ $$aSong, R$$uDelft University of Technology
000010722 7001_ $$aPapadimitriou, E$$uDelft University of Technology
000010722 7001_ $$aNegenborn, R$$uDelft University of Technology
000010722 7001_ $$avan Gelder, P$$uDelft University of Technology
000010722 773__ $$tConference Proceedings of iSCSS
000010722 773__ $$jiSCSS 2022
000010722 85641 $$uhttps://www.imarest.org/events/category/categories/imarest-event/international-ship-control-systems-symposium-2022$$yConference website
000010722 8564_ $$9a56d4c08-d73d-444a-952a-fd01da1f299b$$s7888098$$uhttps://library.imarest.org/record/10722/files/10722.pdf
000010722 980__ $$aConference Proceedings