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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Formal expression of ship behavior is the basis for developing autonomous navigation systems, which supports the scene recognition, the intention inference, and the rule-compliant actions of the systems. The Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) offers experience-based expressions of ship behavior for human beings, helping the humans recognize the scene, infer the intention, and choose rule-compliant actions. However, it is still a challenge to teach a machine to interpret the COLREGs. This paper proposed an ontological ship behavior model based on the COLREGs using knowledge graph techniques, which aims at helping the machine interpret the COLREGs rules. In this paper, the ship is seen as a temporal-spatial object and its behavior is described as the change of object elements in time spatial scales by using Resource Description Framework (RDF), function mapping, and set expression methods. To demonstrate the proposed method, the Narrow Channel article (Rule 9) from COLREGs is introduced, and the ship objects and the ship behavior expression based on Rule 9 are shown. In brief, this paper lays a theoretical foundation for further constructing the ship behavior knowledge graph from COLREGs, which is helpful for the complete machine reasoning of ship behavior knowledge in the future.

Details

Title
Ontological Ship Behavior Modeling Based on COLREGs for Knowledge Reasoning
Author
Zhong, Shubin 1   VIAFID ORCID Logo  ; Wen, Yuanqiao 2 ; Huang, Yamin 2   VIAFID ORCID Logo  ; Cheng, Xiaodong 2 ; Huang, Liang 2   VIAFID ORCID Logo 

 School of Navigation, Wuhan University of Technology, Wuhan 430063, China; [email protected] 
 Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China; [email protected] (Y.W.); [email protected] (X.C.); [email protected] (L.H.); National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China 
First page
203
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
20771312
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2632829776
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.