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  4. Dynamic 'Standing Orders' for Autonomous Navigation System by means of Machine Learning
 
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Dynamic 'Standing Orders' for Autonomous Navigation System by means of Machine Learning

Publikationstyp
Conference Paper
Date Issued
2019-11
Sprache
English
Author(s)
Scheidweiler, Tina 
Burmeister, Hans-Christoph 
Hübner, Sören
Jahn, Carlos  orcid-logo
TORE-URI
https://hdl.handle.net/11420/42470
Journal
Journal of physics. Conference Series  
Volume
1357
Article Number
012046
Citation
International Maritime and Port Technology and Development Conference (MTEC 2019) and International Conference on Maritime Autonomous Surface Ships 13–14 November 2019, Trondheim, Norway, art. no. 012046 (2019)
Contribution to Conference
International Maritime and Port Technology and Development Conference, MTEC 2019  
2nd International Conference on Maritime Autonomous Surface Ships, ICMASS 2019  
Publisher DOI
10.1088/1742-6596/1357/1/012046
Scopus ID
2-s2.0-85076681591
Globalisation and new environmental legislations lead to a rising need for new technological developments for the shipping industry, espacially creating smart ports and smart waterways. Thus, Maritime Autonomus Surface Ships (MASS) are on the horizon. In order to be able to operate safely in the presence of other vessels, a module that dynamically determines action ranges for avoidance manoeuvres based on machine learning algorithms will be developed. Using historical AIS data, which provide ship's dynamic as well as static and voyage related data, ship trajectories and thus historical encounter situations of ships are extracted. Using k-means clustering, navigational behaviour of the vessels during an encounter situation can be examined and predicted for future encounter situations.
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