Fraunhofer-Gesellschaft

Publica

Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Dynamic "Standing Orders" for Autonomous Navigation System by means of Machine Learning

 
: Scheidweiler, Tina; Burmeister, Hans-Christoph; Hübner, Sören; Jahn, Carlos

:
Volltext ()

Institute of Physics -IOP-, London:
International Maritime and Port Technology and Development Conference and International Conference on Maritime Autonomous Surface Ships 2019 : 13-14 November 2019, Trondheim, Norway
Bristol: IOP Publishing, 2019 (Journal of physics. Conference series 1357)
Art. 012046, 3 S.
International Maritime and Port Technology and Development Conference (MTEC) <2019, Trondheim>
International Conference on Maritime Autonomous Surface Ships (ICMASS) <2, 2019, Trondheim>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IML ()
MASS; machine learning; AIS; Collision avoidance

Abstract
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.

: http://publica.fraunhofer.de/dokumente/N-575048.html