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  4. Towards an investigation of a MASS-assisted anti-grounding service through simulated nautical scenarios in a ship handling simulator
 
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Towards an investigation of a MASS-assisted anti-grounding service through simulated nautical scenarios in a ship handling simulator

Publikationstyp
Conference Paper
Date Issued
2020-11
Sprache
English
Author(s)
Schneider, Vincent Emanuel 
Constapel, Manfred  
Riordan, J.
Flannery, F.
Burmeister, Hans-Christoph 
Jahn, Carlos  orcid-logo
TORE-URI
https://hdl.handle.net/11420/42465
First published in
IOP conference series / Materials science and engineering  
Number in series
929
Article Number
012031
Citation
3rd International Conference on Maritime Autonomous Surface Ship (ICMASS 2020)
Contribution to Conference
3rd International Conference on Maritime Autonomous Surface Ship, ICMASS 2020  
Publisher DOI
10.1088/1757-899X/929/1/012031
Scopus ID
2-s2.0-85097609106
Publisher
Institute of Physics
Vessel groundings pose a major risk for maritime safety, constituting 20 percent of all incidents in the last decade. Frequent dredging and bottom mapping are resource intensive solutions currently employed, but these services cannot be maintained with the necessary frequency in all critical areas. While ships are carrying echo sounders to acquire precise and current under keel clearance data, it does not allow the vessel to react to possible deviations from the map data. Within the RoboVaaS project, a service is designed, implemented and tested in simulation. This service consists of one or more small MASS travelling ahead of a merchant vessel, collecting bathymetric data with enough lead time for the merchant vessel to react to possible threats, e.g. by course correction. This service is tested in compliance with the IMO HCD guideline in a quick approach and safe environment using a ship handling simulator. The simulator is augmented by a display system based on an ECDIS map and displaying the bathymetric data in three different scenarios. These scenarios are tested with nautical officers to collect feedback for service design and implementation with trained personnel and show the effectiveness of the chosen human machine interface.
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