A system for route optimization in ice-covered waters
Information about ice is indispensable to navigation in ice-covered sea areas. For vessels traveling long distances in ice, it is worth planning routes that will reduce fuel consumption and travel time, as well as the risk of ending up in hazardous areas or getting stuck in the ice. In addition to o...
Published in: | Cold Regions Science and Technology |
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Language: | English |
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2009
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Online Access: | https://cris.vtt.fi/en/publications/a2677d53-148e-4f84-ab53-b1326bb39de7 https://doi.org/10.1016/j.coldregions.2008.07.003 |
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ftvttcrispub:oai:cris.vtt.fi:publications/a2677d53-148e-4f84-ab53-b1326bb39de7 2024-09-15T18:35:16+00:00 A system for route optimization in ice-covered waters Kotovirta, Ville Jalonen, R. Axell, L. Riska, K. Berglund, Robin 2009 https://cris.vtt.fi/en/publications/a2677d53-148e-4f84-ab53-b1326bb39de7 https://doi.org/10.1016/j.coldregions.2008.07.003 eng eng https://cris.vtt.fi/en/publications/a2677d53-148e-4f84-ab53-b1326bb39de7 info:eu-repo/semantics/closedAccess Kotovirta , V , Jalonen , R , Axell , L , Riska , K & Berglund , R 2009 , ' A system for route optimization in ice-covered waters ' , Cold Regions Science and Technology , vol. 55 , no. 1 , pp. 52-62 . https://doi.org/10.1016/j.coldregions.2008.07.003 Baltic Sea ice fields mathematical models modeling optimization sea ice article 2009 ftvttcrispub https://doi.org/10.1016/j.coldregions.2008.07.003 2024-08-21T23:33:26Z Information about ice is indispensable to navigation in ice-covered sea areas. For vessels traveling long distances in ice, it is worth planning routes that will reduce fuel consumption and travel time, as well as the risk of ending up in hazardous areas or getting stuck in the ice. In addition to observations on board, there is a multitude of data sources available for seafarers like satellite images, ice model data, weather observations and forecasts. However, it is difficult for a human to take into consideration all the time-varying data parameters when planning a route. In this paper, a prototype system for optimizing routes through the ice field is presented. The system integrates state-of-the-art ice modeling, ship transit modeling, and an end-user system as a route optimization tool for vessels navigating in ice-covered waters. The system has recently been validated on board merchant vessels in the Baltic Sea, and the system's performance has been analyzed statistically using AIS data. Based on the AIS data analysis the mean relative error of the estimated transit time was 0.144 [s/s] with a standard deviation of 0.147 [s/s] for long routes (90-650 km), and 0.018 [s/s] with standard deviation of 0.193 [s/s] for 50 km route segments. Article in Journal/Newspaper Sea ice ice covered waters VTT's Research Information Portal Cold Regions Science and Technology 55 1 52 62 |
institution |
Open Polar |
collection |
VTT's Research Information Portal |
op_collection_id |
ftvttcrispub |
language |
English |
topic |
Baltic Sea ice fields mathematical models modeling optimization sea ice |
spellingShingle |
Baltic Sea ice fields mathematical models modeling optimization sea ice Kotovirta, Ville Jalonen, R. Axell, L. Riska, K. Berglund, Robin A system for route optimization in ice-covered waters |
topic_facet |
Baltic Sea ice fields mathematical models modeling optimization sea ice |
description |
Information about ice is indispensable to navigation in ice-covered sea areas. For vessels traveling long distances in ice, it is worth planning routes that will reduce fuel consumption and travel time, as well as the risk of ending up in hazardous areas or getting stuck in the ice. In addition to observations on board, there is a multitude of data sources available for seafarers like satellite images, ice model data, weather observations and forecasts. However, it is difficult for a human to take into consideration all the time-varying data parameters when planning a route. In this paper, a prototype system for optimizing routes through the ice field is presented. The system integrates state-of-the-art ice modeling, ship transit modeling, and an end-user system as a route optimization tool for vessels navigating in ice-covered waters. The system has recently been validated on board merchant vessels in the Baltic Sea, and the system's performance has been analyzed statistically using AIS data. Based on the AIS data analysis the mean relative error of the estimated transit time was 0.144 [s/s] with a standard deviation of 0.147 [s/s] for long routes (90-650 km), and 0.018 [s/s] with standard deviation of 0.193 [s/s] for 50 km route segments. |
format |
Article in Journal/Newspaper |
author |
Kotovirta, Ville Jalonen, R. Axell, L. Riska, K. Berglund, Robin |
author_facet |
Kotovirta, Ville Jalonen, R. Axell, L. Riska, K. Berglund, Robin |
author_sort |
Kotovirta, Ville |
title |
A system for route optimization in ice-covered waters |
title_short |
A system for route optimization in ice-covered waters |
title_full |
A system for route optimization in ice-covered waters |
title_fullStr |
A system for route optimization in ice-covered waters |
title_full_unstemmed |
A system for route optimization in ice-covered waters |
title_sort |
system for route optimization in ice-covered waters |
publishDate |
2009 |
url |
https://cris.vtt.fi/en/publications/a2677d53-148e-4f84-ab53-b1326bb39de7 https://doi.org/10.1016/j.coldregions.2008.07.003 |
genre |
Sea ice ice covered waters |
genre_facet |
Sea ice ice covered waters |
op_source |
Kotovirta , V , Jalonen , R , Axell , L , Riska , K & Berglund , R 2009 , ' A system for route optimization in ice-covered waters ' , Cold Regions Science and Technology , vol. 55 , no. 1 , pp. 52-62 . https://doi.org/10.1016/j.coldregions.2008.07.003 |
op_relation |
https://cris.vtt.fi/en/publications/a2677d53-148e-4f84-ab53-b1326bb39de7 |
op_rights |
info:eu-repo/semantics/closedAccess |
op_doi |
https://doi.org/10.1016/j.coldregions.2008.07.003 |
container_title |
Cold Regions Science and Technology |
container_volume |
55 |
container_issue |
1 |
container_start_page |
52 |
op_container_end_page |
62 |
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1810478300649226240 |