Abstract
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.
Original language | English |
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Pages (from-to) | 52-62 |
Number of pages | 11 |
Journal | Cold Regions Science and Technology |
Volume | 55 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2009 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Baltic Sea
- ice fields
- mathematical models
- modeling
- optimization
- sea ice