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A System For Route Optimization In Ice-covered Waters

机译:冰覆水域航线优化系统

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摘要

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.
机译:关于冰的信息对于在冰雪覆盖的海域中导航是必不可少的。对于在冰上长途跋涉的船只,值得规划航线,以减少油耗和航行时间,以及减少进入危险区域或陷入冰中的风险。除船上观察外,还有许多海员可用的数据源,例如卫星图像,冰模型数据,天气观察和预报。但是,人在规划路线时很难考虑所有随时间变化的数据参数。在本文中,提出了一种用于优化冰原路径的原型系统。该系统集成了最先进的制冰模型,船舶运输模型和最终用户系统,作为航线优化工具,用于在冰雪覆盖的水域中航行的船只。该系统最近已在波罗的海商船上得到验证,并且已使用AIS数据对系统的性能进行了统计分析。根据AIS数据分析,长途路线(90-650公里)的估计渡越时间的平均相对误差为0.144 [s / s],标准偏差为0.147 [s / s],而0.018 [s / s] 50公里路段的标准偏差为0.193 [s / s]。

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