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首页> 外文会议>IEEE International Conference on Industrial Engineering and Engineering Management >Vessel speed analytics using satellite-based ship position data
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Vessel speed analytics using satellite-based ship position data

机译：使用基于卫星的船舶位置数据进行船速分析

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In the maritime supply chain, sailing speed is a key variable governing ship-to-air emissions and the profitability of vessels. While there can be substantial economic gains to be had from dynamic speed optimization, real-life constraints such as weather conditions, contractual limitations and supply chain considerations may govern the speed choice in practice. The increasing availability of high-frequency ship positions and vessel speeds reported by the terrestrial and satellite-based Automated Identification System (AIS) enables formal empirical testing of the determinants of vessel speed. We use a panel data set of nearly 62,000 weekly average speed observations for a fleet of 607 Very Large Crude oil Carriers (VLCCs) during 2013 - 2015 to estimate a multiple regression model with technical, operational and macro-economic variables. We find that macroeconomic variables have a marginal influence only on ballast speeds, while laden speeds are influenced mainly by whether the operator is also the cargo owner.
机译：在海上供应链中，航行速度是控制船对空排放量和船舶获利能力的关键变量。尽管动态速度优化可以带来可观的经济收益，但实际操作中的限制因素（例如天气条件，合同限制和供应链考虑因素）可能会在实践中控制速度选择。地面和基于卫星的自动识别系统（AIS）报告的高频船位和船速的可用性不断提高，可以对船速的决定因素进行正式的经验检验。在2013年至2015年期间，我们使用607个超大型原油运输船队（VLCC）的每周平均速度观测值近62,000的面板数据集，以估算具有技术，运营和宏观经济变量的多元回归模型。我们发现，宏观经济变量仅对压载速度有边际影响，而满载速度主要受操作者是否也是货物所有人的影响。

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