基于改进A*算法的船舶航向航速协同优化方法

崔金龙,李元奎,索基源,杨雪锋

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大连海事大学学报 ›› 2022, Vol. 48 ›› Issue (4) : 29-37. DOI: 10.16411/j.cnki.issn1006-7736.2022.04.004
交通运输工程

基于改进A*算法的船舶航向航速协同优化方法

  • 崔金龙1,李元奎*1,索基源1,杨雪锋2
作者信息 +

Collaborative optimization method of ship course and speed based on improved A* algorithm

  • CUI Jin-long1,LI Yuan-kui*1,SUO Ji-yuan1,YANG Xue-feng2
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摘要

基于航海实际改进A*算法,实现了对船舶全航程的航向航速协同优化,可以通过合理配置航线和航速,保证船舶更加安全、节能地完成航行任务。首先,利用气象水文数据集建立具有复杂气象的动态海域模型,基于船舶实际情况划定船舶的可航行区域和禁航区;其次,将航速优化加入优化环节中,以船舶λ置、航速以及航行时刻为优化变量,通过标准化方法,以航行油耗与航行时间综合评估航行成本,构建了船舶航向和航速协同优化模型;最后,为符合较低航行油耗和时间的航行任务,通过改进A*算法的评价函数和运行步骤对模型进行仿真和求解。对北太平洋区域的航行规划仿真结果表明:与大圆航线相比,本文提出的方法能够保障船舶在有效避离大风浪区域的同时降低油耗,航行决策更加灵活,能够适应复杂多变的远洋航行任务。

Abstract

Based on the navigation practice, the A* algorithm was improved to achieve the coordinated optimization of the course and speed of the ship throughout the voyage, which can ensure that the ship can complete the navigation task more safely and energyefficient by reasonably configuring the route and speed. Firstly, a dynamic sea area model with complex weather was established by using meteorological and hydrological data sets, and the navigable area and restricted area of the ship were delineated based on the actual situation of the ship. Secondly, speed optimization was added to the optimization link. With ship position, speed and sailing time as the optimization variables, the navigation cost was comprehensively evaluated by the standardized method based on the navigation fuel consumption and sailing time, and a collaborative optimization model of ship course and speed was constructed. Finally, in order to meet the navigation task with low fuel consumption and time, the model was simulated and solved by improving the evaluation function and operation steps of A* algorithm. The simulation results of navigation planning in the North Pacific region show that, compared with the big circle route, the proposed method can ensure that ships can effectively avoid the big wind and waves while reducing fuel consumption, and navigation decisions are more flexible, and can adapt to complex and changeable ocean navigation tasks.

关键词

智能航行 / 航线优化 / 航速优化 / A*算法

Key words

Intelligent navigation / route optimization / speed optimization / A* algorithm

引用本文

导出引用
崔金龙,李元奎,索基源,杨雪锋. 基于改进A*算法的船舶航向航速协同优化方法[J]. 大连海事大学学报, 2022, 48(4): 29-37. https://doi.org/10.16411/j.cnki.issn1006-7736.2022.04.004
CUI Jin-long,LI Yuan-kui,SUO Ji-yuan,YANG Xue-feng. Collaborative optimization method of ship course and speed based on improved A* algorithm[J]. Journal of Dalian Maritime University, 2022, 48(4): 29-37. https://doi.org/10.16411/j.cnki.issn1006-7736.2022.04.004

基金

交通安全应急信息技术国家工程实验室开放基金资助项目(YW170301-05);重庆市自然科学基金资助项目(cstc2019jcyj-msxmX0729);中央高校基本科研业务费专项资金资助项目(3132022147)
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