中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (7): 90-97.doi: 10.16265/j.cnki.issn1003-3033.2023.07.2046

• 安全工程技术 • 上一篇    下一篇

多碍航物水域救援船路径规划方法

刘钊1,2,3(), 罗辰汉1,2, 张明阳4   

  1. 1 武汉理工大学 航运学院,湖北 武汉 430063
    2 武汉理工大学 水路交通控制全国重点实验室,湖北 武汉 430063
    3 内河航运技术湖北省重点实验室,湖北 武汉 430063
    4 阿尔托大学 工程学院,芬兰 爱斯堡 20110
  • 收稿日期:2023-02-21 修回日期:2023-05-14 出版日期:2023-07-28
  • 作者简介:

    刘钊 (1986—),男,河南周口人,博士,副教授,主要从事群船智慧挖掘与应用、船舶智能组织与调度、船舶风险计算与自主航行方面的研究。E-mail:

  • 基金资助:
    国家自然科学基金(52171351)

Path planning method of rescue ships in waters with multiple obstacles

LIU Zhao1,2,3(), LUO Chenhan1,2, ZHANG Mingyang4   

  1. 1 School of Navigation, Wuhan University of Technology, Wuhan Hubei 430063, China
    2 State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan Hubei 430063, China
    3 Hubei Key Laboratory of Inland Shipping Technology, Wuhan Hubei 430063, China
    4 School of Engineering, Aalto University, Espoo 20110, Finland
  • Received:2023-02-21 Revised:2023-05-14 Published:2023-07-28

摘要:

为提升救援船在复杂环境中的适用性,基于安全距离约束法和改进蚁群算法,提出一种救援船路径规划方法。首先,根据救援船的初始位置和目标位置确定目标水域范围,运用栅格法将水域环境划分为可航水域和不可航水域,并通过安全距离约束的方法保障救援船与碍航物间的最小安全距离;然后,优化信息素初始浓度、启发因子和挥发因子,设置期望值启发因子和距离启发函数,改进蚁群算法,提升算法搜索的目的性和快速性,并将其运用于栅格地图中,规划救援船的路径;最后,选取舟山群岛附近水域作为试验水域,以东海救102救援船为试验船舶进行验证。结果表明:与传统方法相比,所提出的救援船路径规划方法收敛速度更快,且给出的路径长度更短,转向点更少,运行时间更短;该方法能够克服救援船路径规划过程中面临的收敛速度慢和局部最优问题,增强鲁棒性。

关键词: 多碍航物水域, 救援船, 路径规划, 改进蚁群算法, 最小安全距离

Abstract:

A path planning method for rescuing ships was proposed to address the challenges associated with navigating in waters containing numerous obstacles, while ensuring safety and efficiency. The proposed method incorporated the safe distance constraint approach and an improved ant colony algorithm to enhance the applicability of rescue ships in complex environments. The method involved determining the target water area range based on the initial and target positions of the rescue ship, employing a grid-based approach to divide the operational environment into navigable and non-navigable areas, and enforcing a minimum safe distance between the rescue ship and obstacles through safety distance constraints. To further improve the efficiency of the path planning process, the ant colony algorithm was enhanced by optimizing the initial concentration of pheromone, heuristic factor and volatilization factor. Additionally, the expected value heuristic factor and distance heuristic function were introduced to enhance the search purpose and speed of the improved ant colony algorithm. The proposed method was applied to a grid map to plan the path of the rescue ship. The waters near the Zhoushan Islands were selected as the experimental waters, and the Donghai Rescue 102 rescue ship was used as the experimental vessel for verification. Experimental results demonstrate that the proposed path planning method exhibits faster convergence compared to the comparison model, resulting in shorter path lengths, fewer turning points and reduced running time. This method overcomes the challenges of slow convergence speed and local optimization in the path planning of rescue ships, thereby enhancing robustness.

Key words: waters with multiple navigational obstacles, rescue ship, path planning, improved ant colony optimization algorithms, minimum safe distance