为规避海洋运输环境中潜在的静态障碍风险区域，并进行平滑、动态避障，降低船舶碰撞风险，研究基于群智能优化算法的船舶最优运输路线规划方法。利用正六边形网格划分方法构建船舶运输所处海洋环境模型；建立基于群智能优化算法的运输航线规划模型，在构建的正六边形网格海洋环境中，动态规划运输避障路径，规划目标为避障过程航行距离与复航路径长度最小化，使用蜘蛛猴算法，求解满足目标函数以及约束条件的本船航行至动态避障转向点的时间、动态避障航向变动量、动态避障转向行为至复航的时间、复航时航向变动量4个规划变量，作为船舶最优运输路线规划方案，实现船舶最优运输路线规划。经测试，所研究方法在存在静态障碍、动态障碍的海况中，规划运输路线后，船舶未出现碰撞风险，且路线平滑。
To avoid potential static obstacle risk areas in the marine transportation environment, and to perform smooth and dynamic obstacle avoidance to reduce the risk of ship collision, a ship optimal transportation route planning method based on swarm intelligence optimization algorithm is studied. This method utilizes the regular hexagonal mesh division method to construct a model of the marine environment in which ships are transported; Establish a transportation route planning model based on swarm intelligence optimization algorithm, and dynamically plan the transportation obstacle avoidance path in the constructed regular hexagonal grid ocean environment. The planning objective is to minimize the navigation distance and the length of the return path during the obstacle avoidance process. Using the Spider Monkey algorithm, solve four planning variables: the time for the ship to navigate to the dynamic obstacle avoidance turning point, the dynamic obstacle avoidance heading change momentum, the time from the dynamic obstacle avoidance turning behavior to the return journey, and the heading change during the return journey, which meet the objective function and constraint conditions. These variables are used as the optimal transportation route planning scheme for ships to achieve the optimal transportation route planning. After testing, it was found that in sea conditions with static and dynamic obstacles, the research method did not pose any collision risks to ships after planning transportation routes, and the routes were smooth.
2024,46(12): 166-169 收稿日期：2023-12-10
DOI：10.3404/j.issn.1672-7649.2024.12.029
分类号：TP391.9
基金项目：全国交通运输职业教育高职百万扩招专项课题项目（2020KZ05）
作者简介：孙琳(1983-),女,硕士,讲师,研究方向为物流管理
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