船舶航行中精准规划航行路线，合理避开障碍物是安全运行的关键。为此，设计一种基于神经网络精准规划船舶航行路线的算法。利用遗传算法优化神经网络权值，建立基于神经网络的船舶航迹预测模型，在模型内输入船舶航向与航速，输出船舶经、纬度差，即船舶航迹预测结果，依据该结果，获取船舶航行时路线规划环境；依据马尔科夫决策过程，得到路线规划最佳策略网络，通过深度强化学习神经网络确定最佳策略，在该网络内输入路线规划环境预测结果，确定规划策略内船舶执行动作，完成航行路线精准规划。实验证明：该算法可精准预测船舶航迹；在不同水域及场景下，均可精准规划航行路线，确保航行时无碰撞危险，降低航迹点平均距离偏差。
Accurate planning of navigation route and reasonable avoidance of obstacles are the key to safe operation. Therefore, an algorithm for accurately planning ship route based on neural network is designed. The weight of neural network is optimized by genetic algorithm, and the ship track prediction model based on neural network is established. The ship course and speed are input into the model, and the ship longitude and latitude difference, that is, the ship track prediction result, is output. According to the result, the route planning environment during ship navigation is obtained; According to the Markov decision-making process, the optimal strategy network of route planning is obtained, the optimal strategy is determined through the deep reinforcement learning neural network, the prediction results of route planning environment are input into the network, the ship execution actions within the planning strategy are determined, and the navigation route is accurately planned. Experiments show that the algorithm can accurately predict the ship track. In different waters and scenarios, the navigation route can be accurately planned to ensure that there is no collision risk during navigation and reduce the average distance deviation of track points.
2022,44(10): 143-146 收稿日期：2021-10-16
DOI：10.3404/j.issn.1672-7649.2022.10.030
分类号：U675.7
基金项目：江苏省高等学校自然科学研究面上项目资助项目（18KJD580002）；南通市科技项目（MSZ21007）；江苏省教育科学“十四五”规划课题（C-b/2021/03/21）
作者简介：曹石勇(1982-)，男，硕士，讲师，研究方向为航海技术及船舶驾驶
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