Autonomous navigation decision-making for ships in complex estuarine waters: Methodology and validation

被引:0
|
作者
Dai, Yonggang [1 ,2 ]
He, Yixiong [1 ,2 ]
Huang, Liwen [1 ,2 ]
Zhao, Xingya [1 ,2 ]
机构
[1] Wuhan Univ Technol, Sch Nav, Wuhan 430063, Peoples R China
[2] Hubei Key Lab Inland Shipping Technol, Wuhan 430063, Peoples R China
基金
中国国家自然科学基金;
关键词
Autonomous navigation decision-making; Integration of virtual and real scenes; Historical AIS data; Collision avoidance mechanism; Complex water environments in estuaries;
D O I
10.1016/j.oceaneng.2024.118474
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
This study focused on key scientific issues in the autonomous navigation for ships, including constraints on environmental and navigation rules, limitations on ship maneuverability, and collision avoidance mechanisms, to address the challenges of autonomous navigation decision-making for ships in complex estuarine waters and validate the feasibility and accuracy of the proposed methodology. A novel autonomous navigation decisionmaking method that can dynamically adapt to residual errors in a system and the random movements of target ships was proposed. The predictive model used to calculate decision plans and the simulation model used to execute and validate decision plans were separated. Environmental constituent elements were classified and modeled to digitize the environment. A navigation scenario was constructed based on the fusion of virtual and real information. The control and process prediction methods were proposed based on the nonlinear ship maneuvering characteristics. Navigation rules were summarized, analyzed, and integrated into the decisionmaking and execution process. The collision avoidance mechanism and calculation method for feasible course and speed range were studied. Simulation experiments were conducted using the North Channel of the Yangtze River Estuary as an example. The results demonstrated that the proposed method can accurately make autonomous navigation decisions, safely avoid collisions, and timely track routes in nearly realistic scenarios.
引用
收藏
页数:18
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