COLREGs-Adaptive trajectory planning and decision-making in maritime autonomous surface ships

被引:2
|
作者
Han, Zhepeng [1 ,2 ,3 ]
Wu, Da [1 ,2 ,3 ]
Zhang, Jinfen [1 ,2 ,3 ]
Huang, Tao [4 ]
Han, Qing-Long [5 ]
Zhang, Mingyang [6 ]
机构
[1] Wuhan Univ Technol, State Key Lab Maritime Technol & Safety, Wuhan 430067, Hubei, Peoples R China
[2] Wuhan Univ Technol, Natl Engn Res Ctr Water Transport Safety, Wuhan 430067, Hubei, Peoples R China
[3] Wuhan Univ Technol, Intelligent Transportat Syst Res Ctr, Wuhan 430067, Hubei, Peoples R China
[4] James Cook Univ, Coll Sci & Engn, Cairns, Qld 4878, Australia
[5] Swinburne Univ Technol, Sch Sci Comp & Engn Technol, Melbourne, Vic 3122, Australia
[6] Aalto Univ, Sch Engn, Dept Mech Engn, FI-00076 Aalto, Finland
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Collision avoidance; COLREGs; Trajectory planning; Hybrid A*; Optimal control;
D O I
10.1016/j.oceaneng.2024.119308
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
Decision-making for collision avoidance and trajectory planning are critical technologies for maritime autonomous surface ships. These systems must align with regulatory frameworks such as the International Regulations for Preventing Collisions at Sea (COLREGs) and account for the ship's maneuvering capabilities for effective control and tracking. This study introduces a novel framework integrating regulatory consideration into the path-searching process, enhancing collision avoidance in both COLREG-compliant and non-compliant scenarios. The framework recasts the trajectory-planning problem into an optimal control problem and employs virtual obstacles and spatial-temporal navigation corridors consistent with collision-free decisions as constraints for trajectory optimization, improving navigation efficiency and comfort. The framework is validated through various encounter scenarios, and the results demonstrate that the proposed framework can produce superior collision avoidance decisions, while planning shorter navigation time and smoother collision- free trajectories, significantly improving the collision avoidance capability of maritime autonomous surface ships.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Local Route Planning for Collision Avoidance of Maritime Autonomous Surface Ships in Compliance with COLREGs Rules
    Namgung, Ho
    SUSTAINABILITY, 2022, 14 (01)
  • [2] Decision-Making for the Autonomous Navigation of Maritime Autonomous Surface Ships Based on Scene Division and Deep Reinforcement Learning
    Zhang, Xinyu
    Wang, Chengbo
    Liu, Yuanchang
    Chen, Xiang
    SENSORS, 2019, 19 (18)
  • [3] What factors may influence decision-making in the operation of Maritime autonomous surface ships? A systematic review
    Lynch, Kirsty M.
    Banks, Victoria A.
    Roberts, Aaron P. J.
    Radcliffe, Stewart
    Plant, Katherine L.
    THEORETICAL ISSUES IN ERGONOMICS SCIENCE, 2024, 25 (01) : 98 - 142
  • [4] Investigating decision-making in the operation of Maritime Autonomous Surface Ships using the SchemaWorld Action Research Method
    Lynch, Kirsty M.
    Roberts, Aaron P. J.
    Banks, Victoria A.
    Taunton, Dominic
    Plant, Katherine L.
    FIRST INTERNATIONAL SYMPOSIUM ON TRUSTWORTHY AUTONOMOUS SYSTEMS, TAS 2023, 2022,
  • [5] Fullest COLREGs Evaluation Using Fuzzy Logic for Collaborative Decision-Making Analysis of Autonomous Ships in Complex Situations
    Bakdi, Azzeddine
    Vanem, Erik
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (10) : 18433 - 18445
  • [6] Decision-making and Trajectory Planning for Autonomous Heavy Truck in Dense Traffic
    Hu W.
    Deng Z.
    Zhang B.
    Cao D.
    Yang Y.
    Cao K.
    Li S.
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2023, 59 (12): : 332 - 342
  • [7] Dynamic Adaptive Decision-Making Method for Autonomous Navigation of Ships in Coastal Waters
    Zhao, Xingya
    Huang, Liwen
    Zhang, Ke
    Mou, Junmin
    Yu, Deqing
    He, Yixiong
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 25 (11) : 17917 - 17930
  • [8] Planning and Decision-Making for Autonomous Vehicles
    Schwarting, Wilko
    Alonso-Mora, Javier
    Rus, Daniela
    ANNUAL REVIEW OF CONTROL, ROBOTICS, AND AUTONOMOUS SYSTEMS, VOL 1, 2018, 1 : 187 - 210
  • [9] Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning
    Geisslinger, Maximilian
    Trauth, Rainer
    Kaljavesi, Gemb
    Lienkamp, Markus
    IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 4 : 570 - 579
  • [10] Maritime Autonomous Surface Ships in Use with LMI and Overriding Trajectory Controller
    Rybczak, Monika
    Gierusz, Witold
    APPLIED SCIENCES-BASEL, 2022, 12 (19):