Ship collision avoidance behaviour recognition and analysis based on AIS data

被引:57
|
作者
Rong, H. [1 ]
Teixeira, A. P. [1 ]
Soares, C. Guedes [1 ]
机构
[1] Univ Lisbon, Ctr Marine Technol & Ocean Engn CENTEC, Inst Super Tecn, Av Rovisco Pais, P-1049001 Lisbon, Portugal
关键词
Ship evasive manoeuvring; Collision avoidance; Sliding window Algorithm; Near collision scenario; RISK-ASSESSMENT; SAFETY; DOMAIN; NAVIGATION; MANEUVERS; SYSTEM; TRAJECTORIES; COMPRESSION; PREDICTION; ACCIDENTS;
D O I
10.1016/j.oceaneng.2021.110479
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
A novel approach is proposed to automatically identify the ship collision avoidance behaviour from ship trajectories based on an improved Sliding Window Algorithm. The approach has three main stages: (1) determining the ships' obligations according to the Convention on the International Regulations for Preventing Collision at Sea (COLREGs); (2) assessing the rudder angle according to the true bearing of the target ship; (3) identifying the corresponding ship handling behaviour from the ship trajectory taking into account the Rate of Turn and its derivative based on the Sliding Window Algorithm. Four typical encounter scenarios are studied to demonstrate the feasibility and effectiveness of the proposed method. The approach is then applied to near collision scenarios identified in the maritime traffic off the continental coast of Portugal, which allowed the characterization of the relative and spatial distributions of the locations at which the ships take evasive manoeuvres. The results show that the approach can be applied to accurately detect the ship collision avoidance behaviour from Automatic Identification System trajectory data, and the characterization of the collision avoidance behaviour can potentially be used by situational awareness systems and as the basis for ship collision avoidance decision-making.
引用
收藏
页数:20
相关论文
共 50 条
  • [1] Pattern knowledge discovery of ship collision avoidance based on AIS data analysis
    Chen P.
    Shi G.
    Liu S.
    Gao M.
    International Journal of Performability Engineering, 2018, 14 (10) : 2449 - 2457
  • [2] Modelling of ship collision avoidance behaviours based on AIS data
    Gao M.
    Shi G.
    Shi, Guoyou (shiguoyoudmu@163.com), 1600, Inderscience Publishers, 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland (15): : 100 - 110
  • [3] Ship encounter scenario generation for collision avoidance algorithm testing based on AIS data
    Wang, Weiqiang
    Huang, Liwen
    Liu, Kezhong
    Zhou, Yang
    Yuan, Zhitao
    Xin, Xuri
    Wu, Xiaolie
    OCEAN ENGINEERING, 2024, 291
  • [4] DECISION SUPPORT BASED ON ARTIFICIAL FISH SWARM FOR SHIP COLLISION AVOIDANCE FROM AIS DATA
    Chen, Peng
    Shi, Guoyou
    Liu, Shuang
    Zhang, Yuanqiang
    PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 1, 2018, : 31 - 36
  • [5] A Research on AIS-based Embedded System for Ship Collision Avoidance
    Chen, Dejun
    Wan, Xuechao
    Dai, Chu
    Mou, Junmin
    3RD INTERNATIONAL CONFERENCE ON TRANSPORTATION INFORMATION AND SAFETY (ICTIS 2015), 2015, : 512 - 517
  • [6] Based on ECDIS and AIS ship collision avoidance warning system research
    He Jincan
    Feng Maoyan
    PROCEEDINGS OF 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION (ICICTA 2015), 2015, : 242 - 245
  • [7] CAPatternMiner: Mining Ship Collision Avoidance Behavior from AIS Trajectory Data
    Lei, Po-Ruey
    Xiao, Li-Pin
    Wen, Yu-Ting
    Peng, Wen-Chih
    CIKM'18: PROCEEDINGS OF THE 27TH ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, 2018, : 1875 - 1878
  • [8] Generation and complexity analysis of ship encounter scenarios using AIS data for collision avoidance algorithm testing
    Wang, Weiqiang
    Liu, Kezhong
    Huang, Liwen
    Xin, Xuri
    Wu, Xiaolie
    Yuan, Zhitao
    OCEAN ENGINEERING, 2024, 312
  • [9] An interpretable knowledge-based decision support method for ship collision avoidance using AIS data
    Zhang, Jinfen
    Liu, Jiongjiong
    Hirdaris, Spyros
    Zhang, Mingyang
    Tian, Wuliu
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2023, 230
  • [10] Validation of ship intention model for maritime collision avoidance control using historical AIS data
    Rothmund, Sverre Velten
    Haugen, Helene Engebakken
    Veglo, Guro Drange
    Brekke, Edmund Forland
    Johansen, Tor Arne
    2023 EUROPEAN CONTROL CONFERENCE, ECC, 2023,