Near-Field Route Optimization-Supported Polar Ice Navigation via Maritime Radar Videos
Author(s) -
Xinwei Lin,
Shengzheng Wang,
Xuesheng Zhang,
Tsung-Hsuan Hsieh,
Zhen Sun,
Tingliu Xu
Publication year - 2021
Publication title -
journal of advanced transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 46
eISSN - 2042-3195
pISSN - 0197-6729
DOI - 10.1155/2021/2798351
Subject(s) - visibility , crew , computer science , radar , search and rescue , arctic , heading (navigation) , marine engineering , field (mathematics) , routing (electronic design automation) , simulation , real time computing , aeronautics , meteorology , engineering , telecommunications , artificial intelligence , geography , aerospace engineering , robot , geology , computer network , oceanography , mathematics , pure mathematics
The accurate design of ship routing plans in arctic areas is not easy, considering that navigation conditions (e.g., weather, visibility, and ice thickness) may change frequently. A ship’s crew identifies sea ice in arctic channels with the help of radar echoes, and ship maneuvering decisions are made to avoid navigation interference. Ship officials must manually and consistently change the ship’s route of travel, which is time-consuming and tedious. To address this issue, we propose a near-field route optimization model for the purpose of automatically selecting an optimal route with the help of radar echo images. The ship near-field route optimization model uses a multiobjective optimal strategy considering factors of minimum navigation risk and steaming distance. We verified the model’s performance with the support of the Xuelong voyage dataset. This research finding can help a ship’s crew to design more reasonable navigation routes in polar channels.
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