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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/41720

Title: The study of ship collision avoidance route planning by ant colony algorithm
Authors: Ming-Cheng Tsou
Chao-Kuang Hsueh
Contributors: 國立臺灣海洋大學:商船學系
Keywords: ant colony algorithm
collision avoidance
GIS
e-navigation
Date: 2010-10
Issue Date: 2017-03-22T02:19:55Z
Publisher: Journal of Marine Science and Technology
Abstract: Abstract: Maritime traffic is becoming more complex every day. At present, due to technological advances and to new maritime regulations, there is increasing demand for new nautical ma-rine instruments to be installed into the bridge, and the breadth of navigational information complicates on-duty officers' de-cisions. Therefore, if decision support tools can be used to help deal with navigational decision-making, human errors arising from subjective judgments can be reduced, and sea transport safety improved. This research uses the concept of e-navigation as a framework, positioning collision avoidance path planning as the main theme, and applies an Ant Colony Algorithm (ACA) in the field of artificial intelligence to con-struct a collision avoidance model that imitates optimization behaviors in real-life applications. This model combines navi-gational practices, a maritime laws/regulations knowledge base and real-time navigation information from the AIS to plan a safe and economical collision avoidance path. Through using such planning, recommendations can be made for colli-sion avoidance and return to course. Lastly, a Geographic Information System (GIS) was used as the platform for a navi-gation decision support system, combining related navigation information, collision avoidance models and electronic charts. This is a source of reference for VTS (Vessel Traffic Service) operators and on-duty officers to assess collisions in territorial waters, achieving objectives such as warning and pre-collision preparations.
Relation: 18(5)
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/41720
Appears in Collections:[商船學系] 期刊論文

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