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Decision Support from Genetic Algorithms for Ship Collision Avoidance Route Planning and Alerts

Published online by Cambridge University Press:  01 December 2009

Ming-Cheng Tsou*
Affiliation:
(National Taiwan Ocean University, Department of Transportation and Navigation Science)
Sheng-Long Kao
Affiliation:
(National Taiwan Ocean University, Department of Transportation and Navigation Science)
Chien-Min Su
Affiliation:
(National Taiwan Ocean University, Department of Electrical Engineering)

Abstract

When an officer of the watch (OOW) faces complicated marine traffic, a suitable decision support tool could be employed in support of collision avoidance decisions, to reduce the burden and greatly improve the safety of marine traffic. Decisions on routes to avoid collisions could also consider economy as well as safety. Through simulating the biological evolution model, this research adopts the genetic algorithm used in artificial intelligence to find a theoretically safety-critical recommendation for the shortest route of collision avoidance from an economic viewpoint, combining the international regulations for preventing collisions at sea (COLREGS) and the safety domain of a ship. Based on this recommendation, an optimal safe avoidance turning angle, navigation restoration time and navigational restoration angle will also be provided. A Geographic Information System (GIS) will be used as the platform for display and operation. In order to achieve advance notice of alerts and due preparation for collision avoidance, a Vessel Traffic Services (VTS) operator and the OOW can use this system as a reference to assess collision avoidance at present location.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2009

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