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Autonomous Ship Collision Avoidance Navigation Concepts, Technologies and Techniques

Published online by Cambridge University Press:  10 December 2007

Thomas Statheros ,
Gareth Howells  and
Klaus McDonald Maier
Thomas Statheros*
Affiliation:
(University of Kent, Department of Electronics)
Gareth Howells
Affiliation:
(University of Kent, Department of Electronics)
Klaus McDonald Maier
Affiliation:
(University of Essex, Department of Computing and Electronic Systems)
*
(Email: t.statheros@kent.ac.uk)
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Abstract

This study provides both a spherical understanding about autonomous ship navigation for collision avoidance (CA) and a theoretical background of the reviewed work. Additionally, the human cognitive abilities and the collision avoidance regulations (COLREGs) for ship navigation are examined together with water based collision avoidance algorithms. The requirements for autonomous ship navigation are addressed in conjunction with the factors influencing ship collision avoidance. Humans are able to appreciate these factors and also perform ship navigation at a satisfactory level, but their critical decisions are highly subjective and can lead to error and potentially, to ship collision. The research for autonomous ship navigation may be grouped into the classical and soft computing based categories. Classical techniques are based on mathematical models and algorithms while soft-computing techniques are based on Artificial Intelligence (AI). The areas of AI for autonomous ship collision avoidance are examined in this paper are evolutionary algorithms, fuzzy logic, expert systems, and neural networks (NN), as well as a combination of them (hybrid system).

Keywords

Autonomous ShipCollision avoidanceNavigation factorsCOLREGs
Type
Research Article
Information
The Journal of Navigation , Volume 61 , Issue 1 , January 2008 , pp. 129 - 142
Copyright
Copyright © The Royal Institute of Navigation 2007

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