Autonomous Ship Collision Avoidance Navigation Concepts, Technologies and Techniques

Statheros, Thomas and Howells, Gareth and McDonald-Maier, Klaus D. (2008) Autonomous Ship Collision Avoidance Navigation Concepts, Technologies and Techniques. Journal of Navigation, 61 (1). pp. 129-142. ISSN 1469-7785 online, 0373-4633 print. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1017/S037346330700447X

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).

Item Type: Article
Uncontrolled keywords: autonomous ship; collision avoidance; navigation factors; COLREGs
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA168 Systems engineering, cybernetics and intelligent systems
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: J. Harries
Date Deposited: 20 Apr 2009 14:04
Last Modified: 23 May 2014 09:11
Resource URI: http://kar.kent.ac.uk/id/eprint/17524 (The current URI for this page, for reference purposes)
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