Statheros, Thomas and Howells, Gareth and McDonald-Maier, Klaus (2008) Autonomous Ship Collision Avoidance Navigation Concepts, Technologies and Techniques. Journal of Navigation, 61 (01). pp. 129-142. DOI https://doi.org/10.1017/S037346330700447X
Statheros, Thomas and Howells, Gareth and McDonald-Maier, Klaus (2008) Autonomous Ship Collision Avoidance Navigation Concepts, Technologies and Techniques. Journal of Navigation, 61 (01). pp. 129-142. DOI https://doi.org/10.1017/S037346330700447X
Statheros, Thomas and Howells, Gareth and McDonald-Maier, Klaus (2008) Autonomous Ship Collision Avoidance Navigation Concepts, Technologies and Techniques. Journal of Navigation, 61 (01). pp. 129-142. DOI https://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 |
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Uncontrolled Keywords: | Autonomous ship; collision avoidance; navigation factors; COLREGs |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 18 Sep 2013 19:47 |
Last Modified: | 30 Oct 2024 19:15 |
URI: | http://repository.essex.ac.uk/id/eprint/6872 |