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Full article: A collision avoidance algorithm for ship guidance applications
Source: tandfonline.com
Article summary:
1. The number of marine accidents is increasing due to the increase in the number and size of ships.
2. This paper proposes a method to improve ship safety by using AIS data to detect surrounding ships and plan an evasive manoeuvre.
3. Various algorithms have been proposed for collision avoidance, such as genetic algorithms, potential field methods, dynamic programming, mixed-integer linear programming, and random sampling algorithms.
Article analysis:
The article is generally reliable and trustworthy in its reporting of the current state of collision avoidance algorithms for ship guidance applications. The article provides a comprehensive overview of the various approaches that have been proposed in the past, including genetic algorithms, potential field methods, dynamic programming, mixed-integer linear programming, and random sampling algorithms. The article also provides evidence for its claims in the form of citations from other research papers on the topic.
The article does not appear to be biased or one-sided in its reporting; it presents both sides equally and does not appear to be promotional or partial in any way. It also notes possible risks associated with each approach discussed and does not make unsupported claims or omit counterarguments.
The only potential issue with the article is that it does not explore all possible approaches to collision avoidance; there may be other approaches that could be explored but are not mentioned in this article. However, this is a minor issue and overall the article appears to be reliable and trustworthy in its reporting on collision avoidance algorithms for ship guidance applications.