A Review of Artificial Intelligence-Based Optimization Applications in Traditional Active Maritime Collision Avoidance

Yi Zhang, Dapeng Zhang () and Haoyu Jiang
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Yi Zhang: Ship and Maritime College, Guangdong Ocean University, Zhanjiang 524088, China
Dapeng Zhang: Ship and Maritime College, Guangdong Ocean University, Zhanjiang 524088, China
Haoyu Jiang: School of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang 524088, China

Sustainability, 2023, vol. 15, issue 18, 1-20

Abstract: The probability of collisions at sea has increased in recent years. Furthermore, passive collision avoidance has some disadvantages, such as low economic efficiency, while active collision avoidance techniques have some limitations. As a result of the advancement of computer technology, active collision avoidance techniques have also been optimized by using artificial intelligence-based methods. The purpose of this paper is to further the development of the field. After reviewing some passive collision avoidance schemes, the paper discusses the potential of active obstacle avoidance techniques. A time-tracing approach is used to review the evolution of active obstacle avoidance techniques, followed by a review of the main traditional active obstacle avoidance techniques. In this paper, different artificial intelligence algorithms are reviewed and analyzed. As a result of the analysis and discussion in this paper, some limitations in this field are identified. In addition, there are some suggestions and outlooks for addressing those limitations. In a way, the paper can serve as a guide for the development of the field.

Keywords: active collision avoidance techniques; artificial intelligence algorithms; collisions at sea; traditional active obstacle avoidance; time-tracing approach (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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