Abstract
Artificial intelligence (AI) may be the panacea for improving safety and efficiency in shipping. Solutions to navigation problems are often challenged by information uncertainty, complexity and time demands. Tactical decisions to understand traffic patterns and future vessel encounters can be compared to a game of chess where an agent has goals and considers the next several moves in advance. AI approaches to machine learning is a reactive tactic but remains relatively ‘‘weak” and relies on computational power and smart algorithms to recreate each decision every time. Ships are required to follow the International Regulations for Preventing Collisions at Sea. While assumed to be the defining rules of the road, these may be ‘‘violated” to solve traffic situations in practice without creating increased risk to the situation. In order to create safe and reliable technologies to support autonomous shipping, the system cannot just rely on where it has to go but anticipate the goals of the surrounding vessels. This paper will explore the challenges, knowledge and technology gaps regarding AI in the shipping sector.
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MacKinnon, S.N., Weber, R., Olindersson, F., Lundh, M. (2020). Artificial Intelligence in Maritime Navigation: A Human Factors Perspective. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1212. Springer, Cham. https://doi.org/10.1007/978-3-030-50943-9_54
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