A Proactive Decision Support Method for Ship Collision Awareness Incorporating Ship Maneuvering

This paper aims to enhance ship collision awareness by providing decision support in collision avoidance. To enable real-time computation in navigation, a Non-iterative Action Distance Determination Algorithm (NADDA) is developed. NADDA reduces the time complexity from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${O}\left( T \log n \right)$</tex-math></inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${O}\left( T\right)$</tex-math></inline-formula> by eliminating iterative processes, while maintaining the same space complexity as conventional bisection-based methods. This improvement significantly enhances computational efficiency, facilitating real-time applications. Based on NADDA, a robust and interpretable method for quantifying collision stages is developed by incorporating operational uncertainties, ship man-euverability, and the International Regulations for Preventing Collisions at Sea (COLREGs), thereby providing proactive colli-sion avoidance timing. Simulation experiments and a historical collision accident validated the effectiveness of the proposed methods. The results demonstrate that NADDA reduces computa-tion time by up to 93.1% compared to existing bisection-based methods, and the proposed collision stages quantification method achieves higher accuracy due to the consideration of operational uncertainties. The proposed method exhibits strong robustness and can provide real-time decision support in multi-ship encounter scenarios involving up to four target ships.

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Publication Details

Journal
IEEE Transactions on Intelligent Transportation Systems
Published
2025-09-26
DOI
https://doi.org/10.1109/tits.2025.3577731
Primary Topic
Maritime Navigation and Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

A Proactive Decision Support Method for Ship Collision Awareness Incorporating Ship Maneuvering

Boyuan Zhang, Wengang Mao, Xiao Lang, Mingyang Zhang et al.
IEEE Transactions on Intelligent Transportation Systems
Maritime Navigation and Safety
article

A Proactive Decision Support Method for Ship Collision Awareness Incorporating Ship Maneuvering

Boyuan Zhang, Wengang Mao, Xiao Lang, Mingyang Zhang, Zhao Liu, Hongdong Wang
article en

Abstract

This paper aims to enhance ship collision awareness by providing decision support in collision avoidance. To enable real-time computation in navigation, a Non-iterative Action Distance Determination Algorithm (NADDA) is developed. NADDA reduces the time complexity from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${O}\left( T \log n \right)$</tex-math></inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${O}\left( T\right)$</tex-math></inline-formula> by eliminating iterative processes, while maintaining the same space complexity as conventional bisection-based methods. This improvement significantly enhances computational efficiency, facilitating real-time applications. Based on NADDA, a robust and interpretable method for quantifying collision stages is developed by incorporating operational uncertainties, ship man-euverability, and the International Regulations for Preventing Collisions at Sea (COLREGs), thereby providing proactive colli-sion avoidance timing. Simulation experiments and a historical collision accident validated the effectiveness of the proposed methods. The results demonstrate that NADDA reduces computa-tion time by up to 93.1% compared to existing bisection-based methods, and the proposed collision stages quantification method achieves higher accuracy due to the consideration of operational uncertainties. The proposed method exhibits strong robustness and can provide real-time decision support in multi-ship encounter scenarios involving up to four target ships.

IEEE Transactions on Intelligent Transportation SystemsVol. 26(10)
Shanghai Jiao Tong University (CN), Wuhan University of Technology (CN), Chalmers University of Technology (SE), Aalto University (FI)
Openalex Percentile: Top 67%
Maritime Navigation and Safety
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