Deep reinforcement learning model for Multi-Ship collision avoidance decision making design implementation and performance analysis

Deep reinforcement learning model for Multi-Ship collision avoidance decision making design implementation and performance analysis

Abstract This paper proposes a novel multi-ship collision avoidance decision-making model based on deep reinforcement learning (DRL). The model addresses the critical challenge of preventing ship collisions while maintaining efficient navigation in complex maritime environments. Our innovation lies...

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Bibliographic Details
Main Authors: Rongjun Pan, Wei Zhang, Shijie Wang, Shuhua Kang
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Deep reinforcement learning
Maritime safety
Collision avoidance
Multi-Ship navigation
Decision-Making
Maritime transportation
Online Access:https://doi.org/10.1038/s41598-025-05636-3
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https://doi.org/10.1038/s41598-025-05636-3

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