AIS-Based Vessel Trajectory Prediction Using Memory-Augmented Neural Networks

📰 ArXiv cs.AI

Learn how to predict vessel trajectories using memory-augmented neural networks for safer maritime operations

advanced Published 5 Jun 2026

Action Steps

Build a memory-augmented neural network using AIS data to predict vessel trajectories
Configure the network to selectively retrieve relevant information from an external memory
Train the model using historical AIS data to improve prediction accuracy
Test the model on new, unseen data to evaluate its performance
Apply the predicted trajectories to optimize route planning and collision avoidance

Who Needs to Know This

Data scientists and AI engineers working in maritime operations can benefit from this research to improve collision avoidance and route optimization

Key Insight

💡 Memory-augmented neural networks can effectively predict vessel trajectories by selectively retrieving relevant information from an external memory

Key Takeaways

Learn how to predict vessel trajectories using memory-augmented neural networks for safer maritime operations

Full Article

Title: AIS-Based Vessel Trajectory Prediction Using Memory-Augmented Neural Networks

Abstract:
arXiv:2606.06311v1 Announce Type: new Abstract: Accurate vessel trajectory prediction is essential for safe and efficient maritime operations, enabling collision avoidance and supporting route optimization. Although memory-augmented neural networks have recently shown strong performance in pedestrian and road-vehicle trajectory prediction by selectively retrieving relevant information from an external memory, their potential for vessel trajectory prediction remains underexplored. This paper pres

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