This research introduces a multi-modal knowledge-enhanced framework that significantly improves vessel trajectory prediction by tackling the challenges of irregular AIS data and complex maritime movements.

• Combines multiple data sources and domain knowledge to enhance prediction accuracy
• Addresses the irregular sampling time intervals in global vessel tracking systems
• Creates a more robust modeling approach for complex maritime navigation patterns
• Enables improved navigational safety, efficient routing, and environmental protection

For engineers and maritime security professionals, this breakthrough means more reliable navigation systems, reduced collision risks, and optimized shipping routes that can save fuel and reduce environmental impact.

A Multi-Modal Knowledge-Enhanced Framework for Vessel Trajectory Prediction