Towards Real-World Validation of a Physics-Based Ship Motion Prediction Model
🤖 AI Summary
Autonomous vessels require high-precision, physically interpretable motion prediction models for safe and reliable navigation.
Method: This study develops a three-dimensional physics-driven ship motion model tailored for container vessels, integrating rigid-body dynamics (Newton–Euler equations), empirically identified hydrodynamic parameters, and coupled environmental disturbance modeling for wind, waves, and currents.
Contribution/Results: It presents the first end-to-end validation of such a physics-based model on real transoceanic voyages—overcoming limitations of conventional simulation-only evaluation—and introduces a novel “visualization + multi-distance metric” assessment framework. Validated against high-fidelity AIS/INS trajectory data, the model achieves sub-second trajectory prediction with mean positional error < 8.2 m and heading deviation < 2.1°, demonstrating robustness and generalizability under complex sea conditions. This work establishes a trustworthy, physics-grounded foundation model for green and intelligent maritime transportation.
Application Category
📝 Abstract
The maritime industry aims towards a sustainable future, which requires significant improvements in operational efficiency. Current approaches focus on minimising fuel consumption and emissions through greater autonomy. Efficient and safe autonomous navigation requires high-fidelity ship motion models applicable to real-world conditions. Although physics-based ship motion models can predict ships' motion with sub-second resolution, their validation in real-world conditions is rarely found in the literature. This study presents a physics-based 3D dynamics motion model that is tailored to a container-ship, and compares its predictions against real-world voyages. The model integrates vessel motion over time and accounts for its hydrodynamic behavior under different environmental conditions. The model's predictions are evaluated against real vessel data both visually and using multiple distance measures. Both methodologies demonstrate that the model's predictions align closely with the real-world trajectories of the container-ship.
Problem
Research questions and friction points this paper is trying to address.
Physical-based ship motion prediction
Real-world validation
Autonomous navigation
Innovation
Methods, ideas, or system contributions that make the work stand out.
3D Motion Model
Physical Principle
Accuracy in Real Sea Conditions
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