Hierarchical Two-Stage Framework for Environment-Aware Long-Horizon Vessel Trajectory Prediction
Long-horizon vessel trajectory forecasting under real ocean conditions is critical for collision avoidance, traffic management, and route planning. However, achieving accurate predictions is challenging due to long-range temporal dependencies and dynamic environmental factors such as currents, wind, and waves. To address these issues, we propose a hierarchical two-stage framework that combines a coarse long-term predictor with a grid-aware short-term predictor through a hierarchical fusion mechanism. The short-term branch leverages a Spatio-Temporal Graph Transformer on discretized maritime cells to capture localized dynamics, while the long-term branch encodes overarching navigational in...
| Authors | Ganeshaaraj Gnanavel, Tharindu Fernando, Sridha Sridharan et al. |
|---|---|
| Primary category | cs.RO |
| Published | 15 May 2026 |
| Last updated at source | 15 May 2026 |
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