A hierarchical framework fuses a long-term intent predictor with a grid-based Spatio-Temporal Graph Transformer and environmental cross-modal attention to cut average displacement error by 25% over 10-hour horizons on Australian vessel data.
Big data driven vessel trajectory and navigating state predic- tion with adaptive learning, motion modeling and particle filtering techniques,
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Hierarchical Two-Stage Framework for Environment-Aware Long-Horizon Vessel Trajectory Prediction
A hierarchical framework fuses a long-term intent predictor with a grid-based Spatio-Temporal Graph Transformer and environmental cross-modal attention to cut average displacement error by 25% over 10-hour horizons on Australian vessel data.