HFD-TM predicts turning movements with 2.49 MAE by hierarchically decomposing corridor flows and enforcing conservation, outperforming Transformer and GRU baselines on six months of Nashville LiDAR data.
Traffic flow prediction in urban built-up areas using deep learning,
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Hierarchical Flow Decomposition for Turning Movement Prediction at Signalized Intersections
HFD-TM predicts turning movements with 2.49 MAE by hierarchically decomposing corridor flows and enforcing conservation, outperforming Transformer and GRU baselines on six months of Nashville LiDAR data.