Predictive Model for Long-Term Lane Occupancy Rate Based on CT-Transformer and Variational Mode Decomposition
Gaoxiang Liu,
Xin Yu,
Danyang Liu
Abstract:Lane occupancy is a crucial indicator of traffic flow and is significant for traffic management and planning. However, predicting lane occupancy is challenging due to numerous influencing factors, such as weather, holidays, and events, which render the data nonsmooth. To enhance lane occupancy prediction accuracy, this study introduces a fusion model that combines the CT-Transformer (CSPNet-Attention and Two-stage Transformer framework) with the Temporal Convolutional Neural Network-Long Short-Term Memory (TCN… Show more
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