A Granger causality-guided multi-graph transformer framework for traffic flow forecasting
Accurate traffic forecasting is challenging because of the difficulty of capturing time-varying propagation and multi-scale spatio-temporal interactions. Most existing deep learning models only learn correlations rather than directional dependencies, which limits interpretability and robustness under dynamic traffic co...