FedSTD: Federated Learning with Spatio-Temporal Decoupling for Cross-Modal Transport Prediction
Modern transportation systems are shaped by multiple interdependent modes of transport. Understanding their interactions is essential for effective management and planning. Cross-modal flow and demand predictions can improve forecasting accuracy for individual modes by exploiting these interdependencies. However, data-...