Federated Learning for Traffic Flow Prediction with Synthetic Data Augmentation

Fermin Orozco, Pedro Porto Buarque de Gusmão, Hongkai Wen +2

Deep-learning based traffic prediction models require vast amounts of data to learn embedded spatial and temporal dependencies. The inherent privacy and commercial sensitivity of s…