A spatio-temporal attention-based spot-forecasting framework for urban traffic prediction

This work focuses on creating a complex deep neural framework for spatio-temporal traffic forecasting with comparatively very good performance and that shows to be adaptable over several spatio/temporal conditions while remaining easy to understand and interpret.