Multistep speed prediction on traffic networks based on spatio-temporal deep learning approach

We constructed a real-time multi-step prediction algorithm for traffic road network based on a comprehensive spatio-temporal deep learning framework. This method can achieve lower prediction error than existing methods (especially in the case of long prediction interval); at the same time, it can better describe the spatio-temporal correlation of highly congested traffic network flow.