1. Spatio-temporal graph convolutional networks: a deep learning framework for traffic forecasting;Bing Yu,2018
2. OSMnx: new methods for acquiring, constructing, analyzing, and visualizing complex Street networks;Boeing;Comput. Environ. Urban Syst.,2017
3. A variational autoencoder solution for road traffic forecasting systems: missing data imputation, dimension reduction, model selection and anomaly detection;Boquet;Transport. Res. Part C,2020
4. Encuesta de Movilidad de la Comunidad de Madrid 2018;Consorc. Reg. de Transp. de Madrid,2018
5. Road short-term travel time prediction method based on flow spatial distribution and the relations;Deng;Math. Probl Eng.,2016