Rutting prediction using deep learning for time series modeling and K-means clustering based on RIOHTrack data

•Deep learning time series models were proposed to predict the rutting progression.•The impacts of different architectures and sequence lengths on deep learning prediction models were analyzed.•The prediction accuracy of ARIMAX, Gaussian process and M−E models were compared.•The proposed model can capture linear and seasonal components of a rutting progression curve.