Norman Bereczki

Recurrent Graph Neural Network Hybrid Model for Spatio-Temporal Traffic Flow Prediction in Intelligent Transportation Systems

TETRA is proposed, a hybrid spatio-temporal traffic forecasting model that integrates Graph Convolutional Networks (GCNs) with Extended Long Short-Term Memory (xLSTM) to capture complex multi-timescale temporal patterns, including congestion propagation and delayed recovery dynamics, which are not well represented by conventional recurrent models.