Relation-Augmented Diffusion Graph Convolution Network (RADGCN)

This repository implements RADGCN, a relation-aware graph neural network for network-wide traffic state estimation (traffic kriging) when only a subset of road sensors is observed. It accompanies the manuscript Relation-diffusion augmented network-wide traffic state estimation.Rather than learning adaptive relations from zero-filled features at unobserved nodes, RADGCN first learns functional relations among nodes with reliable observations. It then diffuses these relations across the directed road graph and uses the resulting relation kernel alongside forward and backward physical diffusion to reconstruct traffic speeds at unobserved nodes.