A dual branch graph neural network based spatial interpolation method for traffic data inference in unobserved locations

Wujiang Zhu, Xinyuan Zhou, Shiyong Lan, Wenwu Wang, Zhiang Hou, Yao Ren, Tianyi Pan

Abstract: Highlights•Designed a Dynamic Graph Learning (DGL) module based on self-attention mechanism.•Proposed a new dual branch architecture to model the diffusion mechanism among nodes.•Explored a novel auxiliary branch to model the local details of spatial correlations.•Our proposed method has achieved the state-of-the-art results on four public datasets.