Before revision:  In order to capture the joint spatial-temporal dynamics of the intersections and road segments, we adopt the spatial-temporal learning layer that incorporates the multi-scale  spatial-temporal graph convolution networks and dual graphinteraction networks.
After revision:  In order to extract the joint spatio-temporal correlations of the intersections and road segments, we adopt the spatial-temporal learning layer that incorporates the multi-scale spatial-temporal graph convolution networks and dual graphinteraction networks.