ST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Road Speed

Understand

Predicting road traffic speed is a challenging task due to different types of roads, abrupt speed change and spatial dependencies between roads; it requires the modeling of dynamically changing spatial dependencies among roads and temporal patterns over long input sequences.

• This paper proposes a novel spatio-temporal graph attention (ST-GRAT) that effectively captures the spatio-temporal dynamics in road networks.
• The novel aspects of our approach mainly include spatial attention, temporal attention, and spatial sentinel vectors.
• The spatial attention takes the graph structure information (e.g., distance between roads) and dynamically adjusts spatial correlation based on road states.