Dynamic traveling time forecasting based on spatial-temporal graph convolutional networks

Traveling time forecasting, the core component in GPS navigation systems and taxi-hailing apps, has attracted widespread attention. Existing research mostly focuses on independent points like traffic flow prediction or route planning, which ignore globality and lack satisfactory dynamic progress to adopt sophisticated traffic conditions.

apps attention computer sciences core dynamic flow forecasting gps graph independent navigation networks planning prediction progress research route spatial systems temporal traffic