Efficient and Accurate Digital Twins for Lane-Wise and Topology-Invariant Intersection Traffic Simulation

Graph Attention Neural Networks are leveraged to build efficient and accurate digital twins that can simultaneously estimate lane-wise traffic waveforms for vehicles approaching and exiting any intersection, while accounting for various influential factors such as signal timing, driving behavior, and turning-movement counts.