A Graph Neural Network Surrogate Model for Incident-Based Travel Time Prediction Under Limited Sensor Data
A Spatio-Temporal Graph Convolutional Network (STGCN) for forecasting route-level travel times on a simulated Nashville, Tennessee road network with 1,037 junctions and 1,601 road segments is presented, demonstrating the potential of the model as an efficient surrogate for transportation resilience screening, incident...