Conditional Deep Learning for Urban Origin–Destination (OD) Matrix Estimation Under Varying Connected-Vehicle Penetration
Connected vehicles and vehicle-to-everything (V2X) communication create new opportunities for estimating urban origin–destination (OD) demand from continuously collected mobility data. However, in realistic deployment conditions, only a fraction of vehicles may be connected, making OD reconstruction a highly underdeter...