Fu, Turkcan, Ghasemi, Mo, Zang, Adhikari, Kostic, Zussman and Di define the urban transportation digital twin as a cyber-physical system whose value lies not only in perception, but in prediction, decision-making and feedback. The iconic idea is the distinction between the twin’s “eyes” and its “brain”: sensing and tracking are insufficient unless coupled to AI-enabled inference and operational response. The contribution is to reposition digital twins as closed-loop urban systems, continuously exchanging data, information and control signals between physical and digital environments. Methodologically, the paper maps the pipeline of sensing, communication, edge-cloud computing, AI modelling, vulnerable road-user awareness and traffic management applications. Its bridge to the wider field is the synthesis of intelligent transportation systems, cyber-physical infrastructure, vulnerable-user safety and urban AI governance. It shows that the digital twin is not merely a replica of mobility, but an institutionalised feedback apparatus whose calibration determines whether simulation improves or distorts urban reality.