Digital twin intelligent transportation system (DT‐ITS)—A systematic review

Abstract Digital twin (DT) has attracted much attention from the transportation community over the past 6 years. Combining the DT with intelligent transportation system (ITS) forms a digital twin intelligent transportation system (DT‐ITS), which stands as one of the most effective solutions for addressing current complex traffic problems. Due to the rapid advancements in this field and a lack of recent literature reviews, this paper first reviews relevant literature on DT‐ITS architecture design, to comprehend its core structure, methods, potential services and stakeholders, and implementation challenges, and then discusses DT‐ITS core considerations, aiming to provide a general configuration model of DT‐ITS for future development. Second, this paper focuses on reviewing the existing progress of DT‐ITS services within the 32 categories of ITS services, adopting the service‐centred point of view, to explore the potential DT‐ITS services, proposed delivery methods, challenges, and opportunities for various stakeholders. Third, key enabling technologies supporting DT‐ITS are reviewed and discussed, such as data fusion, cooperative perception, multi‐access edge computing (MEC) (including computing offloading and service caching), federated learning, edge‐cloud collaboration, secure and efficient communication (including Blockchain BC, 5G), virtual modelling, and eXtended reality (XR). Finally, the paper identifies development trends and provides recommendations for future advancements.