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

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.