TY - JOUR
T1 - Digital Twin Technology for Intelligent Vehicles and Transportation Systems
T2 - A Survey on Applications, Challenges and Future Directions
AU - Gu, Xiaohui
AU - Duan, Wei
AU - Zhang, Guoan
AU - Hou, Jia
AU - Peng, Limei
AU - Wen, Miaowen
AU - Gao, Feifei
AU - Chen, Min
AU - Ho, Pin Han
N1 - Publisher Copyright:
© 1998-2012 IEEE.
PY - 2026
Y1 - 2026
N2 - This survey provides a comprehensive analysis of digital twin (DT) technology as a transformative tool for advancing connected and autonomous vehicles (CAVs) and intelligent transportation systems (ITSs), focusing on advancements in vehicle safety, traffic management, and autonomous driving capabilities. The paper begins by discussing the foundational concepts and enabling technologies behind DT systems, setting the stage for their application in transportation networks. We review DT applications in vehicle safety, highlighting their role in real-time monitoring, predictive maintenance, and risk mitigation. Next, we explore the role of DT technology in optimizing traffic flow, enhancing traffic management, and enabling adaptive responses to dynamic conditions. The paper then examines the integration of DTs in intelligent and autonomous vehicles, emphasizing advancements in simulation, testing, and the development of autonomous driving functionalities. Finally, we outline future research opportunities and challenges for DT applications, providing a roadmap for their continued evolution in CAVs and ITS.
AB - This survey provides a comprehensive analysis of digital twin (DT) technology as a transformative tool for advancing connected and autonomous vehicles (CAVs) and intelligent transportation systems (ITSs), focusing on advancements in vehicle safety, traffic management, and autonomous driving capabilities. The paper begins by discussing the foundational concepts and enabling technologies behind DT systems, setting the stage for their application in transportation networks. We review DT applications in vehicle safety, highlighting their role in real-time monitoring, predictive maintenance, and risk mitigation. Next, we explore the role of DT technology in optimizing traffic flow, enhancing traffic management, and enabling adaptive responses to dynamic conditions. The paper then examines the integration of DTs in intelligent and autonomous vehicles, emphasizing advancements in simulation, testing, and the development of autonomous driving functionalities. Finally, we outline future research opportunities and challenges for DT applications, providing a roadmap for their continued evolution in CAVs and ITS.
KW - Digital twin
KW - connected and autonomous vehicles
KW - intelligent transportation systems
KW - predictive maintenance
KW - real-time data analytics
KW - traffic management
KW - vehicle safety
UR - https://www.scopus.com/pages/publications/105009134633
U2 - 10.1109/COMST.2025.3581152
DO - 10.1109/COMST.2025.3581152
M3 - Review article
AN - SCOPUS:105009134633
SN - 1553-877X
VL - 28
SP - 3235
EP - 3271
JO - IEEE Communications Surveys and Tutorials
JF - IEEE Communications Surveys and Tutorials
ER -