A Digital Twin Framework for Physical-Virtual Integration in V2X-Enabled Connected Vehicle Corridors
<|reference_start|>A Digital Twin Framework for Physical-Virtual Integration in V2X-Enabled Connected Vehicle Corridors: Transportation Cyber-Physical Systems (T-CPS) are critical in improving traffic safety, reliability, and sustainability by integrating computing, communication, and control in transportation systems. The connected vehicle corridor is at the forefront of this transformation, where Cellular Vehicle-to-Everything (C-V2X) technology facilitates real-time data exchange between infrastructure, vehicles, and road users. However, challenges remain in processing and synchronizing the vast V2X data from vehicles and roadside units, particularly when ensuring scalability, data integrity, and operational resilience. This paper presents a digital twin framework for T-CPS, developed from a real-world connected vehicle corridor to address these challenges. By leveraging C-V2X technology and real-time data from infrastructure, vehicles, and road users, the digital twin accurately replicates vehicle behaviors, signal phases, and traffic patterns within the CARLA simulation environment. This framework demonstrates high fidelity between physical and digital systems and ensures robust synchronization of vehicle trajectories and signal phases through extensive experiments. Moreover, the digital twin's scalable and redundant architecture enhances data integrity, making it capable of supporting future large-scale C-V2X deployments. The digital twin is a vital tool in T-CPS, enabling real-time traffic monitoring, prediction, and optimization to enhance the reliability and safety of transportation systems.<|reference_end|>
@article{wu2024a,
    title={A Digital Twin Framework for Physical-Virtual Integration in V2X-Enabled
  Connected Vehicle Corridors},
    author={Keshu Wu, Pei Li, Yang Cheng, Steven T. Parker, Bin Ran, David A.
  Noyce, Xinyue Ye},
    journal={arXiv preprint arXiv:2410.00356},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.00356},
    primaryClass={cs.RO cs.ET cs.SY eess.SY}
}