Towards Next Generation of Pedestrian and Connected Vehicle In-the-loop Research: A Digital Twin Co-Simulation Framework
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Abstract (arXiv)
Digital Twin is an emerging technology that replicates real-world entities into a digital space. It has attracted increasing attention in the transportation field and many researchers are exploring its future applications in the development of Intelligent Transportation System (ITS) technologies. Connected vehicles (CVs) and pedestrians are among the major traffic participants in ITS. However, the usage of Digital Twin in research involving both CV and pedestrian remains largely unexplored. In this study, a Digital Twin framework for CV and pedestrian in-the-loop simulation is proposed. The proposed framework consists of the physical world, the digital world, and data transmission in between. The features for the entities (CV and pedestrian) that need digital twining are divided into external state and internal state, and the attributes in each state are described. We also demonstrate a sample architecture under the proposed Digital Twin framework, which is based on Carla-Sumo Co-simulation and Cave automatic virtual environment (CAVE). A case study that investigates Vehicle-Pedestrian (V2P) warning system is conducted to validate the effectiveness of the presented architecture. The proposed framework is expected to provide guidance to the future Digital Twin research, and the architecture we build can serve as the testbed for further research and development of ITS applications on CV and pedestrians.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Dec 2022.
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Citing papers per year: 2023: 2; 2024: 3; 2025: 3.
8 papers.
- 2023Advances and Applications of Computer Vision Techniques in Vehicle Trajectory Generation and Surrogate Traffic Safety Indicatorscited by 4
- 2023Interaction-Aware Personalized Vehicle Trajectory Prediction Using Temporal Graph Neural Networkscited by 2
- 2024Does Twinning Vehicular Networks Enhance Their Performance in Dense Areas?cited by 2
- 2024AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applicationscited by 1
- 2025Towards Intelligent Transportation with Pedestrians and Vehicles In-the-Loop: A Surveillance Video-Assisted Federated Digital Twin Frameworkcited by 1
- 2025Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detectioncited by 1
- 2024The Design of a 3D Character Animation System for Digital Twins in the Metaversecited by 0
- 2025SimPRIVE: a Simulation framework for Physical Robot Interaction with Virtual Environmentscited by 0
- 2025Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection11 Jul 2025
- 2025SimPRIVE: a Simulation framework for Physical Robot Interaction with Virtual Environments30 Apr 2025
- 2025Towards Intelligent Transportation with Pedestrians and Vehicles In-the-Loop: A Surveillance Video-Assisted Federated Digital Twin Framework6 Mar 2025
- 2024AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applications30 Dec 2024
- 2024The Design of a 3D Character Animation System for Digital Twins in the Metaverse10 Jul 2024
- 2024Does Twinning Vehicular Networks Enhance Their Performance in Dense Areas?16 Feb 2024
- 2023Interaction-Aware Personalized Vehicle Trajectory Prediction Using Temporal Graph Neural Networks14 Aug 2023
- 2023Advances and Applications of Computer Vision Techniques in Vehicle Trajectory Generation and Surrogate Traffic Safety Indicators27 Mar 2023