Closed-Loop Hybrid Digital Twin Platform for Connected and Automated Vehicle Validation
Kanglong Quan, Zhebing Xia, Linfeng Jiang, Hao Yu, Ziheng Qiao, Dapeng Dong, and Dongyao Jia

TL;DR
This paper introduces a real-time hybrid digital twin platform that integrates high-fidelity simulation with physical vehicles for comprehensive CAV validation, enhancing fidelity and scalability.
Contribution
It presents a novel coupling of co-simulation with real vehicles via low-latency V2X communication, enabling closed-loop control and scalable multi-user operation.
Findings
Stable synchronization achieved between simulation and real vehicle.
Effective closed-loop control demonstrated with low latency.
Platform validated for multi-scenario CAV verification.
Abstract
Comprehensive and efficient validation of connected and automated vehicles (CAVs) is critical prior to real-world deployment. While simulation-based testing offers scalability, existing approaches often lack seamless integration with real vehicles and field data, limiting their fidelity in capturing dynamic, real-world interactions. To bridge this gap, this paper proposes a novel real-time hybrid digital twin platform. Its core innovation lies in the tight coupling of a high-fidelity CARLA-SUMO co-simulation with a physical test site and vehicle via a low-latency Vehicle-to-Everything (V2X) communication link. A custom-developed middleware serves as the critical bridge, synchronizing a real CAV's kinematic state as a shadow vehicle in the simulation and translating virtual control commands into chassis-actuating Controller Area Network (CAN) messages for closed-loop control. Detailed…
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