🤖 AI Summary
This study addresses the challenge that existing simulation testing struggles to seamlessly integrate real vehicles and field data, resulting in insufficient high-fidelity replication of dynamic real-world interactions for connected and automated vehicle validation. To overcome this limitation, the authors propose a real-time hybrid digital twin platform that leverages a custom middleware and low-latency V2X communication to map the motion states of physical vehicles into shadow vehicles within a coupled CARLA-SUMO simulation environment. Virtual control commands generated in simulation are transmitted via CAN bus to actuate the physical vehicle’s chassis, establishing a tightly coupled cyber-physical closed loop. Integrating photogrammetry-based modeling and a cloud-edge协同 architecture, the platform demonstrates low latency, high synchronization, and effective closed-loop control across multiple scenarios, significantly enhancing both the efficiency and realism of validation for connected autonomous driving systems.
📝 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 implementation includes using photogrammetry for full-scale asset reconstruction and a cloud-edge collaborative architecture for scalable, multi-user operation. Experimental results demonstrate stable synchronization and effective closed-loop control with low latency, confirming the platform's practicality for multi-scenario CAV verification.