构建实时闭环数字孪生平台，实现虚拟仿真与实车测试无缝联动。
Closed-Loop Hybrid Digital Twin Platform for Connected and Automated Vehicle Validation
- 通过低延迟V2X连接，将实车与高保真仿真环境实时耦合。
- 实车状态同步至虚拟车辆，控制指令反向生成CAN信号实现闭环操控。
- 支持多用户、多场景验证，适用于智能网联汽车全链条测试。
在真实世界部署前，对联网自动驾驶车辆（CAVs）进行全面高效的验证至关重要。尽管基于仿真的测试具备可扩展性，但现有方法往往缺乏与真实车辆和现场数据的无缝集成，限制了其在捕捉动态真实交互方面的保真度。为此，本文提出一种新型实时混合数字孪生平台。其核心创新在于通过低延迟车辆到一切（V2X）通信链路，将高保真CARLA-SUMO联合仿真与实体测试场地及车辆紧密耦合。定制开发的中间件作为关键桥梁，将真实CAV的运动状态同步为仿真中的影子车辆，并将虚拟控制指令转化为可驱动底盘的控制器局域网（CAN）消息，实现闭环控制。详细实现包括使用摄影测量法重建全尺寸资产，以及采用云-边协同架构支持可扩展的多用户运行。实验结果表明，平台具备稳定的同步性能和有效的闭环控制能力，且延迟较低，证实了其在多场景下对CAV验证的实用性。
原文摘要 · Abstract (English)
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.
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