arXiv:2410.00356cs.ROcs.ET2024-10被引 28

构建可实时同步的交通数字孪生系统,提升车路协同安全性与效率。

A Digital Twin Framework for Physical-Virtual Integration in V2X-Enabled Connected Vehicle Corridors

  • 基于真实车路协同走廊,融合C-V2X通信与仿真技术构建数字孪生
  • 实现车辆、信号、通信等多源数据实时同步与行为精确复现
  • 支持信号优化、车辆提醒等反馈应用,适合智慧交通研究者使用

交通信息物理系统(T-CPS)通过融合网络与物理交通系统提升安全性和通行效率。其核心是数字孪生(DT),即通过实时数据交互实现虚拟环境中的仿真、分析与优化。尽管已有研究探索车辆、通信、行人和交通的数字孪生,但涵盖基础设施、车辆、信号、通信等多要素的真实世界验证仍受限于诸多挑战:如难以获取真实联网基础设施、异构多源数据整合困难、实时数据处理要求高,以及数字与物理系统的同步难题。为此,本研究在真实车路协同走廊上构建交通数字孪生系统。依托该走廊的蜂窝车联网(C-V2X)基础设施,结合通信、计算与仿真技术,所提系统能在虚拟环境中准确复现车辆行为、信号时序、通信状态与交通模式。基于已有数据管道,数字系统确保与物理环境的强同步性。此外,该数字孪生具备可扩展、冗余架构,保障数据完整性,支持未来大规模C-V2X部署。通过信号时序调整、车辆提示消息、事故通知等应用,验证了其向物理系统反馈的能力。该数字孪生是T-CPS的关键工具,可实现交通的实时监测、预测与优化,提升交通系统的可靠性与安全性。

原文摘要 · Abstract (English)

Transportation Cyber-Physical Systems (T-CPS) enhance safety and mobility by integrating cyber and physical transportation systems. A key component of T-CPS is the Digital Twin (DT), a virtual representation that enables simulation, analysis, and optimization through real-time data exchange and communication. Although existing studies have explored DTs for vehicles, communications, pedestrians, and traffic, real-world validations and implementations of DTs that encompass infrastructure, vehicles, signals, communications, and more remain limited due to several challenges. These include accessing real-world connected infrastructure, integrating heterogeneous, multi-sourced data, ensuring real-time data processing, and synchronizing the digital and physical systems. To address these challenges, this study develops a traffic DT based on a real-world connected vehicle corridor. Leveraging the Cellular Vehicle-to-Everything (C-V2X) infrastructure in the corridor, along with communication, computing, and simulation technologies, the proposed DT accurately replicates physical vehicle behaviors, signal timing, communications, and traffic patterns within the virtual environment. Building upon the previous data pipeline, the digital system ensures robust synchronization with the physical environment. Moreover, the DT's scalable and redundant architecture enhances data integrity, making it capable of supporting future large-scale C-V2X deployments. Furthermore, its ability to provide feedback to the physical system is demonstrated through applications such as signal timing adjustments, vehicle advisory messages, and incident notifications. The proposed DT is a vital tool in T-CPS, enabling real-time traffic monitoring, prediction, and optimization to enhance the reliability and safety of transportation systems.

数字孪生车路协同C-V2X智能交通

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