A Mobility Digital Twin is an emerging implementation of digital twin technology in the transportation domain, which creates digital replicas for various physical mobility entities, such as vehicles, drivers, and pedestrians. Although a few work have investigated the applications of mobility digital twin recently, the extent to which it can facilitate safer autonomous vehicles remains insufficiently explored. In this paper, we first propose visualization of mobility digital twin, which aims to augment the existing perception systems in connected and autonomous vehicles through twinning high-fidelity and manipulable geometry representations for causal traffic participants, such as surrounding pedestrians and vehicles, in the digital space. An end-to-end system framework, including image data crowdsourcing, preprocessing, offloading, and edge-assisted 3D geometry reconstruction, is designed to enable real-world development of the proposed visualization of mobility digital twin. We implement the proposed system framework and conduct a case study to assess the twinning fidelity and physical-to-digital synchronicity within different image sampling scenarios and wireless network conditions. Based on the case study, future challenges of the proposed visualization of mobility digital twin are discussed toward the end of the paper.

翻译：移动数字孪生是数字孪生技术在交通领域的一种新兴应用，通过为车辆、驾驶员、行人等各类实体移动对象构建数字副本。尽管近期已有少数研究探讨移动数字孪生的应用，但其在提升自动驾驶安全性方面的潜力仍有待深入挖掘。本文首次提出移动数字孪生的可视化概念，旨在通过为数字空间中的因果交通参与者（如周边行人与车辆）构建高保真、可操控的几何表征，增强网联与自动驾驶汽车的现有感知系统。我们设计了一个包含图像数据众包、预处理、卸载及边缘辅助三维几何重建的端到端系统框架，以实现所提移动数字孪生可视化的实际部署。基于该框架实现系统原型，我们开展了案例研究，评估不同图像采样场景与无线网络条件下的孪生保真度及虚实同步性能。最后，结合案例研究结果，本文探讨了移动数字孪生可视化面临的未来挑战。