Visualization of Mobility Digital Twin: Framework Design, Case Study, and Future Challenges
Yueyang Liu, Xiaolong Tu, Dawei Chen, Kyungtae Han, Onur Altintas,, Haoxin Wang, Jiang Xie

TL;DR
This paper introduces a visualization framework for mobility digital twins to enhance perception in autonomous vehicles, involving system design, implementation, and a case study on fidelity and synchronization under various conditions.
Contribution
It proposes a novel visualization system for mobility digital twins in autonomous vehicles, integrating high-fidelity geometry reconstruction and real-world implementation.
Findings
High-fidelity twinning achieved under certain sampling scenarios
System maintains synchronization under specific network conditions
Case study demonstrates potential for safer autonomous vehicle perception
Abstract
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…
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Taxonomy
TopicsDigital Transformation in Industry · Vehicular Ad Hoc Networks (VANETs) · IoT and Edge/Fog Computing
