The metaverse employs globally distributed computing and communication infrastructures to construct an immersive digital world. Its continuous synchronization and hyperinteractivity create a dilemma involving tremendous volumes of sensory data and scarce spectrum resources. Connected and automated vehicle (CAV) networks integrate onboard sensing, communication, computation, and storage capabilities to enhance the metaverse. This article introduces an edge intelligence-based mobile crowdsensing (MCS) CAV framework, which studies both perception and transmission dimensions. The metaverse’s cornerstone is high-quality edge sensory data delivery across a geographical distribution. Thus, we construct a CAV crowdsensing-based traffic coverage model. Furthermore, we provide information silos in urban transportation networks as a use case. Simulation results validate the proposed framework’s superiority in improving MCS coverage and perceptual data offloading efficiency. With edge intelligence, such a framework can illuminate the prospect of the convergence between CAV applications and the metaverse.

中文翻译：

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当网联自动驾驶汽车遇上移动群智感知：元宇宙中的感知和传输框架

虚拟宇宙采用全球分布的计算和通信基础设施来构建沉浸式数字世界。其持续同步和超交互性造成了涉及大量传感数据和稀缺频谱资源的困境。互联和自动驾驶车辆 (CAV) 网络集成了车载传感、通信、计算和存储功能，以增强元宇宙。本文介绍了一种基于边缘智能的移动群智感知（MCS）CAV框架，该框架研究了感知和传输维度。 Metaverse 的基石是跨地理分布的高质量边缘传感数据传输。因此，我们构建了一个基于CAV众智感知的交通覆盖模型。此外，我们提供城市交通网络中的信息孤岛作为用例。仿真结果验证了所提出的框架在提高 MCS 覆盖范围和感知数据卸载效率方面的优越性。借助边缘智能，这样的框架可以阐明 CAV 应用程序与元宇宙之间融合的前景。