When Connected and Automated Vehicles Meet Mobile Crowdsensing: A Perception and Transmission Framework in the Metaverse

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.