Toward A Traffic Metaverse With Shared Vehicle Perception

Ahmad Ahilal, Tristan Braud, Lik-Hang Lee, Hang Chen, Pan Hui

Abstract: The emergence of the Metaverse enables the creation of alternative spaces at the intersection between digital and physical through the replication of physical events and objects within physical-digital twins. In this article, we apply such twins to connected vehicles within a Traffic Metaverse as an intermediate platform for the shared perception of the road environment. The platform builds a real-time digital copy of the road conditions to serve vehicular applications on a city scale through ubiquitous sensing, reliable and low-latency communications, artificial intelligence, and extended reality. This article focuses on collaboratively building virtual 3D maps of road networks that provide road users with a pervasive view of the road conditions to increase situational awareness. Through vehicle-to-everything (V2X) cooperative perception, such a Metaverse platform expands the driver's visibility beyond the vehicle's line of sight. The platform also enables virtual remote access to monitor and forecast traffic ahead of space and time.