Parallel Surfaces: Service-Oriented V2X Communications for Autonomous Vehicles

The application of reconfigurable intelligent surfacess (RIS) in the Internet of Vehicles (IoV) is rapidly progressing, with a focus on intelligent signal manipulation, adaptive channel estimation, and real-time reconfiguration to optimize communication performance. While RIS technology holds significant potential for improving connectivity in IoV and vehicle settings, its fixed configuration falls short in meeting the dynamic demands in IoV. To address the diverse requirements of IoV services, including stringent safety norms, societal acceptance, and cost efficiency, this article proposes a parallel surfaces system to facilitate service-oriented V2X communications for autonomous vehicles. By harnessing artificial models of the physical RIS-assisted IoV system, conducting extensive computational experiments, and parallel execution, the proposed system enables real-time monitoring, predictive analysis, and optimization. Parallel intelligence empowers efficient and adaptable channel estimation, configuration, and energy management, thereby establishing a more intelligent and secure RIS-assisted IoV infrastructure. In addition, the parallel surfaces system encompasses descriptive, predictive, and prescriptive intelligence in IoV for addressing coverage gaps, enabling hotspot offloading, facilitating multiple antenna signal transmission, and enhancing high-precision positioning.