Generative Artificial Intelligence-Empowered Multidomain Internet of Vehicles Systems: Scalability, Efficiency, and Suitability

In the rapidly evolving landscape of aerial–terrestrial–marine integrated transportation, vehicular communication systems are confronted with various challenges, including unpredictable signal fading, the scarcity of spectrum resources, and the complexity of network topologies. This article introduces a novel generative artificial intelligence (GAI)-driven model designed to enhance the Internet of Vehicles (IoV) across these domains. The proposed system enhances situational awareness by seamlessly integrating multisource data, offering a real-time and unified environmental view supporting precise predictive analytics. Additionally, the model employs generative diffusion models (GDMs) in cognitive radio (CR), optimizing spectrum utilization through dynamic sensing and adaptive allocation strategies. Furthermore, the system redefines network performance by enabling real-time configuration adjustments and optimizing communication paths to adapt to ever-changing conditions. Our findings demonstrate that GAI has the potential to significantly improve the scalability, efficiency, and suitability of IoV systems, paving the way for smarter and more resilient vehicular communications in complex multidomain environments.