Vehicle to Everything

Vehicle-to-Everything (V2X) communication aims to enhance road safety and efficiency by enabling vehicles to exchange information with each other and infrastructure. Current research focuses on optimizing resource allocation within V2X networks using techniques like graph neural networks and deep reinforcement learning to improve communication reliability and efficiency, particularly for applications such as platooning and adaptive traffic control. These advancements are significant because they promise to improve traffic flow, reduce fuel consumption, and enhance the safety of autonomous and human-driven vehicles, contributing to the development of smarter and more sustainable transportation systems.