C V2x

Cellular Vehicle-to-Everything (C-V2X) communication aims to improve road safety and efficiency by enabling vehicles to exchange information with each other and infrastructure. Current research heavily focuses on optimizing resource allocation and path planning using techniques like graph neural networks and reinforcement learning to enhance communication reliability and minimize latency, particularly for critical safety applications. This work is further supported by the development of large, real-world datasets for training and validating advanced perception models, such as those employing multi-modal fusion and domain adaptation techniques for robust 3D object detection. The resulting advancements have significant implications for autonomous driving, traffic management, and overall transportation system performance.