Vehicle to Everything (V2X) and Edge Computing: A Secure Federated learning-based Lifecycle for UAV-Assisted Vehicle Network: A Survey

The Internet of Vehicles (IoV), integrated with edge computing, revolutionizes communication in smart cities. This paper investigates Unmanned Aerial Vehicle (UAV)-assisted vehicle networks, addressing the growing complexity of connected vehicle systems. The proposed system enhances efficiency, security, and scalability by incorporating Vehicle-to-Everything (V2X) communication, edge computing, and UAV deployment. Federated Learning (FL) creates a secure, privacy-preserving lifecycle for UAV-assisted V2X networks. UAVs serve as edge computing nodes, extending network coverage, performing real-time data acquisition, and enabling fast processing and decision-making. FL supports collaborative vehicle-UAV model training while ensuring data protection. The system lifecycle involves data acquisition, FL-based model development, and secure communication during system adjustments. Scalability, latency, and energy efficiency challenges are explored with proposed solutions. The research demonstrates how UAV-assisted V2X networks improve traffic management, autonomous driving, and emergency response, contributing to safer and more efficient transportation systems.