The field of vehicular communication is rapidly evolving, with a focus on optimizing network management, predictive analytics, security, and cooperative driving. Recent developments have highlighted the potential of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing V2X communication, particularly in 6G networks. The integration of AI and ML models, such as Deep Learning and Reinforcement Learning, has shown remarkable progress in improving the performance, adaptability, and intelligence of V2X systems. Noteworthy papers in this area include:

• Joint Routing and Control Optimization in VANET, which introduces an adaptive joint optimization framework for dynamic vehicular networks.
• 5G Aero: A Prototyping Platform for Evaluating Aerial 5G Communications, which presents a compact UAV optimized for 5G connectivity.
• A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applications, which comprehensively reviews recent advances in AI and ML models applied to 6G-V2X communication.