Artificial Intelligence-Aided Beam Tracking in Autonomous Vehicles: State of the Art and Future Directions

Autonomous vehicles (AVs) require real-time, low-latency, and high-throughput communication to ensure safe and efficient operation. Fifth-generation ($5$G) and beyond communication networks, particularly New Radio (NR) operating at millimeter wave (mmWave) frequencies, offer promising solutions. However, higher frequencies introduce challenges like signal attenuation, blockage, and complexities of beam management. This paper provides a comprehensive survey of $5$G and beyond communication networks, emphasizing their role in vehicle-to-everything (V2X) communication. It uniquely addresses the technical challenges of beam training and management, highlighting the application of artificial intelligence (AI) and machine learning (ML) techniques to optimize beam selection and reduce delays. Furthermore, the paper explores future directions, focusing on AI/ML-driven solutions to enhance beamforming and communication reliability in dynamic AV environments.