Vehicle 2 Vehicle

Vehicle-to-Vehicle (V2V) communication aims to enhance road safety and efficiency by enabling vehicles to share sensor data and coordinate actions. Current research focuses on improving the reliability and efficiency of V2V data transmission, employing techniques like deep reinforcement learning for resource allocation and federated learning for collaborative model training, often incorporating graph neural networks to handle the dynamic network topology. These advancements are crucial for enabling cooperative perception, improving autonomous driving capabilities, and optimizing resource management in increasingly complex transportation systems.