Vehicle to Vehicle

Vehicle-to-Vehicle (V2V) communication focuses on enabling direct data exchange between vehicles to enhance safety, efficiency, and automation in transportation systems. Current research emphasizes developing robust communication strategies, particularly at high frequencies, using advanced machine learning models like convolutional LSTMs and transformers to predict channel conditions and fuse sensor data from diverse sources (cameras, radar, LiDAR). This work is crucial for advancing autonomous driving, improving traffic flow management, and enabling new applications like V2V charging and cooperative perception, ultimately impacting the safety and efficiency of future transportation networks.