Connected Vehicle

Connected vehicles (CVs) leverage vehicle-to-everything (V2X) communication to enhance road safety, efficiency, and sustainability. Current research emphasizes developing robust and scalable communication architectures, often employing digital twin frameworks for simulation and testing, and utilizing machine learning algorithms like reinforcement learning and federated learning for tasks such as traffic signal optimization, collision avoidance, and cooperative perception. This field is significant for its potential to improve traffic flow, reduce accidents, and enable new intelligent transportation system applications, impacting both the scientific understanding of complex transportation networks and the practical design of safer and more efficient roadways.