Vehicle Road Cloud

Vehicle road cloud (VRC) research focuses on integrating vehicles, roadside infrastructure, and cloud computing to enhance safety, efficiency, and intelligence in transportation systems. Current efforts center on developing algorithms for real-time risk assessment (e.g., using 4D occupancy grids and federated learning for driver scoring), efficient task scheduling in vehicular clouds (e.g., employing graph neural networks and reinforcement learning), and robust validation methods using mixed digital twins. This interdisciplinary field is significantly impacting autonomous driving, smart city development, and the broader adoption of connected and automated vehicles by improving traffic management, enhancing safety features, and optimizing resource allocation.