Vehicle to Infrastructure

Vehicle-to-infrastructure (V2I) communication aims to enhance autonomous driving safety and efficiency by integrating data from vehicles and roadside infrastructure. Current research focuses on improving cooperative perception through sensor fusion techniques, often employing deep learning models like graph neural networks and deep reinforcement learning to optimize resource allocation and data transmission, addressing challenges like communication bandwidth limitations and data asynchrony. This interdisciplinary field is significant for advancing autonomous driving capabilities, particularly in complex urban environments, and for developing more robust and reliable intelligent transportation systems.