Urban Airspace

Urban airspace research focuses on optimizing the management and utilization of airspace above cities, primarily to improve efficiency and safety of drone deliveries and other aerial operations. Current research employs diverse methods, including deep learning models (e.g., transformers, normalizing flows) for tasks like traffic prediction and path planning, and leverages multimodal data sources such as remote sensing imagery, IoT sensor networks, and mobile phone positioning data to create comprehensive urban models. This work is significant for improving urban planning, resource allocation, and the development of intelligent transportation systems, ultimately enhancing city livability and sustainability.