DeepFlow · enabled Dynamic Air Traffic Flow Configuration for Flow-Centric Airspace Management

Facing the air traffic growth and the challenges in balancing air traffic between geographical sectors, the air traffic control paradigm is shifting from local sector-based solutions to cross-border flow-based approaches. Such flow-centric approaches can be promising to overcome the scalability limits of geographical sectors and optimize the traffic at a regional level. Under this paradigm, this project proposes to develop a dynamic air traffic flow configuration method to assess, predict, manage, and optimize the evolving air traffic flows to enable more efficient flow-centric ATFCM and airspace management. To realize this, first, a flow-pattern extraction module will be developed to identify the major air traffic flows and to characterize the traffic flow structure. Second, with the identified traffic flow pattern, a flow monitor module will be developed to observe the evolution of major traffic flows, such as flow density, flow rate, and flow interactions, integrating as well weather and environmental impact key performance indicators. Third, with the monitored traffic flow data, a traffic flow assessment module will be designed to measure the congestion and flow/capacity imbalance in the airspace, followed by a flow prediction module to provide forecasts of the future air traffic flow features. The fifth module, traffic flow configuration, will investigate the dynamic flow management strategies, such as flow merge and split and flow regulation, based on the flow assessment/prediction outcome. This last module will allow for installation of Flow Regulation Gates to monitor flow interactions and to regulate flights according to flow capacity. An integration of these modules into a flow-centric airspace management framework can pave the way to the dynamic airspace management. Finally, all the developments will be integrated into an innovative platform to validate the concept and methods proposed by the project.