Traffic-dependent Airborne Delay Buffer Optimization for Efficient Air Traffic Flow Management under Uncertainties

抄録

Air traffic flow management balances demand and capacity strategically by applying various initiatives such as ground delay programs and controlled enroute delays. The delay assigned to each flight is determined by the estimated time of arrival and the maximum allowed airborne delay (buffer) set to absorb uncertainties and minimize arrival runway throughput and capacity loss. Current operations often apply a constant buffer regardless of the projected traffic. This research uses high-fidelity traffic simulations to investigate the effect of a dynamically selected buffer optimizing the daily flow control. Performance is measured by three metrics: ground delay, airborne delay and capacity loss, which assures that runway pressure is maintained. Simulations over 162 days of traffic demonstrate the potential for considerable savings using the proposed method. Furthermore, an initial feasibility investigation of machine learning applied to the dynamic buffer selection problem is performed, and is concluded that, despite a certain loss of optimality and estimation accuracy challenges, such techniques can aid real-life implementation.