Analyze possible benefits of real-time taxi flow optimization using actual data

Traffic control on the airport surface is tactical rather than strategic, preventing the optimal use of the available taxiway and runway infrastructure. In the current taxi process the controller has to estimate a number of time windows while optimizing the traffic flow. To compensate for the uncertainties in these time windows and to prevent the runway from not being utilized efficiently, the controllers create buffers by planning a queue of aircraft at the runway. As a result aircraft have to wait while the engines are running which may lead to unnecessary fuel consumption. One of the goals of the described research is to reduce the amount of unnecessary taxi time while engines are running, by reducing the taxi process uncertainties and thus reducing the need of aircraft queuing at the runway. At the same time reducing taxi time uncertainties enables runway sequence planning when the aircraft is still at the gate improving the optimal use of the available runway infrastructure. Our proposed approach is to develop a planning function that will optimize the traffic flow by real-time sequencing the departure traffic at the gate and provide the controller and pilots with timing information. This paper describes the identification of the uncertainties that can be compensated for by our proposed approach and the extent of the possible benefits by analyzing actual taxi traffic flow data from Amsterdam airport.