Creating a Simulation Environment to Analyze Benefits of Real-time Taxi Flow Optimization Using Actual Data

To make optimal use of the available runway and taxiway infrastructure and to prevent the workload of the controllers becoming a limitation, a route-planning function that generates routes automatically is needed. The uncertainty in the taxi process is an important disturbance in today’s surface operations. To allow for deconfliction in the planning domain, the routes need to include time information. The route-planning function will need to use time-margins to provide a certain level of robustness against disturbances. A determining factor in the selection of the size of the margins is the tradeoff between the (maximum) capacity that can theoretically be achieved in the absence of disturbances and the robustness against disturbances. A key challenge is the identification of the relation needed to specify time margins as a function of traffic density and disturbance statistics. An important uncertainty of the taxi processes is the taxi speed. This paper will describe a method to obtain and quantify taxi traffic flow performance and taxi speed distribution using real world data from Amsterdam airport. Furthermore the development of a simulation environment to evaluate the performance of various route-planning functions for selectable time-margins and disturbance statistics is described. In addition a method is described to extract surface traffic scenarios from real world data. The scenarios are used to verify the fidelity of the surface traffic simulation.Electrical Engineering, Mathematics and Computer Scienc