Improved Continuous Descent Operations considering environmental and mission related uncertainties

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Along the large scale project Single European Sky (SES), EUROCONTROL issued an ATM masterplan in 2012 to pave the way for the next generation ATM System beyond 2020. Next to the integration of airport processes and the development of a system-wide information management (SWIM), a major pillar of the masterplan targets the implementation of low energy, economic Continuous Descent Operations (CDO) to increase operational efficiency of descent and approach procedures. However, so far implemented CDO cannot demonstrate the expected efficiency gains mainly due to poor flight technical performance of pilots an ATC controllers in determining the right time to issue descent clearances. This in turn relies on the effects of numerous input and disturbance variables, which are relevant for the precise conduct of each CDO, but not yet formally known. A reliable and precise prediction of the Top of Descent (ToD) is therefore not yet available to pilots. The present study aims at overcoming this deficiency towards a more precise modeling and description of causal deterministic input variables and stochastic disturbance variables and the effect of missed flightplan waypoints (especially the ToD). In those often cases where the ToD may not be matched by any reason, the pilot will be given a sound decision support called Improved Descent Advisor to judge whether a rather late or early start of descent should be preferred, always considering current ambient conditions and the individual cost function of that flight. In order to provide robust solutions to the pilot in cooperation with ATC, stochastic optimization techniques will be applied to solve the individual cost function. Consequently the advisor will not only depict the best case but an acceptable 4 D flight regime within which a minimum solver quality will be granted. The objective functions will for the first time consider both economic and ecological efficiency. Along seven work packages, we start with a state-of-the-art for optimized approach procedures focusing on restrictions for existing CDO procedures, and uncertainty handling resulting from partly unknown ambient conditions, aircraft configuration data and their forecast techniques. We so aim at identifying on how to model best energy-optimized CDO through stochastic modeling. Following this first step, a stochastic optimization of all theoretical CDO solutions is undertaken using innovative OR methods, so generating second best CDO solutions. Subsequently, the visualization concept Improved Descent Advisor will be developed and implemented into the air traffic simulation environment at TU Dresden comprising an A320 flight and an experimental air traffic control simulator.