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Trajectory-Based Co-Optimization of Arrival Scheduling and Descent Path Design in the Terminal Maneuvering Area

Yutian Pang, John-Paul Clarke

arXiv:2609.03234Published September 3, 20260 citations
  • eess.SY
  • trajectory

Abstract

Terminal arrival scheduling and descent procedure design are studied in two largely separate literatures. Scheduling models reduce each aircraft to a travel time and deliver target landing times, and fuel-efficient descent procedures are designed one aircraft at a time with the schedule taken as given, although both decide where an arriving aircraft absorbs delay before final approach. Existing formulations therefore cannot trade a slower, earlier-configuring descent against level track miles, a schedule that is efficient in time can be expensive in fuel, and autonomous or reduced-crew operations will need a single trajectory plan that ground automation and the flight management system both accept. To close this gap, we propose a four-dimensional terminal arrival scheduler that selects each aircraft's lateral path extension, glideslope-capture distance, and flap-deployment trigger speeds in one decision. We evaluate every candidate idle-thrust descent offline with a wind-aware backward plan and a six-degree-of-freedom forward simulation that returns descent time, fuel burn, minimum track length, and stabilized-approach feasibility, and a rolling-horizon scheduler commits one verified descent and one extension per aircraft under wake-separation constraints and observed entry winds. Two Atlanta terminal airspace case studies quantify the benefit. We show that co-optimized continuous descents save about 15\% of fleet fuel below saturation in a free-descent environment and that delayed deceleration saves about 23\%, while on the six published Runway 8L arrival flows the charted altitude floors remove 31\% of the design lattice and reduce the savings to 9--10\% and 20--21\%, respectively. We also find that wind moves single-aircraft descent fuel by 34--81\% yet explains at most 4\% of fleet fuel variance, because aircraft-specific wind effects average out across a scenario.

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