Data-Driven Cruise-Speed Control Balancing Demand and Capacity for Transatlantic Arrivals at Schiphol under Uncertainties

Abstract

European hub airports face persistent demand-capacity imbalances generating 22.4 million minutes of delays in 2024, costing €2.8 billion. Traditional reactive approaches prove inefficient for long-haul transatlantic flights. Moreover, long-haul flights have historically been granted exemptions from ground delay programs, meaning short-haul flights disproportionately absorb delays during capacity constraints. This research develops an uncertainty-aware cruise speed control strategy for managing transatlantic arrivals to Amsterdam Schiphol Airport. The methodology decomposes arrival time uncertainty using Johnson distributions conditioned on flight status and temporal horizon, continuously monitoring probability that demand at Initial Approach Fixes exceeds capacity. One-time strategic speed adjustments trigger only when exceedance probability surpasses a predetermined threshold of 70 \%. Fast-time simulation of 30 days using BlueSky and EUROCONTROL trajectory data validates the approach. Across 79 interventions, the strategy achieved 35 \% capacity exceedance certainty reductions on average. These required only 8.72 minutes average delay through conservative Mach reductions of 0.01-0.05. The approach offers a practical, environmentally beneficial pathway for long-range air traffic flow management at capacity-constrained hubs.