Departure management at major airports relies on Target Off-Block Time (TOBT), a human-declared readiness estimate that is prone to inaccuracy. Sensor-derived predictions from computer-vision turnaround monitoring offer a complementary signal, but their higher update frequency and distinct error profile risk destabilising the departure sequence.

This study evaluates whether Predicted End of Ground handling Time (PEGT) predictions can improve departure sequencing at Amsterdam Airport Schiphol without sacrificing schedule stability. A characterisation of operational PEGT data shows that PEGT becomes more accurate than TOBT within approximately 27 minutes of departure, but produces nearly twice as many updates and exhibits pessimistic bias in the final minutes before off-block. These properties motivate the design of selective acceptance filters.

Using a reconstructed rule-based Departure Manager and counterfactual replay of 21,152 departures across 31 operating days (August 2024), 230 configurations of five conjunctive, interpretable acceptance filters were evaluated via Latin hypercube sampling. Results show that unrestricted PEGT adoption reduces vacated slots by 22.6% but increases late resequencing by 18.6%, confirming that improved accuracy alone does not guarantee operational improvement.

However, selective filtering, predominantly through suppression of frequent and late-stage updates, identifies a regime of 55 configurations (24% of those tested) that simultaneously improve all five metrics relative to the TOBT-only baseline: resequencing (-0.6%), late resequencing (-6.6%), vacated slots (-13.3%), TSAT delay (-1.6%), and on-time performance (+0.2%). These configurations improve both the TOBT-only and naive unrestricted-PEGT baselines on every tested metric, demonstrating that composite use of TOBT and selectively filtered PEGT can transcend the baseline stability–slot adherence trade-off.

The results are based on one month of nominal operations at Amsterdam Airport Schiphol; generalisation to disrupted conditions and other departure management architectures requires further investigation.