Noncooperative Virtual Queue Coordination via Uncertainty-Aware Correlated Equilibria

TL;DR

This paper introduces a novel noncooperative virtual queue coordination method using chance-constrained correlated equilibria, improving airport surface congestion management while respecting airline autonomy and accounting for uncertainty.

Contribution

It develops a scalable algorithm for chance-constrained correlated equilibria and demonstrates improved delay reduction in realistic airport traffic scenarios.

Findings

Scales to 210 pushbacks per hour

Reduces delay by up to 8.9%

Balances confidence level and cost efficiency

Abstract

Collaborative virtual queueing has been proposed as a mechanism to mitigate airport surface congestion while preserving airline autonomy over aircraft-level pushback decisions. A central coordinator can regulate aggregate pushback capacity but cannot directly control which specific aircraft are released, limiting its ability to steer system-level performance. We propose a noncooperative coordination mechanism for collaborative virtual queueing based on the correlated equilibrium concept, which enables the coordinator to provide incentive-compatible recommendations on aircraft-level pushback decisions without overriding airline autonomy. To account for uncertainty in airlines' internal cost assessments, we introduce chance constraints into the correlated equilibrium formulation. This formulation provides explicit probabilistic guarantees on incentive compatibility, allowing the coordinator to adjust the confidence level with which airlines are expected to follow the recommended actions. We further propose a scalable algorithm for computing chance-constrained correlated equilibria by exploiting a reduced-rank structure. Numerical experiments demonstrate that the proposed method scales to realistic traffic levels up to 210 eligible pushbacks per hour, reduces accumulated delay by up to approximately 8.9% compared to current first-come-first-served schemes, and reveals a trade-off between confidence level, deviation robustness, and achievable cost efficiency.