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Noncooperative Coordination for Decentralized Air Traffic Management

Jaehan Im

TL;DR

A unified perspective on noncooperative coordination is developed, in which system-level outcomes emerge by designing incentives and assigning signals that reshape individual optimality rather than imposing cooperation or enforcement.

Abstract

Decentralized air traffic management requires coordination among self-interested stakeholders operating under shared safety and capacity constraints, where conventional centralized or implicitly cooperative models do not adequately capture this setting. We develop a unified perspective on noncooperative coordination, in which system-level outcomes emerge by designing incentives and assigning signals that reshape individual optimality rather than imposing cooperation or enforcement. We advance this framework along three directions: scalable equilibrium engineering via reduced-rank and uncertainty-aware correlated equilibria, decentralized mechanism design for equilibrium selection without enforcement, and structured noncooperative dynamics with convergence guarantees. Beyond these technical contributions, we discuss core design principles that govern incentive-compatible coordination in decentralized systems. Together, these results establish a foundation for scalable, robust coordination in safety-critical air traffic systems.

Noncooperative Coordination for Decentralized Air Traffic Management

TL;DR

A unified perspective on noncooperative coordination is developed, in which system-level outcomes emerge by designing incentives and assigning signals that reshape individual optimality rather than imposing cooperation or enforcement.

Abstract

Decentralized air traffic management requires coordination among self-interested stakeholders operating under shared safety and capacity constraints, where conventional centralized or implicitly cooperative models do not adequately capture this setting. We develop a unified perspective on noncooperative coordination, in which system-level outcomes emerge by designing incentives and assigning signals that reshape individual optimality rather than imposing cooperation or enforcement. We advance this framework along three directions: scalable equilibrium engineering via reduced-rank and uncertainty-aware correlated equilibria, decentralized mechanism design for equilibrium selection without enforcement, and structured noncooperative dynamics with convergence guarantees. Beyond these technical contributions, we discuss core design principles that govern incentive-compatible coordination in decentralized systems. Together, these results establish a foundation for scalable, robust coordination in safety-critical air traffic systems.
Paper Structure (19 sections, 3 equations, 4 figures)

This paper contains 19 sections, 3 equations, 4 figures.

Table of Contents

  1. Introduction
  2. Research Program: Noncooperative coordination
  3. Equilibrium engineering and scalable computation
  4. Reduced-rank correlated equilibria my_rrce
  5. Uncertainty-aware correlated coordination
  6. Mechanism design for noncooperative coordination
  7. Trading-based equilibrium selection (TACo) my_taco
  8. Iterative negotiation with oversight my_iteartive
  9. Noncooperative dynamics and equilibrium steering
  10. Noncooperative dynamics in congestion mitigation my_brd
  11. Dynamic incentive design for equilibrium steering
  12. Design Principles for Decentralized ATM Coordination
  13. Incentive compatibility
  14. Convergence guarantees
  15. Authority-autonomy trade-off
  16. ...and 4 more sections

Figures (4)

  • Figure 1: Decentralized runway allocation scenario. Multiple airline-specific departure queues compete for limited runway capacity. Each airline selects pushback or runway assignment actions based on its own delay cost, while a coordinator broadcasts correlated signals to improve system-level efficiency. The resulting game models noncooperative competition over shared departure resources.
  • Figure 2: Equilibrium selection in decentralized arrival sequencing. Different arrival orderings satisfy time-separation constraints, creating multiple feasible equilibria with conflicting airline preferences. Trading auction for Consensus (TACo) enables incentive-compatible selection without centralized enforcement.
  • Figure 3: Decentralized sector overload mitigation through schedule adjustment. Left: a sector experiences congestion due to overlapping flight trajectories. Right: decentralized schedule shifts ($\Delta t$) redistribute traffic temporally, alleviating overload without centralized enforcement.
  • Figure 4: Equilibrium steering in a congestion game. The simplex represents the joint strategy space, and the inner white triangle denotes a non-convex feasibility constraint. From an initial state (green), dynamic incentive signals guide the best-response trajectory toward a desired equilibrium (red) while maintaining feasibility.

Theorems & Definitions (2)

  • Definition 1: Correlated equilibrium
  • Definition 2: Chance-constrained correlated equilibrium