Pathfinders in the Sky: Formal Decision-Making Models for Collaborative Air Traffic Control in Convective Weather
This research is significant for air traffic controllers and aviation authorities as it provides formal models to understand and improve collaborative decision-making during weather disruptions, an area with little prior research.
This paper addresses the lack of research on multi-agent decision-making in air traffic control during convective weather by formulating decision models for pathfinder operations. It constructs a Markov chain to represent operational state transitions and analyzes its steady-state behavior, while also proposing models for flight-specific acceptance and pathfinder selection strategies.
Air traffic can be significantly disrupted by weather. Pathfinder operations involve assigning a designated aircraft to assess whether airspace that was previously impacted by weather can be safely traversed through. Despite relatively routine use in air traffic control, there is little research on the underlying multi-agent decision-making problem. We seek to address this gap herein by formulating decision models to capture the operational dynamics and implications of pathfinders. Specifically, we construct a Markov chain to represent the stochastic transitions between key operational states (e.g., pathfinder selection). We then analyze its steady-state behavior to understand long-term system dynamics. We also propose models to characterize flight-specific acceptance behaviors (based on utility trade-offs) and pathfinder selection strategies (based on sequential offer allocations). We then conduct a worst-case scenario analysis that highlights risks from collective rejection and explores how selfless behavior and uncertainty affect system resilience. Empirical analysis of data from the US Federal Aviation Administration demonstrates the real-world significance of pathfinder operations and informs future model calibration.