Choi, Jimin (University of Michigan), Anand, Kartikeya (University of Michigan, Ann Arbor), Idris, Husni (NASA), Tran, Huy (University of Illinois at Urbana-Champaign), Li, Max (University of Michigan, Ann Arbor)

Pathfinders in the Sky: Formal Decision-Making Models for Collaborative Air Traffic Control in Convective Weather

Scheduled for presentation during the Invited Session "S23c-Trustworthy AI for Traffic Sensing and Control" (TH-LA-T23), Thursday, November 20, 2025, 16:00−16:20, Coolangata 2

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

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.