Reducing Collision Risk in Multi-Agent Path Planning: Application to Air traffic Management

2022/12/08 by Sarah H. Q. Li, Li, Sarah H. Q., Avi Mittal +5
Decision Sciences · Economics, Econometrics and Finance · Engineering · #Air Traffic Management and Optimization #Aviation Industry Analysis and Trends #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Multiagent Systems (cs.MA) #Risk and Portfolio Optimization

paper · pdf · doi:10.48550/arxiv.2212.04122

openalex publication_date 2022/12/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

To minimize collision risks in the multi-agent path planning problem with stochastic transition dynamics, we formulate a Markov decision process congestion game with a multi-linear congestion cost. Players within the game complete individual tasks while minimizing their own collision risks. We show that the set of Nash equilibria coincides with the first-order KKT points of a non-convex optimization problem. Our game is applied to a historical flight plan over France to reduce collision risks between commercial aircraft.

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