Paper ID: 2212.04122

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

Sarah H. Q. Li, Avi Mittal, Pierre-Loïc Garoche, Açıkmeşe, Behçet

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.

Submitted: Dec 8, 2022