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Center for Nonlinear Studies |
All large transport aircraft are required to be equipped with a collision avoidance s ystem that instructs pilots how to maneuver to avoid collision with other aircraft. The uncertainty in pilot behavior makes developing a robust collision avoidance logic challenging. This presentation will discuss an automated approach for optimizing collision avoidance logic based on probabilistic models of aircraft behavior and a performance metric that balances the competing objectives of maximizing safety and minimizing alert rate. The approach involves framing the problem of collision avoidance as a multiagent Markov decision process that is solved offline using dynamic programming. This presentation will also discuss issues with coordination between aircraft with imperfect state information and unreliable communication.
Host: Robert Ecke