Helping Reduce Environmental Impact of Aviation with Machine Learning
This work addresses the significant environmental impact of commercial aviation by proposing methods to reduce flight time, which could benefit airlines and the environment.
This paper proposes two methods to reduce the environmental impact of aviation by reducing flight time. It suggests improving winds aloft forecasts for more efficient flight planning and an aircraft routing method that finds the fastest route by considering wind forecast uncertainty and optimizing exploration-exploitation trade-offs.
Commercial aviation is one of the biggest contributors towards climate change. We propose to reduce environmental impact of aviation by considering solutions that would reduce the flight time. Specifically, we first consider improving winds aloft forecast so that flight planners could use better information to find routes that are efficient. Secondly, we propose an aircraft routing method that seeks to find the fastest route to the destination by considering uncertainty in the wind forecasts and then optimally trading-off between exploration and exploitation.