What is this project about?

In bad weather, commercial aircraft pilots have to make complex decision quickly to ensure flight safety. When there are rainstorms or cumulonimbus (Cb, a type of cloud associated with thunderstorms) near Hong Kong International Airport, the approaching paths of aircrafts may be affected as these are hazardous to aircraft structure and safety. There are 4 situations that pilots may decide to do or experience: holding, slowdown, missed approach and deviation. The resultant situation, or pilot decision, mainly depends on cloud size, movement and position.

With the support of historical time series of radar data and flight path data, it is possible to build an automatic system to predict pilot decision when they encounter rainstorm or cumulonimbus. This project combines aircraft position and radar data to quantify weather impact on aircraft movement. After quantifying and analyzing data, we hope to build a system to predict the probabilities of different pilot decisions: holding, slowdown, missed approach and deviation. We hope this prediction system can aid the air traffic controller in estimating the weather impact and flight planning.