Publication Date

Spring 2023

Degree Type

Master's Project

Degree Name

Master of Science (MS)


Computer Science

First Advisor

Genya Ishigaki

Second Advisor

Faranak Abri

Third Advisor

Saptarshi Sengupta


Reinforcement Learning, Air Traffic Control, Assignment, Airport Assignment, Deep Reinforcement Learning


The volume of air traffic is increasing exponentially every day. The Air Traffic Control (ATC) at the airport has to handle aircraft runway assignments for landing and takeoff and airspace maintenance by directing passing aircraft through the airspace safely. If any aircraft is facing a technical issue or problem and is in a state of emergency, it requires expedited landing to respond to that emergency. The ATC gives this aircraft priority to landing and assistance. This process is very strenuous as the ATC has to deal with multiple aspects along with the emergency aircraft. It is the duty of the ATC to direct the aircraft to the place that is equipped with handling the aircraft. If the ATC does not have immediate answers to the requests from the pilots, then it might result in an aircraft crash and loss of life. This project aims to solve this problem by building a model using Reinforcement Learning that can map an emergency aircraft to the airport in the shortest amount of time.