Go-Around Detection Using Crowd-Sourced ADS-B Position Data

Abstract

The decision of a flight crew to undertake a go-around, aborting a landing attempt, is primarily to ensure the safe conduct of a flight. Although go-arounds are rare, they do cause air traffic disruption, especially in busy airspace, due to the need to accommodate an aircraft in an unusual position, and a go-around can also result in knock-on delays due to the time taken for the aircraft to re-position, fit into the landing sequence and execute a successful landing. Therefore, it is important to understand and alleviate the factors that can result in a go-around. In this paper, I present a new method for automatically detecting go-around events in aircraft position data, such as that sent via the ADS-B system, and apply the method to one year of approach data for Chhatrapati Shivaji Maharaj International Airport (VABB) in Mumbai, India. I show that the method is significantly more accurate than other methods, detecting go-arounds with very few false positives or negatives. Finally, I use the new method to reveal that while there is no one cause for go-arounds at this airport, the majority can be attributed to weather and/or an unstable approach. I also show that one runway (14/32) has a significantly higher proportion of go-arounds than the other (09/27).