Design of a human-in-the-loop aircraft taxi optimisation system using autonomous tow trucks

Abstract

One of the solutions proposed by the aerospace industry to reduce fuel consumption, air pollution and noise at an airport consists of using electric tow trucks to tow aircraft from the gate to the runway (or vice-versa). However, the introduction of tow trucks would result in an increase in vehicle traffic at the airport, potentially increasing the workload of Air Traffic Controllers (ATC). This paper proposes an algorithm – based on Dijkstra’s algorithm – and a Human Machine Interface (HMI) concept to optimise airport taxi operations with autonomous tow trucks at a strategic level, while keeping ATC in the loop. Preliminary tests of the algorithm have been carried out using simulated traffic data for Malta International Airport (MIA) and the results show that the algorithm can be tuned to minimise the average vehicle taxi delay or the number of unresolved vehicle conflicts. It is also shown that, in certain cases, both the taxi delay and the number of conflicts can be reduced through a minor adjustment of the Off-Block Time (OBT) of departing aircraft.