An engineless taxi operations system using battery-operated autonomous tow trucks

Abstract

One of the solutions proposed by the aerospace industry to reduce fuel consumption, air pollution and noise at airports is to introduce electric trucks to tow aircraft from the stand to the runway (or vice-versa). However, the introduction of tow trucks increases surface traffic which, from an Air Traffic Controller’s (ATCo) point of view, is undesirable. Many solutions have been proposed to mitigate this increase in workload through the introduction of automated planning and execution. However, most of these solutions suffer from one or more of the following: severe limitations in the size of their solution spaces; inability to schedule and plan routes for multiple active runways simultaneously; and inability to consider battery state-of-charge when assigning tow trucks. In terms of performance testing of such solutions, only singular performance metrics (e.g., number of potential conflicts between vehicles or average taxi time) have been considered in the literature, thus limiting the validity and applicability of the results. This paper details a novel system for taxi operations using autonomous tow trucks in order to improve ground operations and overcome some of the limitations of existing solutions. The system identifies conflict-free solutions that minimise taxi-related delays and taxi route lengths, while maximising the use of the tow trucks for taxi operations. It can cater for multiple active runways and accounts for tow truck battery state-of-charge, as well as limits in the number of tow trucks and charging stations. The proposed algorithm was tested for a large number of scenarios and was evaluated using various performance metrics. The results show that the algorithm is capable of utilising the tow trucks for aircraft taxiing without creating any traffic conflicts. To achieve this, almost 70% of the flights had to be slightly delayed to ensure adequate traffic separation is maintained at all times, with delays of up to 3 minutes. Furthermore, the algorithm was capable of assigning tow trucks to more than 80% of the flights, even with a tow truck fleet as small as 25% of the airfield hourly traffic.