• Project ID AEON
  • Project duration 2020-11-01 > 2020-12-31
  • Cost
    • Total EUR 1.566.750,00
    • EU Contr. EUR 1.444.525,00
  • Status Ongoing

AEON aims at defining a concept of operations focusing on engine-off taxiing techniques and a set of dedicated tools such as fleet management algorithms and supervision interfaces to support the operators. On one hand, the operators will have to invest in and operate a mixed fleet of vehicles, each with different capacities and objectives. On the other hand, depending on the chosen operational strategies, these operations will require the collaboration of different actors at the airport, from ATC to ground handling.

The main research questions that AEON addresses is: "what should the operations performed by taxiing actors and automation be designed to benefit the most from engine-off taxiing-capable aircraft and autonomous tug in terms of safety, capacity and environmental impact?"

In particular, we address the following questions: How to determine in real time efficient, conflict-free routing plans for autonomous and non-autonomous aircraft taxiing from gates to the corresponding runways and the other way around?; How to schedule for taxiing a fleet of towing vehicles during the day of operations? How to dynamically adjust this schedule when operations disruptions occur?; How to manage and adjust real-time collaboration between human operators and automation? What are the costs for an airport to build the required infrastructure that enables electric taxiing? What are the benefits of implementing electric taxiing at an airport?

The AEON project will hence provide tools that should be part of an airport collaborative decision making tool.

The project considers the probable inception of a “taxiing supervision” role in the tower that could either be a dedicated controller or an additional role to the ground control. Based on their experience in other research projects, the consortium will develop an operational concept and formalise it on a documentation derived from the OSED/SPR/INTEROP template of the SESAR2020 industrial research.



This project has received funding from the SESAR Joint Undertaking under the European Union's Horizon 2020 research and innovation programme under grant agreement No 892928

European Union