Airport surface movement operations present a promising opportunity for enhancing airport sustainability, as up to 25% of airport emissions originate from taxiing aircraft. This study explores the use of Electric Towing Vehicles (ETVs) to tow aircraft to runways, eliminating the operational use of aircraft engines during taxiing. Given the high cost of ETVs, their effective deployment is essential. This research adopts a Multi-Agent Pickup and Delivery (MAPD) framework to optimize ETV operations, addressing both the task assignment and path planning aspects of this problem. A novel task assignment method based on Ant Colony Optimization (ACO) is proposed, capable of efficiently scheduling towing and charging tasks for ETVs. The proposed method outperforms benchmark Mixed Integer Linear Programming (MILP) methods in terms of runtime and scalability, while delivering a competitive solution quality. The ACO-based task assignment method is integrated with a state-of-the-art motion planning algorithm based on Priority Based Search (PBS) and Safe Interval Motion Planning (SIMP). The resulting MAPD solution method is evaluated through its application in a high-fidelity simulation of Amsterdam Airport Schiphol (AAS). The simulation results indicate that deploying 22 ETVs at AAS can achieve a 57% reduction in the annual addressable CO2 emissions, while ensuring the economic feasibility of the operational concept.

This report was written as part of the Design Synthesis Exercise, a 10 week project in which groups of 10 members create a design to obtain their bachelor’s degree at the Faculty of Aerospace Engineering. AirEco’s task is to design and develop a revolutionary and sustainable solution for the future of longrange commercial aviation.
This report deals with the final design, in which a longrange commercial (150250 passengers) aircraft with a propulsion system based on renewable energy principles is proposed...