TY - GEN
T1 - Electric Taxiing with Disruption Management: Assignment of Electric Towing Vehicles to Aircraft
AU - Zoutendijk, M.
AU - van Oosterom, S.J.M.
AU - Mitici, M.A.
PY - 2023
Y1 - 2023
N2 - Reducing aircraft taxiing emissions will deliver a significant contribution to the worldwide goal of net-zero greenhouse gas emissions in the aviation industry. Replacing jet-engine taxiing by towing aircraft with electric towing vehicles is expected to reduce taxiing emissions by roughly 80%. Introducing a fleet of towing vehicles introduces operational challenges to an airport. Although there has been research focused on optimizing the assignment of vehicles to aircraft, such an assignment will require changes during a day of operations, when disruptions such as flight delays occur. This paper proposes two models, a strategic and a disrupted model, with which an adaptive vehicle-to-aircraft assignment is created. The models are formulated as Mixed Integer Linear Problems, and both maximize the number of towed aircraft and minimize the schedule changes for vehicle operators. The approach illustrated includes vehicle and aircraft routing, conflict avoidance, and a model for energy usage. We apply the models to Amsterdam Airport Schiphol, where the disrupted model is able to create assignments that remain the same in subsequent time steps for an average of 55% of the vehicles, on a busy day, when towing all aircraft. Furthermore, the results show that minimizing schedule changes does not come at the expense of fewer towed aircraft, i.e. of smaller emission savings. Lastly, we investigate the impact of fleet size and general on-time performance on the assignments created by the model.
AB - Reducing aircraft taxiing emissions will deliver a significant contribution to the worldwide goal of net-zero greenhouse gas emissions in the aviation industry. Replacing jet-engine taxiing by towing aircraft with electric towing vehicles is expected to reduce taxiing emissions by roughly 80%. Introducing a fleet of towing vehicles introduces operational challenges to an airport. Although there has been research focused on optimizing the assignment of vehicles to aircraft, such an assignment will require changes during a day of operations, when disruptions such as flight delays occur. This paper proposes two models, a strategic and a disrupted model, with which an adaptive vehicle-to-aircraft assignment is created. The models are formulated as Mixed Integer Linear Problems, and both maximize the number of towed aircraft and minimize the schedule changes for vehicle operators. The approach illustrated includes vehicle and aircraft routing, conflict avoidance, and a model for energy usage. We apply the models to Amsterdam Airport Schiphol, where the disrupted model is able to create assignments that remain the same in subsequent time steps for an average of 55% of the vehicles, on a busy day, when towing all aircraft. Furthermore, the results show that minimizing schedule changes does not come at the expense of fewer towed aircraft, i.e. of smaller emission savings. Lastly, we investigate the impact of fleet size and general on-time performance on the assignments created by the model.
UR - http://www.scopus.com/inward/record.url?scp=85191300201&partnerID=8YFLogxK
U2 - 10.2514/6.2023-4219
DO - 10.2514/6.2023-4219
M3 - Conference contribution
T3 - AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023
BT - AIAA AVIATION 2023 Forum
PB - American Institute of Aeronautics and Astronautics Inc. (AIAA)
T2 - AIAA AVIATION 2023 Forum
Y2 - 12 June 2023 through 16 June 2023
ER -