One of the effects of the development of air traffic during recent years is the increase of congestion on major airports and their aprons, where ground handling operations take place. Efficiency and safety issues become important on the aprons. The “Integrated Airport Apron Safety Fleet Management – AAS” project aims at setting a decision support system for an efficient and safe management of apron traffic, taking advantage of information gathered by “intelligent” vehicles equipped with on- board positioning and monitoring systems. In this project, we optimize the assignment of vehicles to apron operations. We present a mathematical formulation of the problem and sketch a fast sequential heuristic, which provides efficient assignments based on real-time data on position and status of vehicles and operations. We then discuss how the procedure can reach good trade-offs between efficiency and robustness against unpredicted, but frequent, delays occurring in real- time at airports. The proposed approach has been applied to a major European airport (Berlin’s Tegel), leading to efficiency improvements and reduction of expected delays due to handling operations.
Efficiency and Robustness in a Support Platform for Intelligent Airport Ground Handling
ANDREATTA, GIOVANNI;DE GIOVANNI, LUIGI;CAPANNA, LORENZO;RIGHI, LUCA
2014
Abstract
One of the effects of the development of air traffic during recent years is the increase of congestion on major airports and their aprons, where ground handling operations take place. Efficiency and safety issues become important on the aprons. The “Integrated Airport Apron Safety Fleet Management – AAS” project aims at setting a decision support system for an efficient and safe management of apron traffic, taking advantage of information gathered by “intelligent” vehicles equipped with on- board positioning and monitoring systems. In this project, we optimize the assignment of vehicles to apron operations. We present a mathematical formulation of the problem and sketch a fast sequential heuristic, which provides efficient assignments based on real-time data on position and status of vehicles and operations. We then discuss how the procedure can reach good trade-offs between efficiency and robustness against unpredicted, but frequent, delays occurring in real- time at airports. The proposed approach has been applied to a major European airport (Berlin’s Tegel), leading to efficiency improvements and reduction of expected delays due to handling operations.
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