Carbon footprint assessment due to airport operations is often required by environmental regulations. Aircraft contribute to local air pollution during the Landing and Take Off cycle. A big portion of the time aircraft spend on the ground is taken by taxi operations. Taxi times also increase at higher rates than traffic demand because of congestion at airports. Several measures are explored in the literature regarding the mitigation of taxi related emissions. These measures are often assessed by means of analytical approaches. In this article, the authors introduce a new micro simulation approach to assess aircraft ground movements with the aim of providing a more realistic estimation of taxi times. The approach is based on the definition of a discrete event model using a generic simulation software, AnyLogic 7. The new model is then used to assess the potential benefits and impacts deriving from the introduction of an environmental friendly taxi procedure at Lisbon International Airport. The simulated procedure envisages the utilization of TaxiBot, a semi-robotic towbarless tractor suitable for dispatch towing at medium to large airports. Results prove the alternative measure would potentially lead to environmental benefits in terms of fuel saved and emissions reduction. Considering an average day, both airports and airlines would gain in terms of, respectively, emitted pollutants and operational costs. Starting from these observations, possibilities for further research are explored.

Micro-simulation of airport taxiing procedures to improve operation sustainability: Application of semi-robotic towing tractor / Khammash, Laura; Mantecchini, Luca; Reis, Vasco. - ELETTRONICO. - (2017), pp. 8005587.616-8005587.621. (Intervento presentato al convegno 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 tenutosi a Napoli nel Giugno 2017) [10.1109/MTITS.2017.8005587].

Micro-simulation of airport taxiing procedures to improve operation sustainability: Application of semi-robotic towing tractor

MANTECCHINI, LUCA;
2017

Abstract

Carbon footprint assessment due to airport operations is often required by environmental regulations. Aircraft contribute to local air pollution during the Landing and Take Off cycle. A big portion of the time aircraft spend on the ground is taken by taxi operations. Taxi times also increase at higher rates than traffic demand because of congestion at airports. Several measures are explored in the literature regarding the mitigation of taxi related emissions. These measures are often assessed by means of analytical approaches. In this article, the authors introduce a new micro simulation approach to assess aircraft ground movements with the aim of providing a more realistic estimation of taxi times. The approach is based on the definition of a discrete event model using a generic simulation software, AnyLogic 7. The new model is then used to assess the potential benefits and impacts deriving from the introduction of an environmental friendly taxi procedure at Lisbon International Airport. The simulated procedure envisages the utilization of TaxiBot, a semi-robotic towbarless tractor suitable for dispatch towing at medium to large airports. Results prove the alternative measure would potentially lead to environmental benefits in terms of fuel saved and emissions reduction. Considering an average day, both airports and airlines would gain in terms of, respectively, emitted pollutants and operational costs. Starting from these observations, possibilities for further research are explored.
2017
5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings
616
621
Micro-simulation of airport taxiing procedures to improve operation sustainability: Application of semi-robotic towing tractor / Khammash, Laura; Mantecchini, Luca; Reis, Vasco. - ELETTRONICO. - (2017), pp. 8005587.616-8005587.621. (Intervento presentato al convegno 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 tenutosi a Napoli nel Giugno 2017) [10.1109/MTITS.2017.8005587].
Khammash, Laura; Mantecchini, Luca; Reis, Vasco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/609082
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