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Collaborative air traffic flow management: Incorporating airline preferences in rerouting decisions

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  • Murça, Mayara Condé Rocha

Abstract

This paper discusses the air traffic flow management problem under the new operating paradigm of collaborative rerouting. A route and slot allocation model that incorporates flight operator's disutility cost of rerouting to avoid an impacted airspace is proposed to optimally schedule flights into multiple flow constrained areas. In order to evaluate the benefits of a combined rerouting/ground holding control mechanism and assess the impacts of accounting for airline preferences on individual and aggregate system delays, the model is applied to a realistic case of flow management into LaGuardia Airport under capacity constraints caused by convective weather conditions in the transition airspace. The results show that incorporating rerouting as a control action has the potential to reduce flight delays considerably if compared to traditional ground holding based mechanisms. Moreover, the specific flight operators' inputs regarding route preference and cost of rerouting and the route network characteristics have major contributions to individual and system level efficiency. Finally, efficiency-fairness trade-offs are discussed for the multi-resource allocation process based on different fairness schemes.

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  • Murça, Mayara Condé Rocha, 2018. "Collaborative air traffic flow management: Incorporating airline preferences in rerouting decisions," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 97-107.
    • Handle: RePEc:eee:jaitra:v:71:y:2018:i:c:p:97-107
    DOI: 10.1016/j.jairtraman.2018.06.009
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    1. Cai, Kaiquan & Shen, Zhiqi & Luo, Xiaoyan & Li, Yue, 2023. "Temporal attention aware dual-graph convolution network for air traffic flow prediction," Journal of Air Transport Management, Elsevier, vol. 106(C).

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