Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Airspace Capacity Assessment with Augmented Cell Transmission Model

Version 1 : Received: 23 October 2021 / Approved: 25 October 2021 / Online: 25 October 2021 (12:54:49 CEST)

How to cite: Gao, W.; Liang, M. Airspace Capacity Assessment with Augmented Cell Transmission Model. Preprints 2021, 2021100351 (doi: 10.20944/preprints202110.0351.v1). Gao, W.; Liang, M. Airspace Capacity Assessment with Augmented Cell Transmission Model. Preprints 2021, 2021100351 (doi: 10.20944/preprints202110.0351.v1).

Abstract

Air traffic congestion is caused by the unbalance between increasing traffic demand and saturating capacity. Flight delay not only causes huge economical lost, but also has very negative environmental impact in the whole air transportation system. In order to identify the impact of extended TMA on airport capacity, an airspace capacity assessment method based on augmented cell transmission model was proposed. Firstly, the airspace structure was modeled with points, segments, layers, and cells. Secondly, mixed integer linear programming model was built up with maximum throughput or capacity as the objective function. Finally, genetic algorithm was used to find the optimal result, and the results were validated by comparing with the fast-time simulation results generated by total airspace and airport modeler (TAAM) software. It is found that the proposed method could achieve a relatively accurate result in a much affordable and fast way. The numerical results could be very helpful for air traffic controllers to analyze the dynamic traffic flow entering and exiting TMA, so as to make decisions via reasonable analysis and do planning in advance by referring to the airport capacity.

Keywords

Air transportation; air traffic control; airspace capacity; cell transmission model

Subject

ENGINEERING, Other

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