Abstract

mpts to manage air traffic by either decreasing delay or increasing flow can have the reverse effect on the other. In the National Airspace System (NAS), flights typically depart at their chosen times, and flow management techniques are implemented in the air in an effort to maximize flow, which could lead to delay for individual aircraft. Other areas of the world allow flights to depart only at predetermined slot times knowing that there is a clear unobstructed path, leading to minimal delays but possibly underutilizing airspace. We propose a new approach in leveraging the highway cell transmission model (CTM) to the airspace in the form of a multi-objective optimization that trades between maximizing throughput and minimizing delay. The model is posed as a multi-commodity traffic flow integer program where the constraints are relaxed slightly from the CTM to examine strategies for achieving optimal throughput and delay. In practice, the model is envisioned to initially run offline to determine a preliminary solution to the initial state of the system. Solutions for subsequent changes in actual state can be determined by running the model online for the incremental state change. Stochastic events such as convective weather clearing times or capacities can be included in the model to better see the benefits and impacts of pre-positioning traffic to take advantage of possible future clearing.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1109/dasc.2009.5347552
https://www.isr.umd.edu/~baras/publications/papers/2009/AlexBaras_DASC2009.pdf,
https://academic.microsoft.com/#/detail/2164963305
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Published on 01/01/2009

Volume 2009, 2009
DOI: 10.1109/dasc.2009.5347552
Licence: CC BY-NC-SA license

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