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Decision support system in tactical air traffic flow management for air traffic flow controllers

Author

Listed:
  • Weigang, Li
  • de Souza, Bueno Borges
  • Crespo, Antonio Marcio Ferreira
  • Alves, Daniela Pereira

Abstract

A distributed decision support system for tactical air traffic flow management is developed for the First Integrated Center of Air Defense and Air Traffic Control (CINDACTA I) in Brasilia. The paper specifies the role of CINDACTA I, looking at the problems of air traffic flow management in Brazil and describing an initial evaluation of the decision support system. The decision process involves a meta-level control approach and reinforcement-learning algorithms that allow air traffic flow controllers and supervisors to acquire knowledge and get assistance to enhance their decision-making. The paper also develops simulations involving egalitarian and prioritization distribution of flight flows for the Sao Paulo Terminal Area.

Suggested Citation

  • Weigang, Li & de Souza, Bueno Borges & Crespo, Antonio Marcio Ferreira & Alves, Daniela Pereira, 2008. "Decision support system in tactical air traffic flow management for air traffic flow controllers," Journal of Air Transport Management, Elsevier, vol. 14(6), pages 329-336.
  • Handle: RePEc:eee:jaitra:v:14:y:2008:i:6:p:329-336
    DOI: 10.1016/j.jairtraman.2008.08.007
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    References listed on IDEAS

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    1. Mukherjee, Avijit, 2004. "Dynamic Stochastic Optimization Models for Air Traffic Flow Management," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2vk8w6nc, Institute of Transportation Studies, UC Berkeley.
    2. Michael O. Ball & Robert Hoffman & Amedeo R. Odoni & Ryan Rifkin, 2003. "A Stochastic Integer Program with Dual Network Structure and Its Application to the Ground-Holding Problem," Operations Research, INFORMS, vol. 51(1), pages 167-171, February.
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    Cited by:

    1. Al Hajj Hassan, Lama & Mahmassani, Hani S. & Chen, Ying, 2020. "Reinforcement learning framework for freight demand forecasting to support operational planning decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).

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