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An Evolutive Environment for Development of Free-Flight

  • Ítalo Oliveira
  • Paulo Cugnasca
  • João CamargoJr.
  • Rubens Fonseca
  • Jobson Silva
Conference paper

Abstract

The risk analysis complexity of the whole air traffic system is very high, and even more the future system, whose technologies and procedures are not accurately defined. This paper proposes a game-like evolutive environment to simulate and evaluate this open system, which is currently changing due to long-term increases of demand and economical factors.

Keywords

Evolutive Environment Strategy Space Hybrid Automaton Conflict Detection International Civil Aviation Organization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Regras do Ar e Serviço de Tráfego Aéreo (IMA100-12). Ministério da Aeronáutica — Departamento de Eletrônica e Proteção ao Vôo, Rio de Janeiro, 1999.Google Scholar
  2. 2.
    Tomlin, C., Pappas, G. J., Sastry, S. Conflict Resolution for Air Traffic Management: a Study in Multi-Agent Hybrid Systems. IEEE Transactions on Automatic Control, 43(4): 509–521, April 1998.CrossRefMATHMathSciNetGoogle Scholar
  3. 3.
    Annual Report of the Council. Documentation of the session of the Assembly in 2004. International Civil Aviation Organization — Doc 9814, 2002.Google Scholar
  4. 4.
    Hoekstra, J. M., van Gent, R. N. H. W., Ruigrok, R. C. J. Designing for safety: the ‘free-flight’ air traffic management concept. Reliability Engineering & System Safety, 75, p. 215-232.Google Scholar
  5. 5.
    Government/Industry Operational Concept for the Evolution of Free Flight. Edition 2. Issued 8-16-00, Free Flight Steering Committee. Radio Technical Commission for Aeronautics RTCA Inc, Washington, DC, 2000.Google Scholar
  6. 6.
    Muñoz, C. et al. On the Formal Verification of Conflict Detection Algorithms. Lecture Notes in Computer Science v. 2144, Springer Verlag, 2001.Google Scholar
  7. 7.
    Prandini, M. et al. A Probabilistic Framework for Aircraft Conflict Detection. In Proceedings of AIAA Guidance, Navigation AND Control Conference, 1999.Google Scholar
  8. 8.
    Paielli, R. A., Erzberger, H. Conflict probability and estimation for free-flight. In Proceedings of th 35th Meeting of the American Institute of Aeronautics and Astronautics, AIAA-97-0001, Reno, 1997.Google Scholar
  9. 9.
    Federal Aviation Administration: Welcome to Free Flight, http://frp1.faa.gov. Accessed in November, 2003.
  10. 10.
    Axelrod, R. The Evolution of Cooperation. Basic Books Inc., 1984.Google Scholar
  11. 11.
    Johansson, S. J. Game Theory and Agents. Licentiate Thesis, University of Karlskrona/Ronneby, 1999.Google Scholar
  12. 12.
    Vismari, L.F. et al. The Influences of Security Concept in Safety-Related Systems: an Approach to CNS/ATM System. WSEAS Transactions on Systems. Issue 1, Volume 2, 2003.Google Scholar
  13. 13.
    ICAO Global Air Navigation Plan for CNS/ATM Systems. Doc 9750, Second Edition. International Civil Aviation Organization, 2002.Google Scholar

Copyright information

© Springer-Verlag London 2004

Authors and Affiliations

  • Ítalo Oliveira
    • 1
  • Paulo Cugnasca
    • 1
  • João CamargoJr.
    • 1
  • Rubens Fonseca
    • 1
  • Jobson Silva
    • 1
  1. 1.Safety Analysis Group, Computer and Digital Systems Engineering Department, Escola PolitécnicaUniversidade de São PauloSão PauloBrazil

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