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Formal Methods in Air Traffic Management: The Case of Unmanned Aircraft Systems (Invited Lecture)

  • César A. Muñoz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9399)

Abstract

As the technological and operational capabilities of unmanned aircraft systems (UAS) continue to grow, so too does the need to introduce these systems into civil airspace. Unmanned Aircraft Systems Integration in the National Airspace System is a NASA research project that addresses the integration of civil UAS into non-segregated airspace operations. One of the major challenges of this integration is the lack of an on-board pilot to comply with the legal requirement that pilots see and avoid other aircraft. The need to provide an equivalent to this requirement for UAS has motivated the development of a detect and avoid (DAA) capability to provide the appropriate situational awareness and maneuver guidance in avoiding and remaining well clear of traffic aircraft. Formal methods has played a fundamental role in the development of this capability. This talk reports on the formal methods work conducted under NASA’s Safe Autonomous System Operations project in support of the development of DAA for UAS. This work includes specification of low-level and high-level functional requirements, formal verification of algorithms, and rigorous validation of software implementations. The talk also discusses technical challenges in formal methods research in the context of the development and safety analysis of advanced air traffic management concepts.

References

  1. 1.
    Consiglio, M., Chamberlain, J., Muñoz, C., Hoffler, K.: Concept of integration for UAS operations in the NAS. In: Proceedings of 28th International Congress of the Aeronautical Sciences, ICAS 2012, Brisbane, Australia (2012)Google Scholar
  2. 2.
    Denman, W., Muñoz, C.: Automated real proving in PVS via MetiTarski. In: Jones, C., Pihlajasaari, P., Sun, J. (eds.) FM 2014. LNCS, vol. 8442, pp. 194–199. Springer, Heidelberg (2014) CrossRefGoogle Scholar
  3. 3.
    Dutle, A.M., Muñoz, C.A., Narkawicz, A.J., Butler, R.W.: Software validation via model animation. In: Blanchette, J.C., Kosmatov, N. (eds.) TAP 2015. LNCS, vol. 9154, pp. 92–108. Springer, Heidelberg (2015) CrossRefGoogle Scholar
  4. 4.
    FAA Sponsored Sense and Avoid Workshop. Sense and avoid (SAA) for Unmanned Aircraft Systems (UAS), October 2009Google Scholar
  5. 5.
    Goodloe, A.E., Muñoz, C., Kirchner, F., Correnson, L.: Verification of numerical programs: from real numbers to floating point numbers. In: Brat, G., Rungta, N., Venet, A. (eds.) NFM 2013. LNCS, vol. 7871, pp. 441–446. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  6. 6.
    Jenkins, D., Vasigh, B.: The economic impact of Unmanned Aircraft Systems integration in the United States. Economic report of the Association For Unmanned Vehicle Systems International (AUVSI), March 2013Google Scholar
  7. 7.
    Mariano Moscato, César Muñoz, and Andrew Smith. Affine arithmetic and applications to real-number proving. In: Urban, C., Zhang, X. (ed.), Proceedings of the 6th International Conference on Interactive Theorem Proving (ITP 2015), vol. 9236 of Lecture Notes in Computer Science, Nanjing, China, Springer, Heidelberg, August 2015Google Scholar
  8. 8.
    Muñoz, C.: Rapid prototyping in PVS. Contractor Report NASA/CR-2003-212418, NASA, Langley Research Center, Hampton VA 23681–2199, USA, May 2003Google Scholar
  9. 9.
    Muñoz, C., Narkawicz, A.: Formalization of a representation of Bernstein polynomials and applications to global optimization. J. Autom. Reason. 51(2), 151–196 (2013)CrossRefzbMATHGoogle Scholar
  10. 10.
    Muñoz, C., Narkawicz, A., Chamberlain, J.: A TCAS-II resolution advisory detection algorithm. In: Proceedings of the AIAA Guidance Navigation, and Control Conference and Exhibit 2013, number AIAA-2013-4622, Boston, Massachusetts, August 2013Google Scholar
  11. 11.
    Muñoz, C., Narkawicz, A., Chamberlain, J., Consiglio, M., Upchurch, J.: A family of well-clear boundary models for the integration of UAS in the NAS. In: Proceedings of the 14th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference, number AIAA-2014-2412, Georgia, Atlanta, USA, June 2014Google Scholar
  12. 12.
    Muñoz, C., Narkawicz, A., Consiglio, G.: DAIDALUS: detect and avoid alerting logic for unmanned systems. In: Proceedings of the 34th Digital Avionics Systems Conference (DASC 2015), Prague, Czech Republic, September 2015Google Scholar
  13. 13.
    Narkawicz, A., Muñoz, C.: A formally verified generic branching algorithm for global optimization. In: Cohen, E., Rybalchenko, A. (eds.) VSTTE 2013. LNCS, vol. 8164, pp. 326–343. Springer, Heidelberg (2014) CrossRefGoogle Scholar
  14. 14.
    Narkawicz, A., Muñoz, C., Dutle, A.: Formally-verified decision procedures for univariate polynomial computation based on Sturm’s and Tarski’s theorems. J. Autom. Reason. 54(4), 285–326 (2015)CrossRefGoogle Scholar
  15. 15.
    Owre, S., Rushby, J., Shankar, N.: PVS: A prototype verification system. In: Kapur, D. (ed.) Automated Deduction–CADE-11. LNAI, vol. 607, pp. 748–752. Springer, Heidelberg (1992)Google Scholar
  16. 16.
    RTCA SC-147. RTCA-DO-185B, Minimum operational performance standards for traffic alert and collision avoidance system II (TCAS II), July 2009Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.NASA Langley Research CenterHamptonUSA

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