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A Heuristic Search Approach to Find Contrail Avoidance Flight Routes

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AI 2015: Advances in Artificial Intelligence (AI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9457))

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Abstract

Contrails are line-shaped clouds or “condensation trails,” composed of ice particles that are visible behind jet aircraft engines. Contrails can affect the formation of clouds effecting climate change. This paper proposes an integrated model of atmosphere, airspace and flight routing with a Gradient Descent based heuristic search algorithm to find Contrail avoidance trajectories with climb, descent and vector maneuvers. Trade off analysis of Contrails avoidance with fuel burn/CO2 and distance flown is also presented.

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References

  1. Intergovernmental Panel on Climate Change (IPCC), Penner, J.E., Lister, D.H., Griggs, D.J., Dokken, D.J., McFarland, M. (eds.): Aviation and the Global Atmosphere. Cambridge University Press, Cambridge (1999)

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  2. Mannstein, H., Meyer, R., Wendling, P.: Operational detection of contrails from NOAA-AVHRR data. Int. J. Remote Sensing 20, 1641–1660 (1999)

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  3. Mitchell, T.: Machine Learning. McGraw Hill, New York (1997)

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  4. Mannstein, H., Spichtinger, P., Gierens, K.: A note on how to avoid contrail cirrus. Transp. Res. Part D Transport Environ. 10(5), 421–426 (2005)

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Author information

Authors and Affiliations

  1. School of Engineering and IT, University of New South Wales, Canberra, Australia

    Rubai Amin & Sameer Alam

Authors
  1. Rubai Amin
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  2. Sameer Alam
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Corresponding author

Correspondence to Sameer Alam .

Editor information

Editors and Affiliations

  1. The University of Waikato, Hamilton, New Zealand

    Bernhard Pfahringer

  2. The Australian National University, Canberra, Aust Capital Terr, Australia

    Jochen Renz

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© 2015 Springer International Publishing Switzerland

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Amin, R., Alam, S. (2015). A Heuristic Search Approach to Find Contrail Avoidance Flight Routes. In: Pfahringer, B., Renz, J. (eds) AI 2015: Advances in Artificial Intelligence. AI 2015. Lecture Notes in Computer Science(), vol 9457. Springer, Cham. https://doi.org/10.1007/978-3-319-26350-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-26350-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26349-6

  • Online ISBN: 978-3-319-26350-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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