Flight Planning in Free Route Airspaces

Authors Casper Kehlet Jensen, Marco Chiarandini, Kim S. Larsen



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Casper Kehlet Jensen
Marco Chiarandini
Kim S. Larsen

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Casper Kehlet Jensen, Marco Chiarandini, and Kim S. Larsen. Flight Planning in Free Route Airspaces. In 17th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2017). Open Access Series in Informatics (OASIcs), Volume 59, pp. 14:1-14:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
https://doi.org/10.4230/OASIcs.ATMOS.2017.14

Abstract

We consider the problem of finding cheapest flight routes through free route airspaces in a 2D setting. We subdivide the airspace into regions determined by a Voronoi subdivision around the points from a weather forecast. This gives rise to a regular grid of rectangular regions (quads) with every quad having an associated vector-weight that represents the wind magnitude and direction. Finding a cheapest path in this setting corresponds to finding a piece-wise linear path determined by points on the boundaries of the quads. In our solution approach, we discretize such boundaries by introducing border points and only consider segments connecting border points belonging to the same quad. While classic shortest path graph algorithms are available and applicable to the graphs originating from these border points, we design an algorithm that exploits the geometric structure of our scenario and show that this algorithm is more efficient in practice than classic graph-based algorithms. In particular, it scales better with the number of quads in the subdivision of the airspace, making it possible to find more accurate routes or to solve larger problems.
Keywords
  • Flight planning
  • Geometric shortest path
  • Free route airspace
  • Vector weighted paths
  • Vector weighted planar subdivisions

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References

  1. Lyudmil Aleksandrov, Anil Maheshwari, and Jörg-Rüdiger Sack. Approximation algorithms for geometric shortest path problems. In 32nd Annual ACM Symposium on Theory of Computing (STOC), pages 286-295, 2000. Google Scholar
  2. Steve Altus. Effective flight plans can help airlines economize. AERO, 35, 2009. Google Scholar
  3. Marco Blanco, Ralf Borndörfer, Nam-Dung Hoang, Anton Kaier, Adam Schienle, Thomas Schlechte, and Swen Schlobach. Solving Time Dependent Shortest Path Problems on Airway Networks Using Super-Optimal Wind. In 16th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2016), volume 54 of OpenAccess Series in Informatics (OASIcs), pages 12:1-12:15. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2016. URL: http://dx.doi.org/10.4230/OASIcs.ATMOS.2016.12.
  4. John Canny and John Reif. New lower bound techniques for robot motion planning problems. In 28th IEEE Annual Symposium on Foundations of Computer Science (FOCS), pages 49-60, 1987. Google Scholar
  5. Danny Z. Chen. Efficient algorithms for geometric shortest path query problems. In Handbook of Combinatorial Optimization, pages 1125-1154. Springer, 2013. Google Scholar
  6. Danny Z. Chen, Robert J. Szczerba, and John J. Uhran. A framed-quadtree approach for determining Euclidean shortest paths in a 2-D environment. IEEE Transactions on Robotics and Automation, 13(5):668-681, 1997. Google Scholar
  7. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms. MIT Press, 3rd edition, 2009. Google Scholar
  8. Mark de Berg, Otfried Cheong, Marc van Kreveld, and Mark Overmars. Computational Geometry: Algorithms and Applications. Springer, 2008. Google Scholar
  9. Eurocontrol. Free route airspace (FRA). http://www.eurocontrol.int/articles/free-route-airspace. Accessed: 2017-03-28.
  10. Michael L. Fredman and Robert Endre Tarjan. Fibonacci heaps and their uses in improved network optimization algorithms. Journal of the ACM, 34(3):596-615, 1987. Google Scholar
  11. Andrew Freedman. Planes flew from New York to London at near-supersonic speeds due to powerhouse jet stream. Mashable, 9 Jan 2015. http://mashable.com/2015/01/08/jet-stream-new-york-london-flights/ Accessed: 2017-05-30.
  12. Jongrae Kim and João Hespanha. Discrete approximations to continuous shortest-path: Application to minimum-risk path planning for groups of UAVs. In 42nd IEEE Conference on Decision and Control (CDC), pages 1734-1740, 2003. Google Scholar
  13. Anders N. Knudsen, Marco Chiarandini, and Kim S. Larsen. Constraint handling in flight planning. In 23nd International Conference on Principles and Practice of Constraint Programming (CP), Lecture Notes in Computer Science. Springer, 2017. To appear. Google Scholar
  14. Anders Nicolai Knudsen, Marco Chiarandini, and Kim S. Larsen. Vertical optimization of resource dependent flight paths. In 22nd European Conference on Artificial Intelligence (ECAI), pages 639-645, 2016. URL: http://dx.doi.org/10.3233/978-1-61499-672-9-639.
  15. Joseph S. B. Mitchell and Christos H. Papadimitriou. The weighted region problem: Finding shortest paths through a weighted planar subdivision. Journal of the ACM, 38(1):18-73, 1991. Google Scholar
  16. Robert J. Szczerba, Danny Z. Chen, and John J. Uhran. Planning shortest paths among 2D and 3D weighted regions using framed-subspaces. The International Journal of Robotics Research, 17(5):531-546, 1998. Google Scholar
  17. WAFC Washington. The world area forecast system (WAFS) internet file service (WIFS) users guide. https://www.aviationweather.gov/wifs/docs/WIFS_Users_Guide_v4.1.pdf. Accessed: 2017-05-30.
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