Skip to main content
SpringerLink
Log in

Multi-modal Air Trajectory Traffic Management

  • Conference paper
  • First Online:
Intelligent Autonomous Systems 18 (IAS 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 794))

Included in the following conference series:

  • 58 Accesses

Abstract

Although well-established air traffic control methods exist for manned aircraft systems (MAS) and frameworks are being created for Unmanned Aircraft Systems (UAS), the issue of combined MAS-UAS coordination has not been adequately addressed. We propose a lane-based multi-modal traffic management system, called Multi-Modal Air (MM-AIR), which provides efficient and effective strategic deconfliction for MAS and UAS flying in the same airspace, as well as the capability to schedule safe trajectories for other airborne objects (e.g., artillery rounds). The major contributions are: 1. The efficient scheduling of strategically deconflicted flights of platforms with different speeds and air space requirements, and 2. The capability to schedule the safe passage of other trajectories through the lane-based flights.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Federal Aviation Administration. Order JO 7110.65Z, Air Traffic Organization Policy (2021)

    Google Scholar 

  2. Barbagello, J.: Instrument Procedures Handbook. Technical Report FAA-H-8083-16B, Federal Aviation Administration, Washington, DC (2017)

    Google Scholar 

  3. Devasia, S., Heymann, M., Meyer, G.: Automation procedures for air traffic management: a token-based approach. In: Proceedings of the American Control Conference, Anchorage, AK (2002)

    Google Scholar 

  4. Devasia, S., Iamratanakul, D., Chatterji, G., Meyer, G.: Decoupled conflict-resolution procedures for decentralized air traffic control. IEEE-T on Intell. Transp. Syst. 12(2), (2011)

    Google Scholar 

  5. Federal Aviation Administration. Unmanned Aircraft Systems (UAS) Traffic Management (UTM) Concept of Operations, V2.0. Technical report, Federal Aviation Administration (2020)

    Google Scholar 

  6. Yoo, J., Devasia, S.: Provably safe conflict resolution with bounded turn rate for air traffic control. IEEE-T Control Syst. Technol. 21(6), (2013)

    Google Scholar 

  7. AirMap. Five Critical Enablers or Safe, Efficient, and Viable UAS Traffic Management (UTM). Technical report, AirMap, Santa Monica, CA (2018)

    Google Scholar 

  8. Alejo, D., Díaz-Báñez, J.M., Cobano, J.A., Pérez-Lantero, P., Ollero, A.: The velocity assignment problem for conflict resolution with multiple aerial vehicles sharing airspace. J. Intell. Rob. Syst. Theory Appl. 69(1-4), 331–346 (2013)

    Google Scholar 

  9. Alharbi, A., Poujade, A., Malandrakis, K., Petrunin, I., Panagiotakopoulos, D., Tsourdos, A.: Rule-Based conflict management for unmanned traffic management scenarios. In: AIAA/IEEE 39th Digital Avionics Systems Conference (DASC), San Antonio, TX USA (2020)

    Google Scholar 

  10. Balachandran, S., Munoz, C, Consiglio, M.C.: Implicitly coordinated detect and avoid capability for safe autonomous operation of small UAS. In 17th AIAA Aviation Technology, Integration, and Operations Conference, Reston, Virginia. American Institute of Aeronautics and Astronautics (2017)

    Google Scholar 

  11. Blom, H.A.P., Bakker, G.J.: Conflict probability and incrossing probability in air traffic management. In: Proceedings of the 41st IEEE Conference on Decision and Control, 2002, pp 2421–2426, Las Vegas, NV, USA (2002)

    Google Scholar 

  12. Bulusu, V., Sengupta, R., Polishchuk, V., Sedov, L.: Cooperative and Non-cooperative UAS traffic volumes. In: 2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017, Miami, FL, USA (2017)

    Google Scholar 

  13. Coutinho, W.P., Battara, M., Fliege, J.: The Unmanned Aerial Vehicle Routing and Trajectory Optimisation Problem, A Taxonomic Review. Comput. Ind. Eng. 120, 116–128 (2018)

    Article  Google Scholar 

  14. Fluegenschuh, A., Muellenstedt, D.: Flight Planning for unmanned aerial vehicles. In: 4th IMA Conference on Mathematics in Defense, Harwell Oxford, UK, (2015)

    Google Scholar 

  15. Jang, D.S., Ippolito, C.A., Sankararaman, S., Stepanyan, S.: Concepts of airspace structures and system analysis for UAS traffic flows for urban areas. In: AIAA Information Systems-AIAA Infotech @ Aerospace, Grapevine, Texas. American Institute of Aeronautics and Astronautics (2017)

    Google Scholar 

  16. Lappas, V., Zoumponos, G., Kostopoulos, V., Shin, H.Y., Tsourdos, A., Tantarini, M., Shmoko, D., Munoz, J., Amoratis, A., Maragkakis, N., Machairas, T., Trifas, A.: EuroDRONE, A European unmanned traffic management testbed for U-Space. Drones 6(53) (2022)

    Google Scholar 

  17. Murray, C.C., Raj, R.: The multiple flying sidekicks traveling salesman problem: parcel delivery with multiple drones. In: Transportation Research Part C Emerging Technologies (2020)

    Google Scholar 

  18. Rios, J.L.: UAS Traffic Management (UTM) Project Strategic Deconfliction: System Requirements Final Report. Technical Report NASA Report, NASA, Moffet Field, CA (2018)

    Google Scholar 

  19. Rios, J.L., Smith, I.S., Venkatesan, P., Smith, D.R., Baskaran, V., Jurack, S., Iyer, S., Verma, P.: UTM UAS Service Supplier Development, Sprint 2 Toward Technical Capability Level 4. Technical Report NASA/TM-2018-220050, NASA, Moffet Field, CA (2018)

    Google Scholar 

  20. Sedov, L., Polishchuk, V.: Centralized and distributed UTM in layered airspace. In: 8th International Conference on Research in Air Transportation, pp. 1–8 (2018)

    Google Scholar 

  21. Soler, M., Kamgarpour, M., Lloret, J., Lygeros, J.: A hybrid optimal control approach to fuel-efficient aircraft conflict avoidance. IEEE Trans. Intell. Transp. Syst. 17(7), 1826–1838 (2016)

    Article  Google Scholar 

  22. Sunil, E., Hoekstra, J., Ellerbroek, J., Bussink, F., Nieuwenhuisen, D., Vidosavljevic, A., Kern, S.: Metropolis : relating airspace structure and capacity for extreme traffic densities. In: 11th USA/Europe Air Traffic Management Research and Development Seminar, Lisbon, Portugal (2015)

    Google Scholar 

  23. Torabbeigi, M., Lim, G.J., Kim, S.J.: Drone delivery scheduling optimization considering payload-induced battery consumption rates. J. Intell. Rob. Syst. 97, 471–487 (2020)

    Article  Google Scholar 

  24. Tra, M., Sunil, E.., Ellerbroek, J., Hoekstra, J.: Modeling the intrinsic safety of unstructured and layered airspace designs. In: 12th USA/Europe Air Traffic Management Research and Development Seminar, Seattle, Washington, USA (2017)

    Google Scholar 

  25. Weinstein, A.L., Schumacher, C.: UAV scheduling via the vehicle routing problem with time windows. In: Technical Report AFRL-VA-WP-TP-2007-306, Air Force Research Lab, Wright-Patterson AFB, OH (2007)

    Google Scholar 

  26. Thomas C. Henderson David Sacharny and Michael Cline (2020) An efficient strategic deconfliction algorithm for large-scale UAS traffic management. Technical Report UUCS-20-010, University of Utah, Salt Lake City, UT (2020)

    Google Scholar 

  27. Henderson, T.C., Sacharny, D, Cline, M.: An efficient strategic deconfliction algorithm for lane-based large-scale UAV flight planning. Technical Report UUCS-19-005, University of Utah (2019)

    Google Scholar 

  28. Sacharny, D., Henderson, T.: Lane-Based UAS Traffic Management. Springer, Berlin, Germany (2022)

    Google Scholar 

  29. Sacharny, D., Henderson, T., Cline, M.: Large-Scale UAS traffic management (UTM) structure. In: IEEE Multisensor Fusion and Integration Conference, Karlsruhe, Germany (2020)

    Google Scholar 

  30. Sacharny, D., Henderson, T., Guo, E.: A DDDAS protocol for real-time UAS flight coordination. In: InfoSymbiotics/Dynamic Data Driven Applications Systems Conference, Boston, MA (2020)

    Google Scholar 

  31. Sacharny, D., Henderson, T., Marsten, V.: Lane-based large-scale UAS traffic management. IEEE-T Intell. Transp. Syst. 23(10), 18835–18844 (2022). October

    Article  Google Scholar 

  32. Sacharny, D., Henderson, T.C.: A lane-based approach for large-scale strategic conflict management for UAS service suppliers. In: IEEE International Conference on Unmanned Aerial Systems, Atlanta, GA (2019)

    Google Scholar 

  33. Sacharny, D., Henderson, T.C., Guo, E.: A DDDAS protocol for real-time UAS flight coordination. In: InfoSymbiotics/Dynamic Data Driven Applications Systems Conference, Boston, MA (2020)

    Google Scholar 

  34. Sacharny, D., Henderson, T.C.: A lane-based approach for large-scale strategic conflict management for UAS service suppliers. In: 2019 International Conference on Unmanned Aircraft Systems (ICUAS), pages 937–945, Atlanta, GA,. Institute of Electrical and Electronics Engineers (IEEE) (2019)

    Google Scholar 

  35. Sacharny, D., Henderson, T., Wernecke, N.: Dynamic airspace contol via spatial network morphing. In: Dynamic Data Driven Applications Systems Conference, Boston, MA (2022)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Utah, Salt Lake City, UT, 84112, USA

    Thomas C. Henderson & Vista Marston

  2. Blyncsy Inc., Salt Lake City, UT, 84102, USA

    David Sacharny

Authors
  1. Thomas C. Henderson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vista Marston
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David Sacharny
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Thomas C. Henderson .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Kyung Hee University, Yongin-si, Korea (Republic of)

    Soon-Geul Lee

  2. Department of Interdisciplinary Engineering, Daegu Gyeongbuk Institute of Science and DGIST R4-708, Daegu, Korea (Republic of)

    Jinung An

  3. School of Information Science, Japan Advanced Institute of Science and And Technology JAIST, Ishikawa, Japan

    Nak Young Chong

  4. DHBW Karlsruhe, Cooperative State University Baden-Wuerttemberg Karlsruhe, Karlsruhe, Germany

    Marcus Strand

  5. Department of Mechanical and Aerospace Engineering, New York University, New York, NY, USA

    Joo H. Kim

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Henderson, T.C., Marston, V., Sacharny, D. (2024). Multi-modal Air Trajectory Traffic Management. In: Lee, SG., An, J., Chong, N.Y., Strand, M., Kim, J.H. (eds) Intelligent Autonomous Systems 18. IAS 2023. Lecture Notes in Networks and Systems, vol 794. Springer, Cham. https://doi.org/10.1007/978-3-031-44981-9_22

Download citation

Publish with us

Policies and ethics

Search

Navigation