Abstract
In recent years, Unmanned Aerial Vehicles (UAVs) have attracted attentions from almost every industry. Their low cost, high accessibility, and low-risk compared to human-operated vehicles, created a unique opportunity for a variety of use cases in many application domains. The addition of these tele-operated, and sometimes autonomous, vehicles to the air traffic control environment imposed significant challenges and has been calling for appropriate UAV traffic control systems. The complexity of this situation increases manyfold when the UAVs need to work together as a swarm. Air traffic controllers are used to manage 20 or so aircraft separated according to strict guidelines. A highly dynamic, adaptive, fast, and large swarm of UAVs present unprecedented complexity. Shepherding offers an opportunity to provide a concept of a single sheepdog simultaneously guiding a large sheep flock. We present a logical shepherd that could act both in an autonomous mode or in a tele-operation mode by simply sitting in the hands of a swarm traffic controller. Due to the safety critical nature of the environment, we modified the concept of shepherding by designing an asynchronous shepherding algorithm coupled with a digital twin environment to assess consequences. Once the logical shepherd location and orientation is chosen by the human operator, the influence force vectors start to propagate asynchronously from one aircraft to another, maintaining separation assurance and safety constraints. The updated trajectory intent information of the UAVs gets displayed on the screen for the human operator to see if the change is acceptable or not. If acceptable, the recommendation is made and the UAVs commence to follow the new path.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alam, S., Abbass, H.A., Barlow, M.: Atoms: Air traffic operations and management simulator. IEEE Trans. Intell. Transp. Syst. 9(2), 209–225 (2008). https://doi.org/10.1109/TITS.2008.922877
Alam, S., Tang, J., Abbass, H.A., Lokan, C.: The effect of symmetry in representation on scenario-based risk assessment for air-traffic conflict resolution strategies. In: 2009 IEEE Congress on Evolutionary Computation, pp. 2180–2187. IEEE, Piscataway (2009)
Bekkouche, O., Taleb, T., Bagaa, M.: UAVs traffic control based on multi-access edge computing. In: 2018 IEEE Global Communications Conference (GLOBECOM), pp. 1–6. IEEE, Piscataway (2018)
Cardei, M., Cardei, I., Steinberg, A.: UAS trajectory scheduling system. In: 2018 Annual IEEE International Systems Conference (SysCon), pp. 1–8. IEEE, Piscataway (2018)
Clough, B.T.: Metrics, schmetrics! how the heck do you determine a UAV’s autonomy anyway. Technical Report, Air Force Research Lab Wright-Patterson AFB OH (2002)
Devasia, S., Lee, A.: A scalable low-cost-UAV traffic network (uNet). CoRR abs/1601.01952 (2016). http://arxiv.org/abs/1601.01952
FAA, U.S.F.A.A.: Fact sheet – small unmanned aircraft regulations (part 107). https://www.faa.gov/news/fact_sheets/news_story.cfm?newsId=22615 (2019). Accessed 2019 Oct 17
Johnson, R.D.: Unmanned aircraft system traffic management (UTM) project (2018). https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20180002542.pdf
Liu, M., Wan, Y.: Analysis of random mobility model with sense and avoid protocols for uav traffic management. In: 2018 AIAA Information Systems-AIAA Infotech@ Aerospace, p. 0076 (2018)
Murray, C.C., Chu”, A.G.: The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery. Transp. Res. Part C Emerg. Technol. 54, 86–109 (2015). https://doi.org/10.1016/j.trc.2015.03.005. http://www.sciencedirect.com/science/article/pii/S0968090X15000844
NASA: Unmanned Aircraft System (UAS) Traffic Management (UTM). https://utm.arc.nasa.gov/index.shtml (2019). Accessed 2019 Aug 19
Rattanagraikanakorn, B., Sharpanskykh, A., Schuurman, M.J., Gransden, D., Blom, H., Wagter, C.D.: Characterizing UAS collision consequences in future UTM. In: 2018 Aviation Technology, Integration, and Operations Conference, p. 3031 (2018)
Ren, L., Castillo-Effen, M., Yu, H., Yoon, Y., Nakamura, T., Johnson, E.N., Ippolito, C.A.: Small unmanned aircraft system (SUAS) trajectory modeling in support of UAS traffic management (UTM). In: 17th AIAA Aviation Technology, Integration, and Operations Conference, p. 4268 (2017)
Stolaroff, J.K., Samaras, C., O’ Neill, E.R., Lubers, A., Mitchell, A.S., Ceperley, D.: Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery. Nat. Commun. 9(1), 409 (2018)
Strömbom, D., Mann, R.P., Wilson, A.M., Hailes, S., Morton, A.J., Sumpter, D.J.T., King, A.J.: Solving the shepherding problem: heuristics for herding autonomous, interacting agents. J. R. Soc. Interf. 11(100) (2014). https://browzine.com/articles/52614503
Sudbury, A.W., Hutchinson, E.B.: A cost analysis of amazon prime air (drone delivery). J. Econ. Educ. 16(1), 1–12 (2016)
Tang, J., Alam, S., Lokan, C., Abbass, H.A.: A multi-objective approach for dynamic airspace sectorization using agent based and geometric models. Transp. Res. Part C Emerg. Technol. 21(1), 89–121 (2012)
Van Pham, V., Tang, J., Alam, S., Lokan, C., Abbass, H.A.: Aviation emission inventory development and analysis. Envir. Model. Softw. 25(12), 1738–1753 (2010)
Wang, B., Xie, J., Wan, Y., Guijarro Reyes, G.A., Garcia Carrillo, L.R.: 3-d trajectory modeling for unmanned aerial vehicles. In: AIAA Scitech 2019 Forum, p. 1061 (2019)
Zhao, W., Tang, J., Alam, S., Bender, A., Abbass, H.A.: Evolutionary-computation based risk assessment of aircraft landing sequencing algorithms. In: Distributed, Parallel and Biologically Inspired Systems, pp. 254–265. Springer, Berlin (2010)
Acknowledgements
This project is partially funded by an Australian Research Council Discovery Grant DP160102037 and partially funded by the Office of Naval Research Global.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
El-Fiqi, H., Kasmarik, K., Abbass, H.A. (2021). Logical Shepherd Assisting Air Traffic Controllers for Swarm UAV Traffic Control Systems. In: Abbass, H.A., Hunjet, R.A. (eds) Shepherding UxVs for Human-Swarm Teaming. Unmanned System Technologies. Springer, Cham. https://doi.org/10.1007/978-3-030-60898-9_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-60898-9_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-60897-2
Online ISBN: 978-3-030-60898-9
eBook Packages: EngineeringEngineering (R0)