Airspace Deregulation for UAM: Self-organizing VTOLs in Metropoles

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Huseyin Onder ALDEMIR
Caglar UCLER


Small-scale aviation has been driven extensively by recent technological developments. Distinct micro/small scale mobility modes are being interlined, where automated Vertical Take-Off and Landing Aircraft (VTOLs) are being conceptualized for Urban Air Mobility (UAM) in the form of air taxi, cargo, disaster relief, or medical help. This implicates many simultaneous flights over cities, which is a significant challenge. Traditional air traffic control is customized for commercial aviation, and it is not suitable for the dynamic variation in the flight routes of UAM. Consequently, a literature review is conducted firstly for air traffic management subject to UAM. Then, as a critical finding, a self-organizing model integrating particularly micro/small scale UAM is proposed utilizing the swarm concept to leverage the autonomous behavior of VTOLs. Rules for self-organization are set, which are then discussed in conjunction with available technologies such as Global Positioning System (GPS) and Traffic Alert and Collision Avoidance System (TCAS). Finally, the basic concept definition is elaborated to determine challenges and future research.

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Airbus. (2018). Blueprint for Airspace: The roadmap for the safe integration of autonomous aircraft.

Al Haddad, C., Chaniotakis, E., Straubinger, A., Plötner, K., & Antoniou, C. (2020). Factors affecting the adoption and use of urban air mobility. Transportation Research Part A. 132, 696-712.

Aviation Week. (2020, 12 February). Singapore Links with Airbus On UAM. [online]

Balachandran, S., Munoz, C., & Consiglio, M. (2018). Distributed Consensus to Enable Merging and Spacing of UAS in an Urban Environment. International Conference on Unmanned Aircraft Systems (ICUAS), June 12-15, Dallas, TX, USA.

Bertram, J., Yang, X., Brittain, M. W., & Wei, P. (2019). Online Flight Planner with Dynamic Obstacles for Urban Air Mobility. In AIAA Aviation 2019 Forum, 3625.

Besada, J., Campana, I., Bergesio, L., Bernardos, A., & Miguel, G. (accepted in 2019). Drone flight planning for safe urban operations- UTM requirements and tools. Personal and Ubiquitous Computing, in press.

Bijjahalli, S., Sabatini, R., & Gardi, A. (2019). GNSS Performance Modelling and Augmentation for Urban Air Mobility. Sensors. 19, 4209, 1-24.

Bischoff, J., & Maciejewski, M. (2016). Autonomous Taxicabs in Berlin - A Spatiotemporal Analysis of Service Performance. Transportation Research Procedia, 19(June), 176–186. Available at:

Campion, M., Ranganathan, P., & Faruque, S. (2018). A review and future directions of UAV swarm communication architectures. 2018 IEEE International Conference on Electro/Information Technology (EIT), 0903-0908.

Chung, S. J., Paranjape, A. A., Dames, P., Shen, S., & Kumar, V. (2018). A survey on aerial swarm robotics. IEEE Transactions on Robotics, 34(4), 837-855.

Cohen, M. M. (1996). The Vertiport as an Urban Design Problem. Technical Report SAE Technical Paper.

Cotton, W. B., & Wing, D. J. (2018). Airborne Trajectory Management for Urban Air Mobility. AIAA Aviation Forum, Aviation Technology, Integration, and Operations Conference, June 25-29, Atlanta, Georgia.

Draft Annex to EASA Opinion No 01/2020. (2020). Commission Implementing Regulation (EU) of High-level regulatory framework for the U-space.

EASA Opinion No 01/2020. (2020). High-level regulatory framework for the U-space.

eHang. (2020). The future of transportation: White paper on Urban Air Mobility Systems. [online]

EU. (2016). Warsaw Declaration: Drones as a leverage for jobs and new business opportunities. Warsaw, 24 November 2016 [online]

EU. (2017). Drones Helsinki Declaration, 22 November 2017 [online]

Floreano, D., & Wood, R.J. (2015). Science, technology and the future of small autonomous drones. Nature, 521(7553), 460–466.

Fu, M., Rothfeld, R., & Antoniou, C. (2019). Exploring Preferences for Transportation Modes in an Urban Air Mobility Environment: Munich Case Study. Transportation Research Record, 2673(10), 427–442.

Garcia, G.A., & Keshmiri, S.S. (2016). Biologically inspired trajectory generation for swarming UAVs using topological distances. Aerospace Science and Technology, 54, 312-319.

Gao, C., Zhen, Z., & Gong, H. (2016). A self-organized search and attack algorithm for multiple unmanned aerial vehicles. Aerospace Science and Technology, 54, 229-240.

Garrow, L. A., Ilbeigi, M., & Chen, Z. (2017). Forecasting Demand for On Demand Mobility. 17th AIAA Aviation Technology, Integration, and Operations Conference, American Institute of Aeronautics and Astronautics, Denver, doi:10.2514/6.2017-3280.

Gillissen, A., & Schultz, M. (2018). Formal Modeling of Air Traffic as System-of-Systems- Air Traffic as Systems of Interdependent Operational Decision-Making Processes. 8th International Conference for Research in Air Transportation, June 26-29, Barcelona.

Guterres, M., Jones, S., Orrell, G., & Strain, R. (2017). ADS-B surveillance system performance with small UAS at low altitudes. AIAA SciTech Forum.

Hong, W., Jianhua, L., Chengzhe, L., & Zhe, W. (2020). A provably secure aggregate authentication scheme for unmanned aerial vehicle cluster networks. Peer-to-Peer Networking and Applications, 13(1), 53-63.

Hörl, S. (2016). Implementation of an Autonomous Taxi Service in a Multi-Modal Traffic Simulation Using MATSim, doi:10.13140/rg.2.1.2060.9523.

International Civil Aviation Organization (ICAO). (2013). Performance-Based Navigation Manual (Doc 9613), 4th edition.

Jakaria, A.H.M., & Rahman, M.A. (2018). Formal Analysis of k-Resiliency for Collaborative UAVs. 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), 1, 583-592.

Jung, J., D’Souza, S.N., Johnson, M.A., Ishihara, A.K., Modi, H.C., Nikaido, B., & Hasseeb, H. (2016). Applying Required Navigation Performance Concept for Traffic Management of Small Unmanned Aircraft Systems. Proceedings of the 30th ICAS 2016 Congress of the International Council of the Aeronautics Sciences, Daejeon, Korea, 25–30 September.

Katz, S. M. (2019). Collision avoidance for Urban Air Mobility vehicles using Markov decision processes. Stanford University Project Report: Physical Sciences.

Kochenderfer, M. J., Holland, J. E., & Chryssanthacopoulos, J. P. (2012). Next generation airborne collision avoidance system. Massachusetts Institute of Technology-Lincoln Laboratory Lexington United States, Tech. Rep.

Kochenderfer, M. J. (2015). Decision making under uncertainty: Theory and application. MIT Press.

Koperdekar, P., Rios, J., Prevot, T., Johnson, M., Jung, J., & Robinson III, J. E. (2016). Unmanned Aircraft System Traffic Management (UTM) concept of operations. 16th AIAA Aviation Technology, Integration, and Operations Conference, AIAA 2016-3292, Washington D.C.

Lancovs, D. (2017). Broadcast transponders for low flying unmanned aerial vehicles. Transportation Research Procedia, 24, 370–376.

Lowry, M. R. (2018). Towards high density Urban Air Mobility. AIAA Aviation Forum, Aviation Technology, Integration, and Operations Conference, June 25-29, Atlanta, Georgia.

Luo, Q., & Duan, H. (2017). Distributed UAV flocking control based on homing pigeon hierarchical strategies. Aerospace Science and Technology, 70, 257-264.

Maciejewski, M. (2016). Dynamic Transport Services. In A. Horni, K. Nagel, & K. W. Axhausen, eds. The Multi-Agent Transport Simulation MATSim. London: Ubiquity Press, 145–152.

de Mendonça, R.M., Nedjah, N., & de Macedo Mourelle, L. (2016). Efficient distributed algorithm of dynamic task assignment for swarm robotics. Neurocomputing, 172, 345-355.

Merkert, R., & Bushell, J. (2020). Managing the drone revolution: A systematic literature review into the current use of airborne drones and future strategic directions for their effective control. Journal of Air Transport Management, 89, 101929.

Moore, M. (2017). Uber elevate: eVTOL urban mobility. Rotorcraft Business & Technology Summit, Rotor&Wing International, Ft. Worth, TX.

Mualla, Y., Najjar, A., Daoud, A., Galland, S., Nicolle, C., & Shakshuki, E. (2019). Agent-based simulation of unmanned aerial vehicles in civilian applications: A systematic literature review and research directions. Future Generation Computer Systems, 100, 344-364.

Olson, W. A. (2015). Airborne collision avoidance system X. Massachusetts Institute of Technology-Lincoln Laboratory Lexington United States, Tech. Rep.

Rajendran, S., Srinivas, S., & Grimshaw, T. (2021). Predicting demand for air taxi urban aviation services using machine learning algorithms. Journal of Air Transport Management, 92, 102043.

Rosalie, M., Danoy, G., Bouvry, P., & Chaumette, S. (2016). UAV multilevel swarms for situation management. Proceedings of the 2nd Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use, 49-52.

Rothfeld, R., Balac, M., Ploetner, K. O., & Antoniou C. (2018). Initial analysis of Urban Air Mobility’s transport performance in Sioux Falls. AIAA Aviation Forum, Aviation Technology, Integration, and Operations Conference, June 25-29, Atlanta, Georgia.

Rothfeld, R., Balac, M., & Antoniou C. (2019). Modeling and evaluating urban air mobility – an early research approach. Transportation Research Procedia, 41, 41–44.

Sargolzaei, A., Abbaspour, A., & Crane, C. D. (2020). Control of cooperative Unmanned Aerial Vehicles: Review of applications, challenges, and algorithms. In Optimization, Learning, and Control for Interdependent Complex Networks. Springer, Cham, 229-255.

SESAR JU. (2016). European drones outlook study- Unlocking the value for Europe. Publication Office of the European Union, Luxembourg.

SESAR JU. (2017). U-space: Blueprint. Belgium: The European Commission. doi:10.2829/335092

SESAR JU. (2020). Supporting safe and secure drone operations in Europe- Consolidated report on SESAR U-space research and innovation results. Publication Office of the European Union, Luxembourg.

Straubinger, A., Rothfeld, R., Shamiyeh, M., Büchter, K. D., Kaiser, J., & Plötner, K. O. (2020). An overview of current research and developments in urban air mobility–Setting the scene for UAM introduction. Journal of Air Transport Management, 87, 101852.

Sumitomo Corporation. (2020).

Tahir, A., Böling, J., Haghbayan, M. H., Toivonen, H. T., & Plosila, J. (2019). Swarms of Unmanned Aerial Vehicles–A Survey. Journal of Industrial Information Integration, 16(100106).

Torres, S. (2012). Swarm theory applied to air traffic flow management. Procedia Computer Science, 12, 463-470.

Vascik, P. D., & Hansman, R. J. (2017). Constraint identification in on-demand mobility for aviation through an exploratory case study of Los Angeles. 17th AIAA Aviation Technology, Integration, and Operations Conf.

Vascik, P. D., Balakrishnan, H., & Hansman, R. J. (2018). Assessment of air traffic control for Urban Air Mobility and unmanned systems. 8th International Conference for Research in Air Transportation, June 26-29, Barcelona.

Wang, H., & Rubenstein, M. (2020). Shape formation in homogeneous swarms using local task swapping, Early Access, IEEE Transactions on Robotics. DOI: 10.1109/TRO.2020.2967656

Ward, K. A., Winter, S. R., Cross, D. S., Robbins, J. M., Mehta, R., Doherty, S., & Rice, S. (2021). Safety systems, culture, and willingness to fly in autonomous air taxis: A multi-study and mediation analysis. Journal of Air Transport Management, 91(C).

Wood, K.L. & Greer, J.L. (2009). Function-based synthesis methods in engineering design. In: Formal Engineering Design Synthesis. Publisher: Cambridge University Press, New York. DOI: 10.1017/CBO9780511529627.009

Wooldridge, M. (2009). An Introduction to Multiagent Systems, John Wiley & Sons, 2009.

Youn, W. K., Hong, S. B., Oh, K. R., & Ahn, O. S. (2015). Software Certification of Safety-Critical Avionics Systems: DO-178C and Its Impacts. IEEE Aerospace and Electronic Systems Magazine, 30(4), 4-13.

Zhou, Y., Zhao, H., & Liu, Y. (2020). An evaluative review of the VTOL technologies for unmanned and manned aerial vehicles. Computer Communications, 149, 356-369.