Reviews

A scheme for unmanned aerial system traffic management in low-altitude airspace

  • Yongnan JIA
Expand
  • 1.School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing 100083,China
    2.Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education,University of Science and Technology Beijing,Beijing 100083,China
E-mail: ynjia@pku.edu.cn

Received date: 2024-10-13

  Revised date: 2024-12-12

  Accepted date: 2025-04-07

  Online published: 2025-04-25

Abstract

In recent years, with the rapid development of Unmanned Aerial Vehicle (UAV) technology, countries around the world have actively begun to plan and develop low-altitude airspace management systems to ensure the sustainable growth of the low-altitude economy. Existing Air Traffic Management (ATM) systems are primarily designed for manned aircraft operating in medium and high-altitude airspace, making them inadequate for supporting large-scale UAV operations in low-altitude environments. Particularly in application scenarios such as logistics delivery, urban surveillance, and infrastructure inspection, the high-density deployment of UAVs poses new challenges to air traffic management. Consequently, the construction of an efficient, safe, and intelligent Unmanned Aerial System Traffic Management (UTM) framework has become a prominent topic of global research. This paper first reviews the current state of UTM system development both domestically and internationally, with a focus on analyzing similarities and differences among various countries in terms of airspace classification, UTM system architecture, and policy implementation. Then, this paper defines the structure of a typical UTM system and outlines its core technical components, including multi-UAV communication networks, cooperative control, capacity and flow management, conflict detection and resolution, and swarm-level autonomous traffic operations. The main technical challenges currently faced in UTM development are also analyzed in depth. Finally, based on the principles of distributed decision-making, real-time airspace negotiation, and resilient risk management, this study proposes a phased, step-by-step UTM solution tailored to China’‍s low-altitude airspace structure and leveraging the capabilities of the BeiDou Navigation Satellite System (BDS). The proposed system adopts a hierarchical, categorized, zoned, and grid-based management approach, and introduces an innovative “pipeline-style” three-dimensional route network design centered on the “bagua” diagram (a traditional Chinese octagonal structure), to optimize airspace allocation and support the future large-scale autonomous and cooperative operation of UAV.

Cite this article

Yongnan JIA . A scheme for unmanned aerial system traffic management in low-altitude airspace[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2025 , 46(11) : 531399 -531399 . DOI: 10.7527/S1000-6893.2025.31399

References

[1] 深圳市第七届人民代表大会常务委员会 . 深圳经济特区低空经济产业促进条例 [S].深圳: 深圳市第七届人民代表大会常务委员会, 2024
  Standing Committee of the Seventh Shenzhen Municipal People’s Congress. Regulations on the promotion of low-altitude economic industry in Shenzhen special economic zone [S]. Shenzhen: Standing Committee of the Seventh Shenzhen Municipal People’s Congress, 2024 (in Chinese).
[2] NASA. Unmanned aircraft systems traffic management research transition team plan?[R]. Washington, D.C.: NASA, 2019.
[3] FAA. Unmanned aircraft systems traffic management concept of operations V2.0?[R]. Washington, D. C.: FAA, 2020.
[4] JOHNSON M, JUNG J, RIOS J, et al. Flight test evaluation of an unmanned aircraft system traffic management (UTM) concept for multiple beyond-visual-line-of-sight operations?[C]?∥Proceedings of 12th USA/Europe Air Traffic Management Research and Development Seminar. 2017.
[5] FAA. Airspace guidance for small UAS operators[R]. Washington, D.C.: FAA, 2018.
[6] KOPARDEKAR P, RIOS J, PREVOT T, et al. Unmanned aircraft system traffic management (UTM) concept of operations[C]∥AIAA Aviation Forum and Exposition. Reston: AIAA, 2016.
[7] PREVOT T, HOMOLA J, MERCER J. From rural to urban environments: Human/systems simulation research for low altitude UAS traffic management (UTM)[C]?∥16th AIAA Aviation Technology, Integration, and Operations Conference. Reston: AIAA, 2016.
[8] AWEISS A S, OWENS B D, RIOS J, et al. Unmanned aircraft systems (UAS) traffic management (UTM) national campaign Ⅱ[C]?∥2018 AIAA Information Systems-AIAA Infotech @ Aerospace. Reston:AIAA, 2018.
[9] MARCUS J. Unmanned aircraft systems traffic management(UTM): Conflict mitigation approach[C]?∥Mitigation by Technology Workshop. Washington, D.C.: NASA, 2018.
[10] RIOS J, SMITH I, VENKATESAN P, et al. UTM UAS serivce supplier development: Sprint 1 toward technical capability level 4[C]?∥Mitigation by Technology Workshop. Washington, D.C.: NASA, 2018.
[11] UAS traffic management (UTM) Research transition team(RTT) plan[EB/OL]. (2017-1-31) [2020-09-22]. .
[12] FAA. UAS traffic management (UTM) pilot program (UPP)[EB/OL]. (2019-11-14)[2023-09-22]. .
[13] FAA. FAA ATO LAANC concept of operations v2.1[EB/OL].(2020-03-20)[2023-09-22]. .
[14] THIPPHAVONG D P, APAZA R, BARMORE B, et al. Urban air mobility airspace integration concepts and considerations[C]?∥2018 Aviation Technology, Integration, and Operations Conference. Reston: AIAA, 2018.
[15] 廖小罕, 屈文秋, 徐晨晨, 等. 城市空中交通及其新型基础设施低空公共航路研究综述[J]. 航空学报202344(24): 028521.
  LIAO X H, QU W Q, XU C C, et al. A review of urban air mobility and its new infrastructure low-altitude public routes?[J]. Acta Aeronautica et Astronautica Sinica202344(24): 028521 (in Chinese).
[16] 李诚龙, 屈文秋, 李彦冬, 等. 面向eVTOL航空器的城市空中运输交通管理综述[J]. 交通运输工程学报202020(4): 35-54.
  LI C L, QU W Q, LI Y D, et al. Overview of traffic management of urban air mobility (UAM) with eVTOL aircraft[J]. Journal of Traffic and Transportation Engineering202020(4): 35-54 (in Chinese).
[17] NASA. UTM: Air traffic management for low-altitude drones[EB/OL]. (2015-10)[2019-04-12]. .
[18] SESAR. U-space blueprint[EB/OL]. (2017-06-09)[2019-04-12]. .
[19] BARRADO C, BOYERO M, BRUCCULERI L, et al. U-space concept of operations: A key enabler for opening airspace to emerging low-altitude operations?[J]. Aerospace20207(3): 24.
[20] Eurocontrol. U-Space concept of operation(Fourth Edition)[EB/OL]. (2019-10-25)[2023-07-20]. .
[21] 中国民用航空局 . 国家空域基础分类方法 [S].北京:中国民用航空局, 2023.
  Civil Aviation Administration of China. National airspace fundamental classification method? [S]. Beijing: Civil Aviation Administration of China, 2023 (in Chinese).
[22] CHO J, YOON Y. How to assess the capacity of urban airspace: A topological approach using keep-in and keep-out geofence?[J]. Transportation Research Part C: Emerging Technologies201892: 137-149.
[23] LABIB N S, DANOY G, MUSIAL J, et al. A multilayer low-altitude airspace model for UAV traffic management[C]?∥Proceedings of the 9th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications. New York: ACM, 2019.
[24] XU C C, LIAO X H, TAN J M, et al. Recent research progress of unmanned aerial vehicle regulation policies and technologies in urban low altitude[J]. IEEE Access20208: 74175-74194.
[25] BAUM S M. Unmanned aircraft systems traffic management(1st Edition)[M]. Boca Raton. CRC Press. 2021.
[26] SHRESTHA R, BAJRACHARYA R, KIM S. 6G enabled unmanned aerial vehicle traffic management: A perspective[J]. IEEE Access20219: 91119-91136.
[27] LI A, HANSEN M, ZOU B. Traffic management and resource allocation for UAV-based parcel delivery in low-altitude urban space[J]. Transportation Research Part C: Emerging Technologies2022143: 103808.
[28] SHRESTHA R, OH I, KIM S. A survey on operation concept, advancements, and challenging issues of urban air traffic management[J]. Frontiers in Future Transportation20212: 626935.
[29] 金安, 程承旗. 基于全球剖分网格的空间数据编码方法[J]. 测绘科学技术学报201330(3): 284-287.
  JIN A, CHENG C Q. Spatial data coding method based on global subdivision grid[J]. Journal of Geomatics Science and Technology201330(3): 284-287 (in Chinese).
[30] 程承旗, 陈东, 童晓冲. 基于地球剖分网格的无人机数据组织模型初探[J]. 地理信息世界201522(4): 46-50.
  CHENG C Q, CHEN D, TONG X C. The UAV data organization model based on global subdivision grid[J]. Geomatics World201522(4): 46-50 (in Chinese).
[31] 程承旗. 建立健全国家北斗标准促进低空立体交通红绿灯系统建设[J]. 新经济导刊2024(7): 31-35.
  CHENG C Q. Establish and improve national BeiDou standard and promote the construction of the low-altitude 3D traffic light system[J]. New Economy Weekly2024(7): 31-35 (in Chinese).
[32] JAVAID S, SAEED N, QADIR Z, et al. Communication and control in collaborative UAVs: Recent advances and future trends?[J]. IEEE Transactions on Intelligent Transportation Systems202324(6): 5719-5739.
[33] WU G X, LIU Q, XU J F, et al. Energy efficient task caching and offloading in UAV-enabled crowd management[J]. IEEE Sensors Journal202222(18): 17565-17572.
[34] TUN Y K, PARK Y M, TRAN N H, et al. Energy-efficient resource management in UAV-assisted mobile edge computing?[J]. IEEE Communications Letters202125(1): 249-253.
[35] 中国电子科技集团有限公司 . 低空航行系统 [S].北京: 中国电子科技集团有限公司,2024.
  China Electronics Technology Group Corporation. Low-altitude navigation system [S]. Beijing: China Electronics Technology Group Corporation, 2024 (in Chinese).
[36] WU J H, YU Y Z, MA J, et al. Autonomous cooperative flocking for heterogeneous unmanned aerial vehicle group[J]. IEEE Transactions on Vehicular Technology202170(12): 12477-12490.
[37] POPESCU D, STOICAN F, STAMATESCU G, et al. A survey of collaborative UAV-WSN systems for efficient monitoring[J]. Sensors201919(21): 4690.
[38] CHEN J C, LI T Y, ZHANG Y, et al. Global-and-local attention-based reinforcement learning for cooperative behaviour control of multiple UAVs?[J]. IEEE Transactions on Vehicular Technology202473(3): 4194-4206.
[39] JIA Y N, LI Q, ZHANG W C. A distributed cooperative approach for unmanned aerial vehicle flocking?[J]. Chaos201929(4): 043118.
[40] YANG H L, XIE X Z. Energy-efficient joint scheduling and resource management for UAV-enabled multicell networks?[J]. IEEE Systems Journal202014(1): 363-374.
[41] PATRINOPOULOU N, DARAMOUSKAS I, BADEA C A, et al. Dynamic capacity management for air traffic operations in high density constrained urban airspace[J]. Drones20237(6): 395.
[42] WAN Y, TANG J, LAO S Y. Distributed conflict-detection and resolution algorithm for UAV swarms based on consensus algorithm and strategy coordination[J]. IEEE Access20197: 100552-100566.
[43] FAN L J, TANG J, LING Y X, et al. Novel conflict resolution model for multi-UAV based on CPN and 4D trajectories[J]. Asian Journal of Control201618(2): 721-732.
[44] LI Y M, DU W B, YANG P, et al. A satisficing conflict resolution approach for multiple UAVs[J]. IEEE Internet of Things Journal20196(2): 1866-1878.
[45] ALHARBI A, POUJADE A, MALANDRAKIS K, et al. Rule-based conflict management for unmanned traffic management scenarios[C]∥2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC). Piscataway: IEEE Press, 2020.
[46] YANG J, YIN D, NIU Y F, et al. Cooperative conflict detection and resolution of civil unmanned aerial vehicles in metropolis?[J]. Advances in Mechanical Engineering20168(6): 1687814016651195.
[47] PEREZ-LEON H, ACEVEDO J J, MAZA I, et al. Integration of a 4D-trajectory follower to improve multi-UAV conflict management within the U-space context[J]. Journal of Intelligent & Robotic Systems2021102(3): 62.
[48] ACEVEDO J J, CAPITAN C, CAPITIIN J, et al. A geometrical approach based on 4D grids for conflict management of multiple UAVs operating in U-space[C]?∥2020 International Conference on Unmanned Aircraft Systems (ICUAS). Piscataway: IEEE Press, 2020.
[49] TANG X, JI X, LI T. Key technology in multi-UAV conflict detection and resolution strategy?[J]. Transactions of Nanjing University of Aeronautics and Astronautics. 202037(2): 175-186.
[50] RADANOVIC M, OMERI M, PIERA M A. Test analysis of a scalable UAV conflict management framework[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering2019233(16): 6076-6088.
[51] 李安醍, 李诚龙, 武丁杰, 等. 结合跳点引导的无人机随机搜索避撞决策方法?[J]. 航空学报202041(8): 323726.
  LI A T, LI C L, WU D J, et al. Collision avoidance decision method for UAVs in random search combined with jump point guidance[J]. Acta Aeronautica et Astronautica Sinica202041(8): 323726 (in Chinese).
[52] LABIB N S, DANOY G, MUSIAL J, et al. Internet of unmanned aerial vehicles-a multilayer low-altitude airspace model for distributed UAV traffic management[J]. Sensors201919(21): 4779.
[53] HUANG H L, SAVKIN A V, HUANG C. Decentralized autonomous navigation of a UAV network for road traffic monitoring[J]. IEEE Transactions on Aerospace and Electronic Systems202157(4): 2558-2564.
[54] RUMBA R, NIKITENKO A. The wild west of drones: A review on autonomous-UAV traffic-management[C]∥2020 International Conference on Unmanned Aircraft Systems (ICUAS). Piscataway: IEEE Press, 2020.
[55] 国务院, 中央军委. 《关于深化我国低空空域管理改革的意见》出台[J]. 空运商务2010(21): 25.
  Council State, Central Military Commission.“Opinions on deepening the reform of low-altitude airspace management in China” was issued[J]. Air Transport & Business2010(21): 25 (in Chinese).
[56] 张洪海, 李姗, 夷珈, 等. 城市低空航路规划研究综述[J]. 南京航空航天大学学报202153(6): 827-838.
  ZHANG H H, LI S, YI J, et al. Review on urban low-altitude air route planning[J]. Journal of Nanjing University of Aeronautics & Astronautics202153(6): 827-838 (in Chinese).
[57] JARDIN M. Air traffic conflict models[C]?∥AIAA 4th Aviation Technology, Integration and Operations (ATIO) Forum. Reston: AIAA, 2004.
[58] BADEA C, MORFIN V A, RIBEIRO M J, et al. Limitations of conflict prevention and resolution in constrained very low-level urban airspace[C]?∥11th SESAR Innovation Days, 2021.
[59] MUNA S I, MUKHERJEE S, NAMUDURI K, et al. Air corridors: concept, design, simulation, and rules of engagement[J]. Sensors202121: 7536-7553.
[60] LI Z L, LI S, LU J, et al. Air route network planning method of urban low-altitude logistics UAV with double-layer structure[J]. Drones20259(3): 193.
[61] ALLOUCH A, CHEIKHROUHOU O, KOUB?A A, et al. UTM-chain: Blockchain-based secure unmanned traffic management for Internet of drones[J]. Sensors202121(9): 3049.
Outlines

/