Review on research of low-altitude airspace capacity evaluation

ZHANG Hong-hai; YI Jia; LI Shan; LIU Hao; ZHONG Gang

doi:10.19818/j.cnki.1671-1637.2023.06.003

Volume 23 Issue 6

Dec. 2023

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ZHANG Hong-hai, YI Jia, LI Shan, LIU Hao, ZHONG Gang. Review on research of low-altitude airspace capacity evaluation[J]. Journal of Traffic and Transportation Engineering, 2023, 23(6): 78-93. doi: 10.19818/j.cnki.1671-1637.2023.06.003

Citation:

ZHANG Hong-hai, YI Jia, LI Shan, LIU Hao, ZHONG Gang. Review on research of low-altitude airspace capacity evaluation[J]. Journal of Traffic and Transportation Engineering, 2023, 23(6): 78-93. doi: 10.19818/j.cnki.1671-1637.2023.06.003

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Review on research of low-altitude airspace capacity evaluation

doi: 10.19818/j.cnki.1671-1637.2023.06.003

1.
School of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China
2.
School of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China

Funds:

National Natural Science Foundation of China 71971114

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Author Bio:
ZHANG Hong-hai(1979-), male, professor, PhD, honghaizhang@nuaa.edu.cn
Received Date: 2023-05-19
Publish Date: 2023-12-25

Abstract

Abstract

The basic definition of airspace capacity was combed. The origin and development of airspace capacity evaluation methodology research were reviewed. The main findings of four typical airspace capacity evaluation methods (evaluation method based on mathematical calculation models, radar simulator evaluation method based on controller workloads, evaluation method based on computer simulation modeling, and evaluation method based on data-driven) were summarized. Combined with the current situation and reform needs of China's airspace management, a framework for the low-altitude airspace capacity evaluation was proposed. The low-altitude airspace classification and air route planning, landing and take-off airport location layout and capacity evaluation, influencing factors analysis and evaluation methods of low-altitude airspace capacity were introduced, respectively. Future development trend was predicted. Research results show that the classification and planning of low-altitude airspace is the basic premise of capacity evaluation, and the complexity of the low-altitude airspace environment should be fully considered, combined with the performance of aircraft and scientific planning of application scenarios. Landing and take-off airports are key nodes in the low-altitude airspace environment. The site location and internal structure will directly affect the overall low-altitude airspace capacity level. The influencing factors analysis on the low-altitude airspace capacity is a key step and serves as a cross-validation with the results of low-altitude airspace capacity evaluation. At present, a mature methodological system for the low-altitude airspace capacity evaluation has not been developed. Three methods are mainly introduced, which are the threshold-based airspace capacity evaluation method, geometrical topology-based airspace capacity evaluation method, and control-variable-based airspace capacity evaluation method. In general, the low-altitude airspace capacity evaluation is an important content to realize the rational allocation of low-altitude airspace resources and ensure the safe and efficient low-altitude airspace operation, and it should be combined with the characteristics of China's airspace management to carry out locally adapted research on the low-altitude airspace capacity evaluation method and pilot validation.
- air transport,
- air traffic management,
- airspace management,
- capacity evaluation,
- low-altitude airspace capacity,
- system framework

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References(106)

References

[1]	ZHOU Xiong-fei, HU Ming-hua. An overview on airspace capacity evaluation[J]. Journal of Civil Aviation Flight University of China, 2016, 27(6): 37-40. (in Chinese)
[2]	BOWEN E, PEARCEY T. Delays in the flow of air traffic[J]. The Aeronautical Journal, 1948, 52(448): 251-258.
[3]	FAA. FACT1: capacity needs in the national airspace system[R]. Washington DC: FAA, 2004.
[4]	FAA. FACT2: capacity needs in the national airspace system[R]. Washington DC: FAA, 2007.
[5]	FAA. FACT3: airport capacity needs in the national airspace system[R]. Washington DC: FAA, 2015.
[6]	BULUSU V, SENGUPTA R, POLISHCHUK V, et al. Cooperative and non-cooperative UAS traffic volumes[C]//IEEE. 2017 International Conference on Unmanned Aircraft Systems (ICUAS). New York: IEEE, 2017: 1673-1681.
[7]	BULUSU V, POLISHCHUK V. A threshold based airspace capacity estimation method for UAS traffic management[C]// IEEE. 2017 Annual IEEE International Systems Conference. New York: IEEE, 2017: 1-7.
[8]	SALLEH M F B, CHI Wan-chao, WANG Zhen-kun, et al. Preliminary concept of adaptive urban airspace management for unmanned aircraft operations[C]//AIAA. 2018 AIAA Information Systems Infotech@Aerospace. Reston: AIAA, 2018: 1-12.
[9]	QUAN Quan, LI Gang, BAI Yi-qin, et al. Low altitude UAV traffic management: an introductory overview and proposal[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(1): 323238. (in Chinese)
[10]	PEARCEY T. Delays in landing of air traffic[J]. Aeronautical Journal, 1950, 52(456): 799-812.
[11]	BLUMSTEIN A. The landing capacity of a runway[J]. Operations Research, 1959, 7(6): 752-763. doi: 10.1287/opre.7.6.752
[12]	HOOTON E N, GALLIHER H P, WARSKOW M A, et al. Operational evaluation of airport runway design and capacity: a study of methods and techniques[R]. New York: DTIC, 1963.
[13]	RATNER R S, SIDDIQUEE W, GLASER M B, et al. A methodology for evaluating the capacity of air traffic control systems[R]. Menlo Park: Stanford Research Institute, 1970.
[14]	JANIC M, TOSIC V. Terminal airspace capacity model[J]. Transportation Research Part A: General, 1982, 16(4): 253-260. doi: 10.1016/0191-2607(82)90052-8
[15]	JANIC M, TOSIC V. En route sector capacity model[J]. Transportation Science, 1991, 25(4): 299-307. doi: 10.1287/trsc.25.4.299
[16]	FAA. Airport capacity and delay[R]. Washington DC: FAA, 1983.
[17]	TOFUKUJI N. An enroute ATC simulation experiment for sector capacity estimation[J]. IEEE Transactions on Control Systems Technology, 1993, 1(3): 138-143. doi: 10.1109/87.251881
[18]	GILBO E P. Airport capacity: representation, estimation, optimization[J]. IEEE Transactions on Control Systems Technology, 1993, 1(3): 144-154. doi: 10.1109/87.251882
[19]	WANG Chao, ZHANG Xin-yue, XU Xiao-hao. Simulation study on airfield system capacity analysis using SIMMOD[C]// IEEE. 2008 International Symposium on Computational Intelligence and Design. New York: IEEE, 2008: 87-90.
[20]	MAJUMDAR A, OCHIENG W, POLAK J. Estimation of European airspace capacity from a model of controller workload[J]. Journal of Navigation, 2002, 55(3): 381-403. doi: 10.1017/S037346330200190X
[21]	WEN Yuan-yuan, DAI Fu-qing. Terminal area capacity assessment based on TAAM[J]. Journal of Civil Aviation Flight University of China, 2013, 24(6): 9-14. (in Chinese)
[22]	SUNIL E, HOEKSTRA J M, ELLERBROEK J, et al. Metropolis: relating airspace structure and capacity for extreme traffic densities[C]//FAA. Proceedings of the 11th USA/Europe Air Traffic Management Research and Development Seminar (ATM2015). Washington DC: FAA, 2015: 23-26.
[23]	SWEDISH W J. Upgraded FAA airfield capacity model, Volume 1: supplemental users guide[R]. Washington DC: FAA, 1981.
[24]	SWEDISH W J. Upgraded FAA airfield capacity model, Volume 2: technical description of revisions[R]. Washington DC: FAA, 1981.
[25]	LEE D A, KOSTIUK P F, HEMM R V, et al. Estimating the effects of the terminal area productivity programs[R]. Washington DC: NASA, 1997.
[26]	LEE D A, NELSON C, SHAPIRO G. The aviation system analysis capability airport capacity and delay models[R]. Washington DC: NASA, 1998.
[27]	STAMATOPOULOS M A, ZOGRAFOS K G, ODONI A R. A decision support system for airport strategic planning[J]. Transportation Research Part C: Emerging Technologies, 2004, 12(2): 91-117. doi: 10.1016/j.trc.2002.10.001
[28]	TIAN Yong. Research on key techniques of air traffic flow management[D]. Nanjing: Nanjing University of Aeronautics and Astronautic, 2011. (in Chinese)
[29]	FENG Xiao-lei, TANG He-dan, LI Ming-jie. Research on the capacity evaluation model of staggered parallel double runways[J]. Mathematics in Practice and Theory, 2017, 47(11): 66-73. (in Chinese)
[30]	LI Xiong, LI Feng, CHEN Xiao-qing. Study on the configuration and capacity of the lateral runway based on the airport green operation[C]//IOP Publishing. 2017 International Conference on Environmental and Energy Engineering. Ostrava: IOP Publishing, 2017: 012032-1-8.
[31]	SHEN Zhi-yuan, HU Ying-ying. Runway capacity of lateral double-runway airport considering wake effect[J]. Journal of Nanjing University of Aeronautics and Astronautics, 2020, 52(1): 161-170. (in Chinese)
[32]	LIU Ke-xuan, MA Lan. Capacity assessment of two open Ⅴ-shaped runways based on isolated operation mode[J]. China Sciencepaper, 2018, 13(7): 825-830. (in Chinese) doi: 10.3969/j.issn.2095-2783.2018.07.019
[33]	FENG Kui-kui, ZHAI Wen-peng, WANG Wei-qing. Capacity evaluation of Urumqi Airport based on queuing model[J]. Mathematics in Practice and Theory, 2019, 49(21): 1-8. (in Chinese)
[34]	CHEUNG W L, PIPLANI R, ALAM S, et al. Dynamic capacity and variable runway configurations in airport slot allocation[J]. Computers and Industrial Engineering, 2021, 159: 107480. doi: 10.1016/j.cie.2021.107480
[35]	MIRKOVIC B, TOSIC V. Airport apron capacity: estimation, representation, and flexibility[J]. Journal of Advanced Transportation, 2014, 48(2): 97-118. doi: 10.1002/atr.1250
[36]	MIRKOVIC B. Airport apron capacity estimation-model enhancement[J]. Procedia-Social and Behavioral Sciences, 2011, 20: 1108-1117. doi: 10.1016/j.sbspro.2011.08.120
[37]	CAI Kai-quan, LI Wei, JU Fei, et al. A scenario-based optimization approach to robust estimation of airport apron capacity[C]//IEEE. 2018 Integrated Communications, Navigation, Surveillance Conference (ICNS). New York: IEEE, 2018: 3A1-1-3A1-8.
[38]	LIAO Chen-xi, WEI Zheng. Study on sector capacity and workload model of air traffic controllers based on least square method[C]//IEEE. 2020 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS). New York: IEEE, 2020: 1058-1062.
[39]	WELCH J D, ANDREWS J W, MARTIN B D, et al. Macroscopic workload model for estimating en route sector capacity[C]//FAA. Proceedings of 7th USA/Europe ATM Research and Development Seminar. Washington DC: FAA, 2007: 1-17.
[40]	TIAN Yong, WAN Li-li, YANG Shuang-shuang. Research on the method of sector dynamic capacity evaluation[J]. System Engineering—Theory and Practice, 2014, 34(8): 2163-2169.
[41]	LUO Feng-e, QI Fang, ZHAO Qi, et al. Flight dispatcher workload assessment based on improved DORATASK[J]. Science Technology and Industry, 2021, 21(4): 240-243. (in Chinese)
[42]	DONG Xiang-ning. Sector capacity evaluation and complexity analysis[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2017. (in Chinese)
[43]	KAGEYAMA K. ATC procedures modeling for capacity estimation of Japanese airspace[C]//AIAA. 2017 AIAA Modeling and Simulation Technologies Conference. Reston: AIAA, 2017: 1-10.
[44]	ZHANG Ming, SHAN Le, LIU Kai, et al. Terminal airspace sector capacity estimation method based on the ATC dynamical model[J]. Kybernetes, 2016, 45(6): 884-899.
[45]	MAJEED M, SU Rong. Neural partial differentiation-based estimation of terminal airspace sector capacity[J]. SAE International Journal of Aerospace, 2021, 14(2): 203-217.
[46]	REN Guang-jian, ZHU Jin-fu, LU Chao-yang. Research on assessment method of sector capacity based on ES model[J]. Aeronautical Computing Technique, 2018, 48(6): 40-44. (in Chinese)
[47]	ZHANG Wen-qian, WANG Ying, YAN Wei, et al. Research on multi-sector dynamic capacity evaluation method in severe weather[J]. Fire Control and Command Control, 2019, 44(3): 126-130, 140. (in Chinese)
[48]	LIU Lu. Terminal airspace capacity evaluation model under weather condition from perspective of a controller[J]. International Journal of Aerospace Engineering, 2018(2): 1-11.
[49]	HUANG Hai-qing, GAN Xu-sheng, DING Li-ying, et al. Study on capacity assessment method of terminal area under the influence of military activities[J]. Advances in Aeronautical, Science and Engineering, 2020, 11(3): 344-352. (in Chinese)
[50]	LIU Lu. Research on short-term terminal capacity assessment under weather conditions[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2018. (in Chinese)
[51]	WANG Xiao-tian, BAI Nai-gui. Airspace capacity simulation evaluation of Wuhan Tianhe International Airport based on AirTop[J]. Aircraft Design, 2018, 38(1): 72-75. (in Chinese)
[52]	GAO Wei, KANG Dao-chi. Regional controlled airspace capacity assessment based on an augmented cell transport model[J]. Science Technology and Engineering, 2020, 20(29): 12211-12217. (in Chinese)
[53]	SUN Hai-yong, LIU Yu-xu. Research on long parallel runway capacity in different operation modes[J]. Aeronautical Computing Technique, 2019, 49(5): 59-62, 66. (in Chinese)
[54]	WANG Qiang, ZUO Jie-jun, ZHONG Qi, et al. Capacity evaluation analysis of small and medium airports based on AnyLogic simulation[J]. Aeronautical Computing Technique, 2020, 50(3): 21-24. (in Chinese)
[55]	PARAMBATH S K. Capacity of ATC sectors in Chennai Upper Area Control Centre[C]//IEEE. 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). New York: IEEE, 2020: 1-7.
[56]	RAMAMOORTHY K, HUNTER G. Simulation-based airport capacity estimation[C]//NASA. 2013 Aviation Technology, Integration, and Operations Conference. Washington DC: NASA, 2013: 14-28.
[57]	BARRER J, KUZMINSKI P, SWEDISH W. Analyzing the runway capacity of complex airports[C]//AIAA. 5th ATIO and 16th Lighter-Than-Air Systems Technology. and Balloon Systems Conferences. Reston: AIAA, 2005: 1-7.
[58]	HU Qing-yun. Research on sector optimization of multi-airport terminal area based on complex airspace[D]. Guanghan: Civil Aviation Flight University of China, 2020. (in Chinese)
[59]	ZHAO Zheng. Research on airspace capacity assessment and forecast[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2015. (in Chinese)
[60]	ZHAO Zheng, HU Ming-hua. Research on peak service rate of airport[J]. Aeronautical Computing Technique, 2015, 45(1): 17-21. (in Chinese)
[61]	LYU Zhi-han, SONG Hou-bing, BASANTA-VAL P, et al. Next-generation big data analytics: state of the art, challenges, and future research topics[J]. IEEE Transactions on Industrial Informatics, 2017, 13(4): 1891-1899. http://discovery.ucl.ac.uk/10043069/1/Review%20on%20Network%20Big%20Data_v6.pdf
[62]	ZHANG Kai, LIU Yong-xin, WANG Jian, et al. Tree-based airspace capacity estimation[C]//IEEE. 2020 Integrated Communications Navigation and Surveillance Conference (ICNS). New York: IEEE, 2020: 5C1-1-5C1-8.
[63]	MO Fan. Research on sector capacity evaluation method based on machine learning[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2020. (in Chinese)
[64]	CHEN Jia-tong, CAI Kai-quan, LI Wei, et al. An airspace capacity estimation model based on spatio-temporal graph convolutional networks considering weather impact[C]//IEEE. 2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC). New York: IEEE, 2021: 1-7.
[65]	HU Jin-wen, CHENG Wei. Study on the high quality development of Jiangxi general aviation industry[J]. Co-Operative Economy and Science, 2022, 692(21): 10-12. (in Chinese)
[66]	ZHANG Hong-hai, ZOU Yi-yuan, ZHANG Qi-qian, et al. Future urban air mobility management: review[J]. Acta Aeronautica et Astronautica Sinica, 2021, 42(7): 82-106. (in Chinese)
[67]	LI Cheng-long, QU Wen-qiu, LI Yan-dong, et al. Overview of traffic management of urban air mobility (UAM) with eVTOL aircraft[J]. Journal of Traffic and Transportation Engineering, 2020, 20(4): 35-54. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2020.04.003
[68]	ZHANG Hong-hai, LI Shan, YI Jia, et al. Review on urban low-altitude air route planning[J]. Journal of Nanjing University of Aeronautics and Astronautics, 2021, 53(6): 827-838. (in Chinese)
[69]	MUELLER E R. Enabling airspace integration for high density urban air mobility[R]. Washington DC: NASA, 2017.
[70]	CHEN Yi-you, ZHANG Jian-ping, ZOU Xiang, et al. System framework and key technologies of civil unmanned aircraft system traffic management[J]. Science Technology and Engineering, 2021, 21(31): 13221-13237. (in Chinese)
[71]	JIANG Tao, GELLER J, NI Dai-heng, et al. Unmanned aircraft system traffic management: concept of operation and system architecture[J]. International Journal of Transportation Science and Technology, 2016, 5(3): 123-135.
[72]	HOEKSTRA J M, ELLERBROEK J, SUNIL E, et al. Geovectoring: reducing traffic complexity to increase the capacity of UAV airspace[C]//ICRAT. International Conference for Research in Air Transportation. Barcelona: ICRAT, 2018: 1-8.
[73]	MOHAMED SALLEH M F B, LOW K H. Concept of operations (ConOps) for traffic management of unmanned aircraft systems (TM-UAS) in urban environment[C]//AIAA. 2017 AIAA Information Systems—AIAA Infotech Aerospace. Reston: AIAA, 2017: 1-13.
[74]	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 Technologies, 2018, 92: 137-149.
[75]	ZHANG Yu-mei, YUAN Yong-yue. Situation and development strategy of lower altitude airspace management in China[J]. Electronic Technology, 2020, 49(7): 104-105. (in Chinese)
[76]	SHI Xiao-zhu. Discussion on layout of Chinese low altitude airspace structure[J]. Command Information System and Technology, 2010, 1(3): 23-26. (in Chinese)
[77]	GAO Ping, WANG Gu-chang, ZHENG Xing, et al. Status and development trend of UAV airspace flight[C]//CSAA. 2014 (5th) China UAV Conference Proceedings. Beijing: CSAA, 2014: 638-641. (in Chinese)
[78]	GHARIBI M, BOUTABA R, WASLANDER S L. Internet of drones[J]. IEEE Access, 2016, 4: 1148-1162.
[79]	SUNIL E, ELLERBROEK J, HOEKSTRA J, et al. An analysis of decentralized airspace structure and capacity using fast-time simulations[J]. Journal of Guidance, Control and Dynamics, 2017, 40(1): 38-51.
[80]	ROBERGE V, TARBOUCHI M, LABONTÉ G. Fast genetic algorithm path planner for fixed-wing military UAV using GPU[J]. IEEE Transactions on Aerospace and Electronic Systems, 2018, 54(5): 2105-2117.
[81]	LIAO Xiao-han, XU Chen-chen, YUE Huan-yin. Enable UAVs safely flight in low-altitude: a preliminary research of the public air route network of UAVs[C]//IEEE. 2019 International Conference on Unmanned Aircraft Systems (ICUAS). New York: IEEE, 2019: 959-964.
[82]	ZHANG Qi-qian, XU Wei-wei, ZHANG Hong-hai, et al. Path planning for logistics UAV in complex low-altitude airspace[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(7): 1275-1286. (in Chinese)
[83]	TANG Li, HAO Peng, ZHANG Xue-jun. An UAV path planning method in mountainous area based on an improved ant colony algorithm[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(1): 158-164. (in Chinese)
[84]	ZHANG Hong-hai, LI Han, LIU Hao, et al. Path planning for logistics unmanned aerial vehicle in urban area[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(6): 22-29. (in Chinese)
[85]	WANG Yun-chang, DAI Zhu-xiang, LI Tao. UAV path planning based on A-star algorithm and artificial potential field method[J]. Journal of Yangzhou University (Natural Science Edition), 2019, 22(3): 36-38, 49. (in Chinese)
[86]	LIN Xi, WANG Chen-zhang, WANG Kai-ping, et al. Trajectory planning for unmanned aerial vehicles in complicated urban environments: a control network approach[J]. Transportation Research Part C: Emerging Technologies, 2021, 128: 103-120.
[87]	DIMAS N F. A GIS-based analysis for selecting ground infrastructure locations for urban air mobility[D]. Munich: Environmental Engineering Technical University of Munich, 2018.
[88]	SHAVARANI S M, NEJAD M G, RISMANCHIAN F, et al. Application of hierarchical facility location problem for optimization of a drone delivery system: a case study of Amazon prime air in the city of San Francisco[J]. The International Journal of Advanced Manufacturing Technology, 2018, 95(9): 3141-3153.
[89]	QIAN Xin-yue, ZHANG Hong-hai, ZHANG Fang, et al. Research on location allocation of UAV landing points for terminal distribution logistics[J]. Journal of Wuhan University of Technology (Transportation Science and Engineering), 2021, 45(4): 682-687, 693. (in Chinese)
[90]	GOLABI M, SHAVARANI S M, IZBIRAK G. An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case study of Tehran Earthquake[J]. Natural Hazards, 2017, 87(3): 1545-1565.
[91]	REN Xin-hui, WANG Liu. Location model of automatic airport partitioning for unmanned aerial vehicles under urban instant delivery[J]. Computer Engineering and Applications, 2021, 57(10): 266-272. (in Chinese)
[92]	CHEN Gang, FU Jiang-yue. Drone distribution center location problem under military-civilian integration strategy[J]. Computer Engineering and Applications, 2019, 55(8): 226-231, 237. (in Chinese)
[93]	HONG I, KUBY M, MURRAY A T. A range-restricted recharging station coverage model for drone delivery service planning[J]. Transportation Research Part C: Emerging Technologies, 2018, 90: 198-212.
[94]	CHAUHAN D, UNNIKRISHNAN A, FIGLIOZZI M. Maximum coverage capacitated facility location problem with range constrained drones[J]. Transportation Research Part C: Emerging Technologies, 2019, 99: 1-18.
[95]	VENKATESH N, PAYAN A P, JUSTIN C Y, et al. Optimal siting of sub-urban air mobility (sUAM) ground architectures using network flow formulation[C]//AIAA. AIAA Aviation 2020 Forum. Reston: AIAA, 2020: 1-19.
[96]	ZHANG Hong-hai, FENG Di-kun, ZHANG Xiao-wei, et al. Urban logistics unmanned aerial vehicle vertiports layout planning[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(3): 207-214. (in Chinese)
[97]	PREIS L. Quick sizing, throughput estimating and layout planning for vtol aerodromes—a methodology for vertiport design[C]//AIAA. AIAA Aviation 2021 Forum. Reston: AIAA, 2021: 1-19.
[98]	EASA. Prototype technical design specifications for vertiports[R]. Cologne: EASA, 2022.
[99]	FAA. Engineering brief No. 105 vertiport design[R]. Washington DC: FAA, 2022.
[100]	VASCIK P D, HANSMAN R J. Development of vertiport capacity envelopes and analysis of their sensitivity to topological and operational factors[C]//AIAA. AIAA Scitech 2019 Forum. Reston: AIAA, 2019: 1-26.
[101]	ZHANG Hong-hai, FEI Yu-han, LI Jing-yu, et al. Method of vertiport capacity assessment based on queuing theory of unmanned aerial vehicles[J]. Sustainability, 2023, 15(1): 709-732.
[102]	RIMJHA M, TRANI A. Urban air mobility: factors affecting vertiport capacity[C]//IEEE. 2021 Integrated Communications Navigation and Surveillance Conference (ICNS). New York: IEEE, 2021: 1-14.
[103]	BULUSU V, SENGUPTA R, LIU Zhi-long. Unmanned aviation: to be free or not to be free?[C]//FAA. 7th International Conference on Research in Air Transportation. Washington DC: FAA, 2016: 1-8.
[104]	ZOU Yi-yuan. Research on the demarcation method of safe separation for unmanned aerial vehicle in future smart cities[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2021. (in Chinese)
[105]	BULUSU V, POLISHCHUK V, SENGUPTA R, et al. Capacity estimation for low altitude airspace[C]//AIAA. 17th AIAA Aviation Technology, Integration, and Operations Conference. Reston: AIAA, 2017: 4266.
[106]	BULUSU V, SENGUPTA R, MUELLER E R, et al. A throughput based capacity metric for low-altitude airspace[C]// AIAA. 2018 Aviation Technology, Integration, and Operations Conference. Reston: AIAA, 2018: 1-9.

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Review on research of low-altitude airspace capacity evaluation

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