低空经济背景下人工智能保障eVTOL飞行安全综述

doi:10.11896/jsjkx.250200050

摘要/Abstract

摘要： 随着低空经济的兴起,电动垂直起降飞行器(eVTOL)的应用更加广泛,其飞行安全保障至关重要,有待加强相关应用研究。通过分析大量相关文献,从eVTOL本身的效能可靠性、应用规程的安全性和飞行数据传输的安全这3方面进行深入剖析,梳理了可能面临的数据安全、复杂环境感知决策、计算资源限制和多智能体协同挑战等问题。最后对人工智能在eVTOL安全应用的未来发展趋势进行预测,为后续研究与实践提出技术研发重点、标准法规完善及行业合作等建议,旨在全面展现人工智能保障eVTOL运用安全的应用全景,为其进一步发展提供参考。

关键词: 低空经济, eVTOL, 人工智能, 计算机视觉, 飞行安全

Abstract: With the rise of the low-altitude economy,electric vertical take-off and landing(eVTOL) aircraft are seeing increasingly widespread applications.Ensuring their flight safety has become critically important,necessitating strengthened research into relevant safety measures.Through a systematic review of existing literature,this study conducts an in-depth analysis from three dimensions:the operational reliability of eVTOL systems,the safety of operational protocols,and the security of flight data transmission.It identifies key challenges such as data security risks,decision-making under complex environmental conditions,computational resource constraints,and multi-agent coordination complexities.Finally,the paper forecasts future trends in AI-driven eVTOL safety applications and proposes priorities for technological R&D,regulatory framework optimization,and industry collaboration.These recommendations aim to present a comprehensive roadmap for AI-enabled safety solutions in eVTOL operations,serving as a foundational reference for future advancements in this field.

Key words: Low-altitude economy, eVTOL, Artificial intelligence, Computer vision, Flight safety

中图分类号:

V279

苏志远, 赵利绪, 郝志恒, 百茹峰. 低空经济背景下人工智能保障eVTOL飞行安全综述[J]. 计算机科学, 2025, 52(6A): 250200050-13. https://doi.org/10.11896/jsjkx.250200050

SU Zhiyuan, ZHAO Lixu, HAO Zhiheng, BAI Rufeng. Suvery of Artificial Intelligence Ensuring eVTOL Flight Safety in the Context of Low-altitudeEconomy[J]. Computer Science, 2025, 52(6A): 250200050-13. https://doi.org/10.11896/jsjkx.250200050

参考文献

[1]XIAO J,LI W.Analysis of Airworthiness Requirements forCommercial Aircraft Avionics System Design in Low Altitude Economy[J].Engineering Proceedings,2024,80(1):6.
[2]JULIÀ GARCÍA E.EVTOL concept design[D].UniversitatPolitècnica de Catalunya,2023.
[3]ZAID A A,BELMEKKI B E Y,ALOUINIM S.eVTOL communications and networking in UAM:Requirements,key enablers,and challenges[J].IEEE Communications Magazine,2023,61(8):154-160.
[4]WANG F,YANG J Y,TONG G,et al.The development of unmanned electric vertical take-off and landing aircraft in the future urban air traffic [J],Henan Science and Technology,2021,40(11):82-85.
[5]HE J,HE Q,XU Z,et al.Key technologies and upgrade strategies for eVTOL aircraft energy storage systems[J].Journal of Energy Storage,2024,103:114402.
[6]CHEN Y,CHEN C M,LIU Z Y,et al.The MethodologicalFunction of CiteSpace Knowledge Mapping[J].Research on Science and Technology,2015,33(2):242-253.
[7]LI J,CHEN C M.CiteSpace:Science Text Mining and Visualization(2nd ed.) [M].Beijing:Capital University of Economics and Business Press,2017:171.
[8]LI Y,LIU M.Path planning of electric VTOL UAV considering minimum energy consumption in urban areas[J].Sustainability,2022,14(20):13421.
[9]WEI H,LOU B,ZHANG Z,et al.Autonomous navigation for eVTOL:Review and future perspectives[J].IEEE Transactions on Intelligent Vehicles,2024,9(2):4145-4171.
[10]WANG M,DIEPOLDER J,ZHANG S,et al.Trajectory optimization-based maneuverability assessment of eVTOL aircraft[J].Aerospace Science and Technology,2021,117:106903.
[11]SINGH A,LODGE A,LI Y,et al.A new method to perform lithium-ion battery pack fault diagnostics-Part 3:Adaptation for fast charging[J].Journal of Energy Storage,2023,66:107424.
[12]GRANADO L,BEN-MARZOUK M,SAENZ E S,et al.Machine learning predictions of lithium-ion battery state-of-health for eVTOL applications[J].Journal of Power Sources,2022,548:232051.
[13]DEMIR G,MOSLEM S,DULEBA S.Artificial Intelligence in Aviation Safety: Systematic Review and Biometric Analysis [J].International Journal of Computational Intelligence Systems,2024,17(1):1-30.
[14]WHIG P,KASULA B Y,YATHIRAJU N,et al.Transforming Aviation:The Role of Artificial IntelligenceinAir Traffic Management[M]//New Innovations in AI,Aviation,and Air Traffic Technology.Hershey:IGI Global,2024:60-75.
[15]WANG K J,ZHANG R,GE S J,et al.A multi-level optimization framework of aircraft structure based on hybrid algorithm [C]//Proceedings of the 6th China Aviation Science and Technology Conference.Research Department of New Structural Technology,China Aviation Academy of Science and Technology,2023:10.
[16]MIRJALILI S,MIRJALILIS.Genetic algorithm[J].Evolutionary Algorithms and Neural Networks:Theory and Applications,2019:43-55.
[17]WANG D,TAN D,LIU L.Particle swarm optimization algorithm:an overview[J].Soft computing,2018,22(2):387-408.
[18]SHERSTINSKY A.Fundamentals of recurrent neural network(RNN) and long short-term memory(LSTM) network[J].Physica D:Nonlinear Phenomena,2020,404:132306.
[19]LILLICRAP T P,SANTORO A,MARRISL,et al.Backpropagation and the brain[J].Nature Reviews Neuroscience,2020,21(6):335-346.
[20]LIU Y X,YAO L Z,ZHOU J H,et al.Joint prediction of SOC and SOH of lithium battery energy storage devices based on LSTM [J].Journal of Global Energy Interconnection,2022,5(1):37-45.
[21]YU Y P.Research on 3D visual simulation system of quadrotor unmanned aerial vehicle based on FlightGear [D].Tianjin:Tianjin University,2010.
[22]GROSAN C,ABRAHAM A,GROSA N,et al.Rule-based expert systems[C]//Intelligent Systems:A Modern Approach.Berlin:Springer,2011:149-185.
[23]LI H.Research on crack detection of aero-engine blades basedon image recognition [D].Chengdu:University of Electronic Science and Technology of China,2019.
[24]EJAZ M,GUI J,ASIM M,et al.RL-Planner:ReinforcementLearning-Enabled Efficient Path Planning in Multi-UAV MEC Systems[J].IEEE Transactions on Network and Service Management,2024,21(3):3317-3329.
[25]JU C,LUO Q,YAN X.Path planning using an improved a-star algorithm[C]//2020 11th International Conference on Prognostics and System Health Management(PHM-2020 **an).IEEE,2020:23-26.
[26]LI M,CHEN J L,LIU W,et al.Comparison of path planning algorithms for eVTOL aircraft oriented to urban air traffic [J].Journal of Xihua University(Natural Science Edition),2023,42(5):54-61.
[27]CABAHUG J,ESLAMIAT H.Failure detection in quadcopterUAVs using K-means clustering[J].Sensors,2022,22(16):6037.
[28]DE SILVA B M,CALLAHAM J,JONKER J,et al.Physics-informed machine learning for sensor fault detection with flight test data[J].arXiv:2006.13380,2020.
[29]KALMAN R E.A new approach to linear filtering and prediction problems[J].Journal of Basic Engineering,1960,82(1):35-45.
[30]FUJII K.Extended kalman filter[J].Refernce Manual,2013,14:41.
[31]GUSTAFSSON F.Particle filter theory and practice with positioning applications[J].IEEE Aerospace and Electronic Systems Magazine,2010,25(7):53-82.
[32]NASSIF A B,TALIB M A,NASIR Q,et al.Machine learning foranomaly detection:A systematic review[J].IEEE Access,2021,9:78658-78700.
[33]EMAMI S A,CASTALDI P,BANAZADEH A.Neural net-work-based flight control systems:Present and future[J].Annual Reviews in Control,2022,53:97-137.
[34]ANNASWAMY A M,FRADKOVA L.A historical perspective of adaptive control and learning[J].Annual Reviews in Control,2021,52:18-41.
[35]NHIVEKAR G S,NIRMALE S S,MUDHOLKER R R.Implementation of fuzzy logic control algorithm in embedded microcomputers for dedicated application[J].International Journal of Engineering,Science and Technology,2011,3(4):276-283.
[36]ABDOLRASOL M G M,HUSSAIN S M S,USTUN T S,et al.Artificial neural networks based optimization techniques:A review[J].Electronics,2021,10(21):2689.
[37]SUN H,WANG P,ZHANG D,et al.An improved orb algorithm based on optimized feature point extraction[C]//2020 IEEE 3rd International Conference on Automation,Electronics and Electrical Engineering(AUTEEE).IEEE,2020:389-394.
[38]CHEN M,QU R,FANG W.Case-based reasoning system forfault diagnosis of aero-engines[J].Expert Systems with Applications,2022,202:117350.
[39]YAZDI M,MOHAMMADPOUR J,LI H,et al.Fault tree analysis improvements:A bibliometric analysis and literature review[J].Quality and Reliability Engineering International,2023,39(5):1639-1659.
[40]TEOMITZI H E,SCHMIDT J R.Concept and requirements for an integrated contingency management framework in UAS missions[C]//2021 IEEE Aerospace Conference(50100).IEEE,2021:1-17.
[41]COHEN A P,SHAHEEN S A,FARRARE M.Urban air mobili-ty:History,ecosystem,market potential,and challenges[J].IEEE Transactions on Intelligent Transportation Systems,2021,22(9):6074-6087.
[42]AL-RUBAYE S,TSOURDOS A,NAMUDURI K.Advanced air mobility operation and infrastructure for sustainable connected evtol vehicle[J].Drones,2023,7(5):319.
[43]CANESE L,CARDARILLI G C,DI NUNZIO L,et al.Multi-agent reinforcement learning:A review of challenges and applications[J].Applied Sciences,2021,11(11):4948.
[44]WANG H.Research on fault diagnosis and prediction technology of aircraft information processing equipment [D].Beijing:Beijing Jiaotong University,2020.
[45]LI Z,LIU F,YANG W,et al.A survey of convolutional neural networks:analysis,applications,and prospects[J].IEEE Transactions on Neural Networks and Learning Systems,2021,33(12):6999-7019.
[46]ZHANGY H.A study of face recognition based on convolutional neural network [D].Tianjin:Tianjin University,2018.
[47]KUMBHARE T A,CHOBE S V.An overview of associationrule mining algorithms[J].International Journal of Computer Science and Information Technologies,2014,5(1):927-930.
[48]QI C S,HE W S,JIAO Y,et al.A review of abnormal detection algorithms for UAV flight data [J].Journal of Computer Applications,2023,43(6):1833-1841.
[49]NAIDU G,ZUVA T,SIBANDAE M.A review of evaluationmetrics in machine learning algorithms[C]//Computer Science On-line Conference.Cham:Springer International Publishing,2023:15-25.
[50]ZHOU X Y,HUANG J T,ZHANG S,et al.Aerodynamic modeling of fixed-wing aircraft “neurons” flight considering strong wind interference [J].Acta Aerodynamica Sinica,2024,42(3):92-101.
[51]SCHWEIGER K,SCHMITZ R,KNABE F.Impact of wind on eVTOL operations and implications for vertiport airside traffic flows:A case study of Hamburg and Munich[J].Drones,2023,7(7):464.
[52]ZHAO W,ALWIDIAN S,MAHMOUD Q H.Adversarial training methods for deep learning:A systematic review[J].Algorithms,2022,15(8):283.
[53]LO C H,FUNG E,WONG Y W.Intelligent Automatic FaultDetection for Actuator Failures in Aircraft[J].IEEE Transactions on Industrial Informatics,2009,5(1):50-55.
[54]KAFETZI S,DIMITRIO S.Software-defined networking meets software-defined radio in mobile ad hoc networks:state of the art and future directions[J].IEEE Access,2022(10):9989-10014.
[55]GOUNIS K,BASSILIADES N.Intelligent momentary assisted control for autonomous emergency braking[J].Simulation Mo-delling Practice and Theory,2022,115:102450.
[56]VILLAMIL S,CESAR H, GIOVANNY T.An overview of internet of things[J].Telkomnika(Telecommunication Computing Electronics and Control),2020,18(5):2320-2327.
[57]MANIKANDAPRABHU P,SAMREETHA M.A review of encryption and decryption of text using the AES algorithm[J].International Journal of Scientific Research & Engineering Trends,2024,10(2):400-404.
[58]WAHAB,OSAMA F A,et al.Hiding data using efficient combination of RSA cryptography,and compression steganography techniques[J].IEEE Access,2021(9):31805-31815.
[59]WANG J,LU Y,WEI L,et al.Secure SSL/TLS Communication System Based on Quantum Keys[J].ZTE Communications,2024,22(3):106-115.
[60]KUMAR M,PATTNAIK P.Post Quantum Cryptography(PQC)-An Overview[C]//2020 IEEE High Performance Extreme Computing Conference(HPEC).IEEE,2020:1-9.
[61]GUO H Q,YU J.A survey on blockchain technology and its security[J].Blockchain:Research and Applications,2022,3(2):100067.
[62]CARLO B,CIMATO S,SINISCALCHI L.Managing constraints in role based access control[J].IEEE Access,2020(8):140497-140511.
[63]ZU L J,CAO Y L,MENX H L,et al.An adaptive desensitization algorithm method based on privacy risk assessment [J].Journal of Network and Information Security,2023,9(3):49-59.
[64]ABDUL M,LEE S.Anonymization techniques for privacy preserving data publishing:A comprehensive survey[J].IEEE Access,2020(9):8512-8545.
[65]YE S,WAN Z,ZENG L,et al.A vision-based navigation method for eVTOL final approach in urban air mobility(UAM)[C]//2020 4th CAA International Conference on Vehicular Control and Intelligence(CVCI).IEEE,2020:645-649.
[66]XUE H T,YE Y Y,SHEN L C,et al.A review of research on the architecture and coordination mechanisms of multi-agent systems [J].Robot,2001,23(1):85-90.
[67]LIU X H,HAN J,WEI X J.Distributed fault estimation ofmulti-agent systems based on intermediate observers [J].Acta Automatica Sinica,2020,46(1):142-152.
[68]KUMAR A,BHATIA S,KAUSHIK K,et al.Survey of promising technologies for quantum drones and networks[J].IEEE Access,2021,9:125868-125911.
[69]HE B,YUAN H,MENG J,et al.Brain-computer interfaces[C]//Neural Engineering.Cham:Springer,2020:131-183.
[70]ZAID A A,BELMEKKI B E Y,ALOUINIM S.eVTOL communications and networking in UAM:Requirements,key enablers,and challenges[J].IEEE Communications Magazine,2023,61(8):154-160.

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