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Civil unmanned aircraft system operation in national airspace: A survey from Air Navigation Service Provider perspective

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Chinese Journal of Aeronautics 2021年第3期34卷 200-224页

作者： Zhaoxuan LIU kaiquan cai Yanbo ZHU School of Electronics and Information Engineering Beihang UniversityBeijing 100083China Aviation Data Communication Corporation Beijing 100083China

Unmanned Aircraft Systems(UASs) have advanced technologically and surged exponentially over recent years. Currently, due to safety concerns, most civil operations of UAS are conducted in low-level uncontrolled area or in segregated controlled airspace. As the industry progresses, both operational and technological capabilities have matured to the point where UASs are expected to gain greater freedom of access to both controlled and uncontrolled airspace. Extensive technical and regulatory surveys have been conducted to enable the expanded operations. However, most surveys are derived from the perspective of UAS own operating mechanism and barely consider interactions of their non-segregated activities with the Air Traffic Management(ATM) system. Hence, to fill the gap, this paper presents a survey conducted from the perspective of Air Navigation Service Provider(ANSP), which serves to accommodate these new entrants to the overall national airspace while continuing flight safety and efficiency. The primary objectives of this paper are to:(A) describe what typical ANSP-supplied UAS Traffic Management(UTM) architecture is required to facilitate all types of civil UAS operations;(B) identify three major ANSP considerations on how UAS can be accommodated safely in civil airspace;(C) outline future directions and challenges related with UAS operations for the ANSP.

关键词： Air Navigation Service Provider Airspace Organization and Management Air Traffic Control Air Traffic Management Air traffic service provision Unmanned Aircraft System UAS Traffic Management

Measuring air traffic complexity based on small samples

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Chinese Journal of Aeronautics 2017年第4期30卷 1493-1505页

作者： Xi ZHU Xianbin CAO kaiquan cai School of Electronics and Information Engineering Beihang University Beijing 100191 China Beijing Key Laboratory for Network-Based Cooperative Air Traffic Management Beijing 100083 China

Air traffic complexity is an objective metric for evaluating the operational condition of the airspace. It has several applications, such as airspace design and traffic flow ***, identifying a reliable method to accurately measure traffic complexity is important. Considering that many factors correlate with traffic complexity in complicated nonlinear ways,researchers have proposed several complexity evaluation methods based on machine learning models which were trained with large samples. However, the high cost of sample collection usually results in limited training set. In this paper, an ensemble learning model is proposed for measuring air traffic complexity within a sector based on small samples. To exploit the classification information within each factor, multiple diverse factor subsets（FSSs） are generated under guidance from factor noise and independence analysis. Then, a base complexity evaluator is built corresponding to each FSS. The final complexity evaluation result is obtained by integrating all results from the base evaluators. Experimental studies using real-world air traffic operation data demonstrate the advantages of our model for small-sample-based traffic complexity evaluation over other stateof-the-art methods.

关键词： Air traffic control Air traffic complexity Correlation analysis Ensemble learning Feature selection

Multi-faceted spatio-temporal network for weather-aware air traffic flow prediction in multi-airport system

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Chinese Journal of Aeronautics 2024年第7期37卷 301-316页

作者： kaiquan cai Shuo TANG Shengsheng QIAN Zhiqi SHEN Yang YANG School of Electronic and Information Engineering Beihang UniversityBeijing 100191China State Key Laboratory of CNS/ATM Beijing100191China Institute of Automation Chinese Academy of SciencesBeijing 100190China Research Institute for Frontier Science Beihang UniversityBeijing 100191China

As one of the core modules for air traffic flow management,Air Traffic Flow Prediction(ATFP)in the Multi-Airport System(MAS)is a prerequisite for demand and capacity balance in the complex meteorological *** to the challenge of implicit interaction mechanism among traffic flow,airspace capacity and weather impact,the Weather-aware ATFP(Wa-ATFP)is still a nontrivial *** this paper,a novel Multi-faceted Spatio-Temporal Graph Convolutional Network(MSTGCN)is proposed to address the Wa-ATFP within the complex operations of ***,a spatio-temporal graph is constructed with three different nodes,including airport,route,and fix to describe the topology structure of ***,a weather-aware multi-faceted fusion module is proposed to integrate the feature of air traffic flow and the auxiliary features of capacity and weather,which can effectively address the complex impact of severe weather,e.g.,***,to capture the latent connections of nodes,an adaptive graph connection constructor is *** experimental results with the real-world operational dataset in Guangdong-Hong Kong-Macao Greater Bay Area,China,validate that the proposed approach outperforms the state-of-the-art machine-learning and deep-learning based baseline approaches in performance.

关键词： Air traffic control Graph neural network Multi-faceted information Air traffic flow prediction Multi-airport system

A hybrid distributed-centralized conflict resolution approach for multi-aircraft based on cooperative co-evolutionary

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Science China(Information Sciences) 2013年第12期56卷 281-296页

作者： ZHANG XueJun GUAN XiangMin HWANG Inseok cai kaiquan School of Electronic and Information Engineering Beihang University

Conflict resolution(CR)plays a crucial role in safe air trafc management(ATM).In this paper,we propose a new hybrid distributed-centralized tactical CR approach based on cooperative co-evolutionary named the CCDG(cooperative co-evolutionary with dynamic grouping)strategy to overcome the drawbacks of the current two types of approaches,the totally centralized approach and distributed ***,aircraft are divided into several sub-groups based on their ***,a dynamic grouping strategy is proposed to group the aircraft to better deal with the tight coupling among *** sub-groups are adjusted dynamically as new conflicts appear after each ***,a fast genetic algorithm(GA)is used by each sub-group to optimize the paths of the aircraft ***,the aircraft’s optimal paths are obtained through cooperation among diferent sub-groups based on cooperative co-evolutionary(CC).An experimental study on two illustrative scenarios is conducted to compare the CCDG method with some other existing approaches and it is shown that CCDG which can get the optimal solution efectively and efciently in near real time,outperforms most of the existing approaches including Stratway,the fast GA,a general evolutionary path planner,as well as three well-known cooperative co-evolution algorithms.

关键词： multi-aircraft conflict resolution hybrid distributed-centralized dynamic grouping strategy cooperative co-evolutionary

A geographical and operational deep graph convolutional approach for flight delay prediction

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Chinese Journal of Aeronautics 2023年第3期36卷 357-367页

作者： kaiquan cai Yue LI Yongwen ZHU Quan FANG Yang YANG Wenbo DU School of Electronic and Information Engineering Beihang UniversityBeijing 100191China Key Laboratory of National Airspace Technology Beijing 100085China National Lab of Pattern Recognition Institute of AutomationChinese Academy of SciencesBeijing 100190China Research Institute for Frontier Science Beihang UniversityBeijing 100191China

Flight delay prediction has attracted great interest in civil aviation community due to its significant role in airline planning,flight scheduling,airport operation,and passenger *** delay is affected by numerous factors and irregularly propagates in air transportation networks owing to flight connectivity,which brings critical challenges to accurate flight delay *** recent years,Graph Convolutional Networks(GCNs)have become popular in flight delay prediction due to the advantage in extracting complicated ***,most of the existing GCN-based methods have failed to effectively capture the spatial-temporal information in flight delay *** this paper,a Geographical and Operational Graph Convolutional Network(GOGCN)is proposed for multi-airport flight delay *** GOGCN is a GCN-based spatial-temporal model that improves node feature representation ability with geographical and operational spatial-temporal interactions in a ***,an operational aggregator is designed to extract global operational information based on the graph structure,while a geographical aggregator is developed to capture the similar nature among spatially close *** experiments on a real-world dataset demonstrate that the proposed approach outperforms the state-of-the-art methods with a satisfying accuracy improvement.

关键词： Flight delay prediction Flight operation pattern Geographical interactive information Graph neural network Spatial-temporal information

Segment-wise learning control for trajectory tracking of robot manipulators under iteration-dependent periods

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Science China(Information Sciences) 2024年第3期67卷 155-166页

作者： Fan ZHANG Deyuan MENG kaiquan cai The Seventh Research Division Beihang University School of Automation Science and Electrical Engineering Beihang University School of Electronics and Information Engineering Beihang University

This paper is concerned with the amplitude boundedness problem of adaptive iterative learning control(AILC) for robot manipulators operating with iteration-dependent periods. By introducing virtual memory slots for storing historical data, a practical AILC method is proposed to achieve the segmentwise learning. This method requires less memory storage for historical information of previous iterations,especially in comparison with that of the conventional AILC methods using point-wise learning *** is shown that not only the energy boundedness but also the amplitude boundedness of estimates and inputs of practical AILC can be guaranteed. Moreover, the practical AILC method can achieve the perfect tracking objective regardless of iteration-dependent periods when the robot manipulators have a persistent full learning property. In addition, a solution to the visual manipulator platform is provided and deployed based on Coppeliasim and Matlab, which helps to show the amplitude boundedness of learning results and the perfect tracking performances of the proposed practical AILC method for robot manipulators.

关键词： amplitude boundedness iteration-dependent period iterative learning control robot manipulator segment-wise virtual memory slot

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高空空域飞机高度保持性能分析

航空学报 2009年第4期30卷 726-731页

作者：蔡开泉张军张学军北京航空航天大学电子信息工程学院北京100191

飞机高度保持性能是影响空域运行安全的重要因素。在总结飞机高度保持性能定义、要素及评价指标的基础上,推导了高空空域飞机高度保持性能的求解公式。针对高度保持偏差样本分布尖峰厚尾的特征,提出了基于指数幂分布和高斯-双指数混合... 详细信息

飞机高度保持性能是影响空域运行安全的重要因素。在总结飞机高度保持性能定义、要素及评价指标的基础上,推导了高空空域飞机高度保持性能的求解公式。针对高度保持偏差样本分布尖峰厚尾的特征,提出了基于指数幂分布和高斯-双指数混合分布拟合区间化的高度保持偏差数据的方法,并利用似然比检验法检验两类分布的拟合优度。实例评估表明,中国现行高空空域内飞机的整体高度保持性能满足安全性要求。

关键词：空中交通管理高度保持性能指数幂分布高斯-双指数混合分布似然比检验

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空中交通自主间隔管控技术研究

南京航空航天大学学报 2022年第4期54卷 688-699页

作者：蔡开泉赵鹏北京航空航天大学电子信息工程学院北京100191

空中交通自主间隔管控是通过将地面管制系统的间隔管制任务部分或全部转移到航空器端,实现空地分布式的间隔保持与安全管控,进而达到改善空中航行的灵活性与效率的目的,是国际民航下一代空中交通管理系统发展的前沿技术方向。本文总结... 详细信息

空中交通自主间隔管控是通过将地面管制系统的间隔管制任务部分或全部转移到航空器端,实现空地分布式的间隔保持与安全管控,进而达到改善空中航行的灵活性与效率的目的,是国际民航下一代空中交通管理系统发展的前沿技术方向。本文总结分析了空中交通自主间隔管控的国内外发展现状与技术挑战,重点从机载飞行态势感知、机载航迹规划与控制、空中交通自主运行管控3方面综述了技术研究进展,归纳了3方面技术的发展趋势,并指出了未来研究的思路与方向。

关键词：空中交通管理自主运行机载间隔保持安全管控

累积冲击下的经济生产批量及视情维修联合优化问题

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工业工程与管理 2023年第5期28卷 57-66页

作者：张楠刘雨蔡开泉张军北京理工大学管理与经济学院北京100080 北京航空航天大学电子信息工程学院北京100191 北京理工大学前沿交叉学院北京100080

为解决传统基于设备不会失效假设下经济生产批量问题研究的不足,考虑经济生产批量系统中设备失效维修的问题,提出了生产批量和视情维修联合优化的方法。基于泊松过程和一般分布构建冲击到达过程及累积冲击效应,结合设备退化观测和具体... 详细信息

为解决传统基于设备不会失效假设下经济生产批量问题研究的不足,考虑经济生产批量系统中设备失效维修的问题,提出了生产批量和视情维修联合优化的方法。基于泊松过程和一般分布构建冲击到达过程及累积冲击效应,结合设备退化观测和具体的维护费用结构,给出了可修退化系统最优的生产批量和视情维修阈值的求解模型。通过数值分析验证了最优策略的有效性,并进行了参数的敏感性分析,为设备管理者提供决策依据。

关键词：经济生产批量视情维修累积冲击失效平均费用率