空中交通管制员工作负荷研究

This paper is focusing on workload leading to stress and fatigue,which,so far,have resulted in real or potential accidents,incidents or errors,not been explored but with impact on the controller everyday,studying workload curve on the real situations based on operational units,e.g. Zhengzhou area control center,and doing certain calculations on the number of air traffic controller needed in accordance with the air traffic to be handled. Lastly,some strategies are put forward.     

基于Eulerian模型的空中交通流量控制

通过拓展公路交通中常见的Eulerian模型,研究了一种空中交通流量模型。利用线性二次型最优控制理论,对空中交通流量模型进行了分析研究,实现对特定区域内流量进行控制。最后,用Matlab对系统进行了仿真,结果表明,引入最优控制向量的方法改善了流量波动性大的情况,降低了管制员的工作负荷。     

天气影响下的空中交通系统容量评估综述

回顾了空中交通系统容量评估的基本方法,随后以恶劣天气为背景,介绍了空中交通系统不同组成单元中容量研究的对象与方法.分析表明现有研究存在缺乏容量短周期评估方法、容量定义多样化、忽略管制员负荷等问题,并提出了后续研究的思路.     

基于空中交通管制运行品质的扇区容量评估

扇区容量反映的是扇区空中交通管制运行品质诸多要素综合寻优下的流量水平,目前将扇区管制员工作负荷阈值映射为扇区容量的评估方法存在片面性。为改善扇区容量评估方法,以成都进近南扇为研究实例,采集198组实际运行数据建立样本集,确立了涵盖空中交通流密度、管制运行安全性能、管制运行效率性能及管制员工作负荷等4类因子的管制运行品质量化指标,并基于主成分分析法实现了扇区管制运行品质综合评价,经函数拟合确定扇区容量为29架次/h,新方法更具科学性、客观性。     

空中交通管制员技能评估主成分分析方法

为改善空中交通管制员技能评估方法,以管制员作业结果评估为立足点,建立了涵盖空中交通流密度、管制运行安全性能、管制运行效率性能及管制员工作负荷等4类因子的管制员技能定量评估指标体系,并给出了基于主成分分析法的管制员技能定量评估方法。经各等级管制员雷达模拟机多场景测试验证,采用新方法对100个测试样本的评估结果符合实际;相比通过管制教员观察管制员作业过程得出人工评定结果的传统方法,新方法的科学性、客观性及适用性更优。     

空中交通复杂性研究进展

空中交通复杂性是空中交通态势的本质属性，是空中交通管制工作负荷的主要驱动因素。空中交通复杂性的科学评价是实现空中交通精细化管理的关键，也是当前空管领域研究热点。本文介绍了国内外空中交通复杂性的研究团队，梳理了空中交通复杂性与工作负荷、安全水平等相互之间的区别和联系，并详细分析了现有研究的具体研究路线。在分析新一代空中交通管理系统特征的基础上，对空中交通复杂性的未来研究趋势和方向进行了展望。     

基于动态空域管理的安全性研究

当前静态的空域结构已很难适应不断变化的流量对空域的使用需求,动态空域管理概念为解决这一问题提供了一个可行的解决方案。扇区结构优化调整作为动态空域管理的核心内容在解决空域资源使用紧张问题的同时,也给当前管制工作安全带来了挑战。主要从管制员工作负荷、空域结构调整可能带来的管制操作困难及空域划分触发机制3个方面来探讨研究动态空域管理相关安全性问题。     

对流天气空域阻塞概率与阻塞指数模型

管制员高估对流天气的影响,发布不必要的流控指令,会使得航班过度延误;管制员低估对流天气的影响,会造成工作负荷的激增,也会使得航班飞行安全风险增大。为了准确评估空域受天气影响程度,减少管制员高估和低估天气影响次数,建立了特定方向对流天气空域阻塞概率模型和航路交通阻塞指数模型。测试结果表明,特定方向对流天气空域阻塞概率模型,用于衡量对流天气下交通流在各个方向被阻塞概率,为管制员决策是否允许航空器沿特定方向在扇区绕飞提供参考有实际意义;对流天气航路交通阻塞指数模型,用于衡量对流天气下沿航路交通流被阻塞的概率,为管制员决策是否允许航空器沿航路穿越对流天气提供参考是可行的。访谈数据表明,90%的参访者同意在这两个参数可得时,他们获取对流天气影响交通态势感知所需要的时间确实有所减少。     

两种空管自动化系统中管制员可靠性研究

介绍了人的可靠性评估的发展,进而提出了雷神雷达系统和欧洲猫雷达系统两种空管自动化系统下的管制员可靠性研究方法和数据采集的形式,通过对采集样本数据的分析,计算出管制员从雷神雷达系统过渡到欧洲猫雷达系统可靠性的评估结果,进一步指出提高管制员可靠性的改进措施.     

Percolation transition in temporal airport network

The air transportation system has a critical impact on the global economy. While the system reliability is essential for the operational management of air traffic, it remains challenging to understand the network reliability of the air transportation system. This paper focuses on how the global air traffic is integrated from local scale along with operational time. The integration process of air traffic into a temporally connected network is viewed as percolation process by increasing the integration time constantly. The critical integration time T_P which is found during the integration process can measure the global reliability of air traffic. The critical links at T_P are also identified, the delay of which will influence the global integration of the airport network. These findings may provide insights on the reliability management for the temporal airport network.     

空中交通改航路径评估方法研究

针对航班改航路径的优劣提出了三种评估模型.首先,从航线的安全性、经济性、管制员及飞行员的工作负荷、同计划航线的差异和航线飞行的舒适性角度出发,选取5个评估指标.然后,应用层次分析法分别确定这5个指标在飞行-空管评估模型、航空公司评估模型和综合评估模型下的权重.最后,将各评估模型应用于现有改航飞行路径的评估,研究结果表明...     

管制员信息处理能力模糊评价

信息处理能力是管制员能力和工作负荷的重要组成部分。针对此方面缺乏系统研究的实际，详细分析了管制员信息处理能力的影响因素，给出了评价指标体系，建立了多级模糊评价模型，实现了此能力的量化评价。通过对管制员的具体评价，符合管制员的自身情况，证明了方法的有效性。     

Measuring air traffic complexity based on small samples

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 management.Therefore,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.     

Identifying and managing risks of AI-driven operations: A case study of automatic speech recognition for improving air traffic safety

In this work, the primary focus is to identify potential technical risks of Artificial Intelligence (AI)-driven operations for the safety monitoring of the air traffic from the perspective of speech communication by studying the representative case and evaluating user experience. The case study is performed to evaluate the AI-driven techniques and applications using objective metrics, in which several risks and technical facts are obtained to direct future research. Considering the safety–critical specificities of the air traffic control system, a comprehensive subjective evaluation is conducted to collect user experience by a well-designed anonymous questionnaire and a face-to-face interview. In this procedure, the potential risks obtained from the case study are confirmed, and the impacts on human working are considered. Both the case study and the evaluation of user experience provide compatible results and conclusions: (A) the proposed solution is promising to improve the traffic safety and reduce the workload by detecting potential risks in advance; (B) the AI-driven techniques and whole diagram are suggested to be enhanced to eliminate the possible distraction to the attention of air traffic controllers. Finally, a variety of strategies and approaches are discussed to explore their capability to advance the proposed solution to industrial practices.     

Multiple air route crossing waypoints optimization via artificial potential field method

Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization, capacity and resilience in dealing with air traffic congestion and delay. However, research is lacking on the optimization of multiple Crossing Waypoints (CWPs) in the fragmented airspace separated by Prohibited, Restricted and Dangerous areas (PRDs). To tackle this issue, this paper proposes an Artificial Potential Field (APF) model considering attractive forces produced by the optimal routes and repulsive forces generated by obstacles. An optimization framework based on the APF model is proposed to optimize the different airspace topologies varying the number of CWPs, air route segments and PRDs. Based on the framework, an adaptive method is developed to dynamically control the optimization process in minimizing the total air route cost. The proposed model is applied to a busy controlled airspace. And the obtained results show that after optimization the safety-related indicators: conflict number and controller workload reduced by 7.75% and 6.51% respectively. As for the cost-effectiveness indicators: total route length, total air route cost and non-linear coefficient, declined by 1.74%, 3.13% and 1.70% respectively. While the predictability indicator, total flight delay, saw a notable reduction by 7.96%. The proposed framework and methodology can also provide an insight in the understanding of the optimization to other network systems.     

基于粒子群算法的飞行冲突解脱问题

自由飞行可有效解决航线日益加剧的拥挤问题,但同时也增加了管制员管制监控的难度,从而使飞行冲突探测和解脱成为自由飞行的关键问题。粒子群算法（particleswaITn0ptimization）是一种群智能优化算法,尝试将其应用于飞行冲突解脱问题,构造了适合飞行冲突解脱问题的粒子表达方式,建立了冲突解脱问题的粒子群算法,成功解决了飞行冲突,并将其运行结果与遗传算法结果作了对比试验。实验结果表明。粒子群算法是求解飞行冲突解脱问题的一个较好方案。     

对流天气下空域通行能力短缺预警及响应综述

对流天气是空域通行能力短缺的主要原因之一。为了解决这一问题,需要通过理论和实践创新,建立对流天气条件下空域通行能力短缺的预警和应急响应机制,提高空域资源配置效率。从对流天气影响信息解释转换、容量评估与预警及空域响应预案三个方面梳理了国内外研究现状,总体趋势是:对流天气逐渐通过各种解释转换模型被量化为对空域和航路的影响;对流天气下空域通行能力主要受管制员工作负荷的限制,只有准确评估对流天气下的工作负荷,才能做出正确的通行能力短缺预警;对流天气响应方案,逐渐由地面等待、增加同航迹间隔、返航、备降等高耗能的流量控制措施,转向以灵活使用空域预案确保改航方案的实施方向发展。课题的应用前景是可以化解对流天气下交通需求与空域通行能力不平衡的矛盾,提高预警准确度,减少响应前置时间,提高流量管理与容量管理协同运行的效率,减轻对流天气造成的航班延误,减少航空器运行成本,实现节能减排的要求。     

基于贡献度模型方法对空中交通管制中心系统的效能评估

 空中交通管制(ATC)中心系统的效能变化,直接影响到管制员的工作负荷和管制中心所辖空域的交通容量,是ATC系统的关键运行指标。基于系统行为表现的效能概念框架,采用系统效能分析的贡献度模型方法,对ATC中心系统的运行环境和工作过程进行了建模分析,构建了一个由9个外部环境变量和50个内部单元变量构成的ATC中心系统行为关系模型。通过采集系统专家和管制人员对外部信息贡献度和内部功能关键度的等级判断,计算生成了反映系统内外因素变化对系统效能影响的系统效能贡献度模型,并利用该模型对一个实际运行的ATC中心系统进行了效能分析评估,初步揭示了ATC中心系统效能变化的特点和规律。评估结果与运行专家对系统效能的经验判断具有较高的吻合度,验证了所创建的ATC中心系统效能贡献度模型及其分析方法的合理性。     

空域交通复杂度计算方法研究

空域复杂度是指管制员所指挥的空域的复杂程度,包括可见的飞机运行、不可见的运行程序等,决定着管制员的工作负荷。而空域交通复杂度则是可见的飞机运行的部分,为其重要组成部分。将对空域交通复杂度进行分析研究,考虑到飞机分布不均匀,修正了飞机的数量,通过对飞机在垂直方向、水平方向、飞行速度的影响分析,得出了交通复杂度的计算公式。并利用雷达模拟机对某一空域进行了测算．得出该空域的交通复杂度的分布。     

中欧枢纽机场航班协同放行需求与对策研究

随着中欧之间航空运输量的不断增加,中欧几个主要枢纽机场之间互飞的航班量增长迅速,从欧洲空中交通流量管理系统发展的经验来看,协调枢纽机场航班放行时间可以显著地减少空域拥挤,减少航班延误,提高航班的正常性和可预测性.尝试从分析中国北京首都机场等几大枢纽机场中欧之间航班飞行流量、起降时刻出发,从减少中国枢纽机场拥挤的角度分析中欧协同放行的必要性,从航班和机场信息共享、协同放行机制等角度分析其可行性,以期望为进一步加强中欧航空合作打下基础.由于时间和数据限制,研究无法从欧洲空管角度做出类似的分析.