区域空中交通流量控制研究

运用排队论思想，结合区域控制的特点建立了区域流量控制模型，分析了郑州区域管制中心实施流量控制的实际效果，研究结果表明，仅考虑单独区域流量控制，将使航班延误的不利影响逐级放大，理想的流量控制应该全面考虑所有受影响的区域，合理地选择控制时段和控制间隔，最大限度地利用空域资源，减少航班延误，保证空中交通的安全畅通。     

工业企业经营状态预警系统研究

本文通过对工业企业预警指标的研究，建立了预警指标体系及综合指标，阐述了预警原理及方法，建立了预警系统的初步框架，为企业经营者加强内部管理提供了有效的方法。     

小区域交通流协调控制技术及应用

提出了一种在线式小区域交通信号协调控制策略,其可行性已在实际应用得到证实。通过设置在交叉口处的车辆检测器不断采集车辆信息,实时调整关联路口间的相位差,并通过合理的交通配时,实现主干道双向绿波控制,从而有效地提升道路的通行能力。     

A multi-aircraft conflict detection and resolution method for 4-dimensional trajectory-based operation

Conflict Detection and Resolution(CDR) is the key to ensure aviation safety based on Trajectory Prediction(TP). Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional(4D) Trajectory-Based Operation(4DTBO), which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CDR from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CDR scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism(STP) for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.     

受限航路空域自主航迹规划与冲突管理技术

为了解决在基于航迹运行的空中交通管理自动化系统中人机意识同步的问题，以航路运行为对象，开展了面向受限空域的自主四维航迹（4DT）冲突探测与解脱（CD&R）技术研究。基于自由航线空域（FRA）环境，提出基于栅格的空域离散化处理与计算方法；在此基础上，提出受限空域自主航迹运行两阶段方法：阶段1运用可视图（VG）法和Dijkstra算法，实现了满足限制区约束的航空器期望航迹快速规划；阶段2提出航迹可达时空域模型及其图形化表达方法，并基于连续飞行动力学推导出了不同情况下的航空器位置更新模型，并采用局部冲突探测与解脱方法，以飞行距离最短为目标，实现航空器自主路径与速度联动规划，从而支撑空地、人机认知同步的无冲突四维航迹生成；最后，以中国西部典型空域为运行场景开展仿真实验，验证了所提方法的计算高效性和模型有效性，并对栅格尺寸和探测距离这2个关键参数进行了灵敏度分析。结果表明，所提方法能够支撑复杂空域高密度运行环境自主航迹运行，为推动自主空中交通系统发展提供了新思路和新方法。     

终端区最优飞行轨迹特征的研究

为了给飞机提供一条能满足多种指标要求的最优飞行轨迹,针对变分最优理论难以求解多指标优化问题,提出了命名为多次优化的方法,即将多要求的优化任务分成先后相继的多次任务,每次任务中选取一种不能边界转化的要求作为最优性能指标,而其余要求转化为边界条件.利用这一方法以时间、转弯次数、转弯角度为最优性能指标给出了终端区最优飞行轨迹的一般特征.     

飞机智慧座舱发展技术研究

未来飞机座舱智慧化转型是必然趋势,研究飞机智慧座舱发展技术能够为未来飞机智慧座舱的设计提供参考支撑。本文探讨了智能与智慧的区别,提出了飞机智慧座舱的概念与设计内涵,总结出深度感知与沉浸式交互、类人的认知及开放性与个性化定制服务的智慧座舱功能设计要素;梳理了发展飞机智慧座舱亟需解决的五项关键技术：多维度深度信息感知与融合技术、先进信息显示技术、沉浸式自然交互技术、智能态势认知技术、多智能体自主适应技术。通过关键技术的分析对未来飞机智慧座舱的发展提出了新的思考。     

一个自主Agent框架及其决策

自主性是Agent的最重要的特征。本提出一个自主Agent的框架及其相应的决策机制。首先介绍了用于描述自主Agent的语言;然后基于BDI模型和情境演算理论,提出一个自主Agent的框架;最后给出自主Agent的一种决策过程。     

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

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.