面向多维性能的柔性空域与航迹互适应机理与调控方法

Flexible Airspace (FA), which is defined as an adaptive flight space having dynamic 3-D boundaries and free route structure, is a new airspace configuration that essentially supports the significant revolution towards Trajectory-Based Operation (TBO) and Performance-Based Air Traffic Management (P-ATM) in the next generation of air transportation system. In this proposal, we put emphasis on the mechanism analysis and control method of co-adaption between flexible airspace and 4-D trajectory based on required performance in en route operation, aiming at exploring the underlying fundamental scientific problem and efficient optimal solutions of air traffic management in FA operation. To start with, from the perspective of complexity, System Dynamics modelling and hybrid fast-time/teal-time simulations are conducted to understand the coevolution and mutual influence between complex traffic situations and controller’s cognition dynamics during trajectory-based operation in flexible airspace. Then, based on extracting multi-dimensional order parameters that characterize air traffic operational performance including complexity, safety, efficiency, economy, etc., analytical methods and dynamic fuzzy machine learning techniques are adopted to establish the mapping between critical state of performance and airspace/trajectory fundamental attributes, as well as dynamic disruptions, in order to reveal the mechanism of multi-dimensional performance-oriented co-adaption between flexible airspace and trajectory using inverse analysis based on a multi-attribute multi-criterion adaptation assessment metric. In the end, from perspective of Complex Adaptive System (CAS), flexible airspace and trajectory are collaboratively optimized for dynamic environment, to enhance the robustness and resilience, as well as operational performance in trajectory-based high density flexible airspace during normal and abnormal situations, from strategic, pre-tactical to tactical level. The explorations of the fundamental nature and required key capabilities of coordinated trajectory-based operation in flexible airspace, would partially lay a solid theoretical basis for the development of integrated, collaborative and intelligent air traffic operation, especially for the transition of performance-based air transport system worldwide.

柔性空域是具有动态三维边界和灵活航线结构的高自由度、适应性飞行空间，是支撑空中交通系统向基于航迹和性能运行变革的新型空域形态。本课题以高空航路运行为对象，开展面向性能的柔性空域与航迹互适应机理和调控方法研究，探索柔性空域空中交通管理蕴含的基础科学问题。以复杂性为切入，采用动态系统建模和快速/实时混合仿真方法，剖析柔性空域航迹运行交通态势主客观关联表征及互作用模式；在此基础上，提炼柔性空域航迹运行多维性能序参量，采用解析法和动态模糊机器学习框架，建立空域航迹特征属性、外界扰动与性能临界态的映射关系，提出空域与航迹多属性多准则适配性度量，反演揭示面向性能的柔性空域与航迹多路径互适应演化机理；从复杂适应系统角度研究柔性空域与航迹跨时域多场景协同调控方法，提升常态和突发异态柔性空域航迹运行性能的鲁棒性和恢复力，为空中交通一体化、协同化和智能化发展，特别是基于性能的航空运输系统转型奠定部分理论基础。

面向基于性能的灵活四维轨迹自主运行世界科技前沿和我国国家空域系统建设重大迫切需求，聚焦空域与航迹互适应柔性调控关键科学问题，针对互适应机理客观完备性、跨时域调控均衡鲁棒性和多主体决策协同透明性三大关键挑战，以基于时间约束的柔性空域航迹时空可达域建模为关键基础，采用概率计算、动力系统等方法，建立了“人-空-迹”多维多要素复合的空域运行性能表征体系，通过设计多类型多场景人在环实验，量化解析了柔性空域航迹运行模式下“管制员-飞行流”复杂互影响共演化特征，指出非稳态状态下管制行为与轨迹行为的混沌性质，首次揭示了鲁棒性弱化是四维航迹异质速度混合造成空域运行性能下降的内在机制。在此基础上，面向战略和预战术阶段，针对大范围高空空域轨迹效率与经济性不佳问题，提出了柔性航路空域概念，建立了航路点与扇区边界动态配置的两阶段方法，实现计划轨迹与扇区之间的一体化规划；针对机场进近空域连续下降高密度运行难题，提出了倒皇冠型新型进近空域概念，建立了新空域下的轨迹运行模式，验证了新型空域的高经济性和大容量潜力，实现了适应动态需求的多层次柔性空域与航迹协同规划。此外，面向战术和实时阶段，针对常态高密度和突发空域限制等复杂场景，建立了空地/人机认知决策协同框架，突破了性能驱动的柔性空域空地一体四维轨迹自主运行技术，实现了大规模航空器无冲突飞行轨迹的秒级管控，支撑柔性空域灵活精准四维航迹高性能运行。研究成果应用于国家空域精细化管理改革等国家重大任务，为我国国家空域系统建设和空中交通管理模式变革，提升空中交通运行安全、效率、环保等综合性能，提供新思路、新方法和新技术。