危險天氣下扇區(qū)空域復雜度和容量
發(fā)布時間：2018-12-15 08:07
【摘要】：高度擁擠的空域中,危險天氣快速變化且預報誤差較大的條件下,預測扇區(qū)容量以及優(yōu)化空域中交通流是非常復雜的問題。危險天氣具有難以準確預報其強度和范圍的特點,給危險天氣下空域容量評估帶來了困難,而空域動態(tài)容量的評估是有效實施空中交通流量管理的基礎(chǔ)。目前基于航空器架次的空域容量評估方法很難映射出交通態(tài)勢、扇區(qū)結(jié)構(gòu)及管制員負荷之間復雜關(guān)系,運用復雜度評估空域系統(tǒng)運行能力已成為當前空中交通管理領(lǐng)域的研究熱點。本文首先從復雜度來源角度,對空域復雜度進行分析和定義,總結(jié)了目前空域復雜度研究方法。針對危險天氣下空域容量評估研究尚未形成成熟理論的現(xiàn)狀,通過重點介紹航路利用率、最小割最大流、隨機空域容量等方面的理論成果,嘗試理清目前國外理論研究的范圍與框架,指出了該領(lǐng)域未來的研究方向和存在的關(guān)鍵問題。其次,本文基于空域復雜度評估方法中的擾動分析思想,根據(jù)扇區(qū)運行實際情況,建立扇區(qū)、航班流、危險天氣模型,采用調(diào)速法進行飛行沖突探測與解脫,定義空域復雜度計算方法,設(shè)計了復雜度可視化表示方法,對預測和降低空域復雜度提供支持。仿真結(jié)果表明,該方法能夠反應(yīng)出扇區(qū)交通態(tài)勢微觀特征,向空中交通管理提供了決策支持工具。最后,采用了最大流最小割擴展定理評估危險天氣存在時扇區(qū)最大通行量,應(yīng)用Folyd算法求解最短路徑,確定扇區(qū)最大通行量。通過隨機的多組天氣數(shù)據(jù),擬合回歸危險天氣覆蓋百分比與扇區(qū)最大通行量的方程式和曲線。仿真結(jié)果表明,回歸方程擬合準確度較高,對于預測危險天氣對扇區(qū)的影響有一定借鑒意義。
[Abstract]:In highly crowded airspace, the prediction of sector capacity and the optimization of traffic flow in airspace are very complicated under the condition that the dangerous weather changes rapidly and the prediction error is large. It is difficult to accurately predict the intensity and range of dangerous weather, which makes it difficult to evaluate the airspace capacity under dangerous weather. The assessment of dynamic airspace capacity is the basis of effective air traffic flow management. At present, it is difficult to map out the complex relationship among traffic situation, sector structure and controller load. The application of complexity in evaluating the operational capability of airspace systems has become a hot topic in the field of air traffic management. This paper firstly analyzes and defines the spatial complexity from the point of view of complexity source, and summarizes the current research methods of spatial complexity. In view of the fact that the research on the evaluation of airspace capacity in dangerous weather has not yet formed a mature theory, this paper mainly introduces the theoretical achievements in the aspects of route utilization ratio, minimum cut maximum flow, random airspace capacity, etc. This paper attempts to clarify the scope and framework of foreign theoretical research at present, and points out the future research direction and key problems in this field. Secondly, based on the idea of disturbance analysis in the method of airspace complexity evaluation, according to the actual situation of sector operation, the model of sector, flight flow and dangerous weather is established, and the speed regulation method is used to detect and resolve the flight conflict. The spatial complexity calculation method is defined, and the complexity visualization method is designed to support the prediction and reduction of spatial complexity. The simulation results show that the method can reflect the microscopic characteristics of traffic situation in sectors and provide a decision support tool for air traffic management. Finally, the maximum flow and minimum cut expansion theorem is used to evaluate the maximum traffic volume in the sector when dangerous weather exists, and the Folyd algorithm is applied to solve the shortest path to determine the maximum traffic volume in the sector. The regression equations and curves of the percentage of dangerous weather coverage and the maximum traffic volume of the sector are fitted by random multi-group weather data. The simulation results show that the fitting accuracy of the regression equation is high, which is useful for predicting the influence of dangerous weather on the sector.
【學位授予單位】：中國民航大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：V355.1;V321.2
本文編號：2380310
[Abstract]:In highly crowded airspace, the prediction of sector capacity and the optimization of traffic flow in airspace are very complicated under the condition that the dangerous weather changes rapidly and the prediction error is large. It is difficult to accurately predict the intensity and range of dangerous weather, which makes it difficult to evaluate the airspace capacity under dangerous weather. The assessment of dynamic airspace capacity is the basis of effective air traffic flow management. At present, it is difficult to map out the complex relationship among traffic situation, sector structure and controller load. The application of complexity in evaluating the operational capability of airspace systems has become a hot topic in the field of air traffic management. This paper firstly analyzes and defines the spatial complexity from the point of view of complexity source, and summarizes the current research methods of spatial complexity. In view of the fact that the research on the evaluation of airspace capacity in dangerous weather has not yet formed a mature theory, this paper mainly introduces the theoretical achievements in the aspects of route utilization ratio, minimum cut maximum flow, random airspace capacity, etc. This paper attempts to clarify the scope and framework of foreign theoretical research at present, and points out the future research direction and key problems in this field. Secondly, based on the idea of disturbance analysis in the method of airspace complexity evaluation, according to the actual situation of sector operation, the model of sector, flight flow and dangerous weather is established, and the speed regulation method is used to detect and resolve the flight conflict. The spatial complexity calculation method is defined, and the complexity visualization method is designed to support the prediction and reduction of spatial complexity. The simulation results show that the method can reflect the microscopic characteristics of traffic situation in sectors and provide a decision support tool for air traffic management. Finally, the maximum flow and minimum cut expansion theorem is used to evaluate the maximum traffic volume in the sector when dangerous weather exists, and the Folyd algorithm is applied to solve the shortest path to determine the maximum traffic volume in the sector. The regression equations and curves of the percentage of dangerous weather coverage and the maximum traffic volume of the sector are fitted by random multi-group weather data. The simulation results show that the fitting accuracy of the regression equation is high, which is useful for predicting the influence of dangerous weather on the sector.
【學位授予單位】：中國民航大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：V355.1;V321.2
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，本文編號：2380310
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