終端區(qū)動態(tài)交通特征與運行態(tài)勢研究
發(fā)布時間：2018-07-14 14:15
【摘要】：面對空中交通運輸需求的快速增加,運用技術(shù)手段提升空管運行效率與服務(wù)能力以緩解供需矛盾是當前行之有效的方式。由于傳統(tǒng)經(jīng)驗型的粗放運行管理模式,未能有效利用空中交通特性、規(guī)律及時空特征,以幫助認知運行的動態(tài)性與問題所在,因此難以實現(xiàn)針對性、精細化的管理與科學決策。隨著空管運行數(shù)據(jù)采集的不斷完善,利用數(shù)據(jù)挖掘技術(shù)發(fā)掘空中交通的運行規(guī)律、動態(tài)模式、場景分類等隱含知識具備了基礎(chǔ)條件,相應(yīng)的智能數(shù)據(jù)分析與決策技術(shù)也成為當前的研究熱點與趨勢。本文總結(jié)了空中交通領(lǐng)域交通特性分析與智能決策支持的研究現(xiàn)狀與趨勢,以終端區(qū)為對象,從管制運行與流量管理的不同應(yīng)用決策需求出發(fā),深入研究了空中交通特性與運行態(tài)勢相關(guān)的若干數(shù)據(jù)分析與挖掘方法,以期提供科學有效的決策數(shù)據(jù)與模型支持,主要內(nèi)容包括:(1)機場飛行區(qū)航班運行時間的特征分析與決策應(yīng)用。利用聚類方法提取飛行區(qū)場面滑行階段運行時間的聚集分布模式,從航班運行的階段構(gòu)成出發(fā),將場面滑行時間的周期性單日變化特征應(yīng)用于城市對航班運行時間的差異化度量,設(shè)計了一種按階段獨立計算、按條件整合的運行時間估算方法,以提供計劃編制的依據(jù);針對惡劣氣象對航班離場階段時間的影響,設(shè)計了適用于機場的氣象影響程度指數(shù)(WITI),研究了機場WITI與不同離場延誤特征間的變化關(guān)系及規(guī)律,建立了回歸模型,以支持預測氣象條件下的終端區(qū)離場階段延誤的早期評判。(2)建立了終端區(qū)交通流識別方法與交通流相態(tài)判別模型。從空中交通流特性分析與狀態(tài)識別的需求出發(fā),首先利用改進的相似性度量與譜聚類實現(xiàn)了終端區(qū)各類交通流的識別與參考航跡提取,抽象了表征交通流相態(tài)的特征度量。通過特征間的數(shù)值關(guān)系與變化規(guī)律,并結(jié)合領(lǐng)域認知,界定了終端區(qū)交通流的自由態(tài)、平穩(wěn)態(tài)與擁堵態(tài),及各相態(tài)對應(yīng)的管制運行特性與演化過程。以此為經(jīng)驗,構(gòu)建了因子分析與遺傳EM聚類的交通流相態(tài)模糊識別方法,實現(xiàn)交通流相態(tài)影響因素分析與隱性特征向量的抽取,為終端區(qū)流量時空分布調(diào)配與飛行程序優(yōu)化提供支撐。(3)構(gòu)建了終端區(qū)交通態(tài)勢模糊評價方法與態(tài)勢等級預測模型。首先從交通態(tài)勢評價的指標缺陷及主觀性問題出發(fā),通過提取終端區(qū)宏觀與微觀的交通特性,從進離場及總量三個維度構(gòu)建態(tài)勢指標描述,進而設(shè)計了基于中介真值程度度量與熵理論權(quán)值賦值的終端區(qū)交通態(tài)勢模糊評價模型,實現(xiàn)了態(tài)勢的客觀判別與差異化度量。同時,鑒于態(tài)勢的模糊性與認知差異,以及流量調(diào)配對交通態(tài)勢識別的需求,設(shè)計了BP神經(jīng)網(wǎng)絡(luò)模型,并利用中介評價結(jié)果與實際管制認知結(jié)果設(shè)定的樣本集合進行模型訓練與驗證,實現(xiàn)了終端區(qū)交通態(tài)勢等級的快速準確預測。(4)設(shè)計了終端區(qū)ATFM決策支持概念框架與可擴展平臺架構(gòu)。由流量管理的目標與泛化內(nèi)涵出發(fā),界定了終端區(qū)運行決策支持的應(yīng)用范疇及方法體系,并從流量管理時效階段與決策應(yīng)用領(lǐng)域維度,實現(xiàn)具體應(yīng)用決策方法的關(guān)聯(lián),構(gòu)建了可擴展的終端區(qū)ATFM決策支持概念框架與一般決策過程框架。以此為依據(jù),進一步建立了決策信息抽取的層次化概念模型,設(shè)計了一種具備擴展能力與松耦合特征的多層次平臺體系框架,通過決策邏輯、數(shù)據(jù)挖掘方法及特征/屬性度量的分離設(shè)計,支持應(yīng)用工具的快速開發(fā)與配置。為終端區(qū)運行決策支持方法的應(yīng)用、研究與工程實施提供科學參考。最后,對本文的研究成果進行了概括性總結(jié),并針對現(xiàn)有研究的缺陷與需求外延,對進一步的研究工作內(nèi)容及方向進行了展望。
[Abstract]:In the face of the rapid increase in the demand for air transportation, it is an effective way to use technical means to improve the efficiency and service ability of air traffic tube in order to alleviate the contradiction between supply and demand. As the problem lies, it is difficult to realize the pertinence, fine management and scientific decision. With the continuous improvement of the data collection of the air traffic management, the underlying conditions of the hidden knowledge, such as the running law of air traffic, the dynamic mode, the scene classification, and so on, are provided with the data mining technology, and the corresponding intelligent data analysis and decision technology have also become the present. This paper summarizes the current situation and trend of traffic characteristics analysis and intelligent decision support in the field of air traffic. Based on the terminal area as the object, starting from the different application decision requirements of the control operation and the flow management, a number of data analysis and mining methods related to the air traffic characteristics and the transportation situation are deeply studied. In order to provide scientific and effective decision data and model support, the main contents include: (1) the characteristics analysis and decision application of the flight time of the airport flight area. The clustering method is used to extract the aggregation distribution pattern of the running time of the flight stage, starting from the stage of the flight operation, and taking the cyclical single time of the skidding time. The diurnal variation characteristics are applied to the difference degree of the flight time of the city, and a method to estimate the running time according to the conditions is designed to provide the basis for the planning, and the meteorological influence index (WITI) for the airport is designed for the effect of the bad weather on the departure time of the flight. The relationship between the airport WITI and the characteristics of different departure delays is investigated. A regression model is established to support the early evaluation of the delay in terminal departure stage under the forecast weather conditions. (2) a traffic flow identification method and a traffic flow phase state discrimination model are established. First, we use improved similarity measure and spectral clustering to realize the recognition and reference track extraction of all kinds of traffic flow in terminal area, abstract the characteristic measurement of traffic flow phase state, and define the free state of traffic flow in terminal area, flat steady state and congestion state through the domain cognition. The characteristic and evolution process of phase state corresponding control operation. In this way, a traffic flow phase state fuzzy recognition method of factor analysis and genetic EM clustering is constructed to realize the analysis of the factors of traffic flow phase state and the extraction of the recessive characteristic vector, which provides support for the spatial and temporal distribution and optimization of the terminal area. (3) the terminal is constructed. The fuzzy evaluation method and the situation grade prediction model of the regional traffic situation. First, starting from the index defect and subjective problem of the traffic situation evaluation, by extracting the macroscopic and microscopic traffic characteristics of the terminal area, the description of the situation index is constructed from three dimensions of entering the field and the total amount, and then based on the measure of the true value of the intermediary and the entropy theory. At the same time, the BP neural network model is designed in view of the ambiguity of the situation and the difference of cognition and the demand for traffic situation recognition, and the sample set is set up by the results of intermediary evaluation and the actual control cognitive results. According to the training and verification of the model, the rapid and accurate prediction of traffic situation level in terminal area is realized. (4) the concept framework and extensible platform architecture of terminal area ATFM decision support are designed. The application category and method system of the terminal operation decision support are defined by the target and generalization of traffic management. The effect phase and the decision application domain dimension, the realization of the relevance of the specific application decision method, the extensible conceptual framework of ATFM decision support and the general decision process framework. Based on this, a hierarchical conceptual model of decision information extraction is established, and a kind of multiple features with the expansion ability and loosely coupled is designed. The framework of hierarchical platform system is designed to support the rapid development and configuration of application tools through decision logic, data mining and feature / attribute measurement. It provides a scientific reference for the application of decision support methods for terminal operation, and provides a scientific reference for the implementation of the research and engineering implementation. The shortcomings and demands of research are discussed, and further research contents and directions are prospected.
【學位授予單位】：南京航空航天大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：V355.1
，
本文編號：2121907
[Abstract]:In the face of the rapid increase in the demand for air transportation, it is an effective way to use technical means to improve the efficiency and service ability of air traffic tube in order to alleviate the contradiction between supply and demand. As the problem lies, it is difficult to realize the pertinence, fine management and scientific decision. With the continuous improvement of the data collection of the air traffic management, the underlying conditions of the hidden knowledge, such as the running law of air traffic, the dynamic mode, the scene classification, and so on, are provided with the data mining technology, and the corresponding intelligent data analysis and decision technology have also become the present. This paper summarizes the current situation and trend of traffic characteristics analysis and intelligent decision support in the field of air traffic. Based on the terminal area as the object, starting from the different application decision requirements of the control operation and the flow management, a number of data analysis and mining methods related to the air traffic characteristics and the transportation situation are deeply studied. In order to provide scientific and effective decision data and model support, the main contents include: (1) the characteristics analysis and decision application of the flight time of the airport flight area. The clustering method is used to extract the aggregation distribution pattern of the running time of the flight stage, starting from the stage of the flight operation, and taking the cyclical single time of the skidding time. The diurnal variation characteristics are applied to the difference degree of the flight time of the city, and a method to estimate the running time according to the conditions is designed to provide the basis for the planning, and the meteorological influence index (WITI) for the airport is designed for the effect of the bad weather on the departure time of the flight. The relationship between the airport WITI and the characteristics of different departure delays is investigated. A regression model is established to support the early evaluation of the delay in terminal departure stage under the forecast weather conditions. (2) a traffic flow identification method and a traffic flow phase state discrimination model are established. First, we use improved similarity measure and spectral clustering to realize the recognition and reference track extraction of all kinds of traffic flow in terminal area, abstract the characteristic measurement of traffic flow phase state, and define the free state of traffic flow in terminal area, flat steady state and congestion state through the domain cognition. The characteristic and evolution process of phase state corresponding control operation. In this way, a traffic flow phase state fuzzy recognition method of factor analysis and genetic EM clustering is constructed to realize the analysis of the factors of traffic flow phase state and the extraction of the recessive characteristic vector, which provides support for the spatial and temporal distribution and optimization of the terminal area. (3) the terminal is constructed. The fuzzy evaluation method and the situation grade prediction model of the regional traffic situation. First, starting from the index defect and subjective problem of the traffic situation evaluation, by extracting the macroscopic and microscopic traffic characteristics of the terminal area, the description of the situation index is constructed from three dimensions of entering the field and the total amount, and then based on the measure of the true value of the intermediary and the entropy theory. At the same time, the BP neural network model is designed in view of the ambiguity of the situation and the difference of cognition and the demand for traffic situation recognition, and the sample set is set up by the results of intermediary evaluation and the actual control cognitive results. According to the training and verification of the model, the rapid and accurate prediction of traffic situation level in terminal area is realized. (4) the concept framework and extensible platform architecture of terminal area ATFM decision support are designed. The application category and method system of the terminal operation decision support are defined by the target and generalization of traffic management. The effect phase and the decision application domain dimension, the realization of the relevance of the specific application decision method, the extensible conceptual framework of ATFM decision support and the general decision process framework. Based on this, a hierarchical conceptual model of decision information extraction is established, and a kind of multiple features with the expansion ability and loosely coupled is designed. The framework of hierarchical platform system is designed to support the rapid development and configuration of application tools through decision logic, data mining and feature / attribute measurement. It provides a scientific reference for the application of decision support methods for terminal operation, and provides a scientific reference for the implementation of the research and engineering implementation. The shortcomings and demands of research are discussed, and further research contents and directions are prospected.
【學位授予單位】：南京航空航天大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：V355.1
，
本文編號：2121907
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