空中交通流非线性特征研究

发布时间：2018-06-16 19:50

本文选题：空中交通流 + 交通流识别　；参考：《中国民航大学》2016年硕士论文

【摘要】：深入剖析空中交通流时空特性是进行空中交通流仿真、预测与控制的重要前提。利用真实航迹数据从混沌与分形角度对空中交通流非线性特征进行研究。首先,分别针对综合航迹数据与ADS-B航迹数据库特点提出航迹数据处理流程,并根据错误轨迹数据特点提出错误轨迹数据识别与处理方法。针对目前空中交通流识别方法中普遍存在的问题,提出基于航路网络结构的空中交通流识别方法,在识别盛行交通流的同时确定交通流经过导航台序列。在此基础上构建空中交通流宏观与微观时间序列。第二,从宏观与微观角度,利用最大Lyapunov指数与递归图,对空中交通流的混沌性特征进行研究。空中交通流具有混沌特性,且不论从宏观还是微观角度均可对这种混沌特性进行识别,这种非线性混沌特征的强弱并不直接取决于交通流流量、交通流疏密程度或交通流类型。在宏观角度研究中混沌性较为显著的交通流,在微观角度混沌特性也较为显著。第三,从宏观与微观角度,利用关联维数对空中交通流的分形特征进行研究。同一交通流在从宏观与微观角度分析其分形特征时,分形维数不同。从宏观角度进行分析,不同航路交汇交通流产生的宏观交通流时间序列的关联维数相差较大,由不同跑道入口到达交通流产生的宏观交通流时间序列的关联维数相差较小。从微观角度进行分析,不同航路交汇交通流产生的微观交通流时间序列的关联维数相差较小,由不同跑道入口到达交通流产生的微观交通流时间序列的关联维数相差较大。最后,研究时间尺度对空中交通流宏观时间序列非线性特征的影响。不同时间尺度下空中交通流宏观时间序列具有不同形态特征,但均具有混沌特性。随着时间尺度的增大,宏观交通流表现出系统的确定性减小,随机性增强,宏观交通流对系统复杂性的表现能力降低。提出一种基于非线性特征分析的空中交通流宏观时间序列的时间尺度选择方法。
[Abstract]:It is an important prerequisite for air traffic flow simulation, prediction and control to deeply analyze the space-time characteristics of air traffic flow. The nonlinear characteristics of air traffic flow are studied from the point of view of chaos and fractal using real track data. Firstly, according to the characteristics of integrated track data and ADS-B track database, the processing flow of track data is proposed, and the identification and processing method of error track data is put forward according to the characteristics of error track data. Aiming at the common problems in the current air traffic flow identification methods, an air traffic flow identification method based on the network structure of air route is proposed, which can identify the prevailing traffic flow and determine the traffic flow passing through the navigation station at the same time. On this basis, the macro and micro time series of air traffic flow are constructed. Secondly, the chaos characteristics of air traffic flow are studied by using the maximum Lyapunov exponent and recursive graph from the macro and micro angles. Air traffic flow has chaotic characteristics, which can be recognized from both macroscopic and microscopic perspectives. The intensity of this nonlinear chaotic feature does not depend directly on the traffic flow, the density of traffic flow or the type of traffic flow. In the macroscopic study, the chaotic characteristic of traffic flow is obvious, and the chaotic characteristic is also obvious in microscopic angle. Thirdly, the fractal characteristics of air traffic flow are studied by using correlation dimension from macro and micro angles. The fractal dimension of the same traffic flow is different when analyzing its fractal characteristics from the macro and micro point of view. From the macro point of view, the correlation dimension of the time series of the macroscopic traffic flow produced by the intersection traffic flow of different routes is quite different, and the correlation dimension of the time series of the macroscopic traffic flow generated by the arrival of different runway entrances to the traffic flow is relatively small. From the microscopic point of view, the correlation dimension of the microscopic traffic flow time series generated by the intersection traffic flow of different routes is relatively small, and the correlation dimension of the microscopic traffic flow time series from different runway entrances to the traffic flow is quite different. Finally, the influence of time scale on the nonlinear characteristics of the macroscopic time series of air traffic flow is studied. The macroscopic time series of air traffic flow have different morphological characteristics, but all have chaotic characteristics. With the increase of the time scale, the macroscopic traffic flow shows a decrease in the certainty of the system, an increase in randomness, and a decrease in the performance of the macro-traffic flow to the complexity of the system. This paper presents a time scale selection method for macroscopic time series of air traffic flow based on nonlinear characteristic analysis.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：V355

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