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Systemic Congestion Propagation in the Airspace Network

机译：空域网络中的系统性拥塞传播

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To be different from the traditional concept of congestion, congestion propagation based on the correlation between aircraft is given. And the main resource shared and competed for in airspace is the air route network, especially the intersection linking the multiroute. The system composed of congestion propagation units operates in airspace network, which is limited by the network geometry and the correlation between aircraft. This paper presents models based on the congestion and propagation characteristics in complex network, predicting the trend of congestion propagation and the peak of congestion size. By analyzing the relationships between system parameters and congestion propagation and accounting for the effects of propagation across networks, this paper enhances the current dynamics models of congestion propagation in airspace. Firstly, a heterogeneous network model is introduced to reveal the propagation process of aircraft with different degrees of correlation. This is followed by the specification of two simplified models for short-term prediction, just taking the sector capacity, propagation rate, and dissipation rate into account. And the propagation rate and dissipation rate depend on the sector geometry and aircraft distribution. Using them (sector capacity, propagation rate, and dissipation rate), the prediction models are accurate in predicting the evolution of congestion peak and propagation trend in comparison with the sample data of intersections in the sector. Of them, the model with capacity limitation is more accurate on busy hour. And on non-busy hour, capacity is insensitive in predicting congestion clusters. Furthermore, the computing method of propagation rate and dissipation rate is given in our paper. Finally, a numerical analysis is performed, in which it is demonstrated that system capacity, propagation rate, and dissipation rate have different effects on congestion propagation in airspace. The results show that low propagation and high dissipation rates not only are nonlinear but also decrease the level of congestion in the propagation of congestion. In particular, of the three parameters, system capacity affects the rate of convergence, with a low-capacity system reaching a stable state quickly and therefore providing a basis for sector partitioning. The method proposed in this paper should enable air traffic controllers to better understand the characteristics of congestion and its propagation for the benefits of both congestion management and improvement of efficiency. Significantly, airspace designers can take congestion propagation into consideration for optimizing the airspace structure in the future.
机译：与传统的拥塞概念不同，基于飞机之间的相关性给出了拥塞传播。空域中共享和竞争的主要资源是空中航线网络，尤其是连接多航线的交叉路口。由拥塞传播单元组成的系统在空域网络中运行，这受到网络几何形状和飞机之间相关性的限制。本文基于复杂网络中的拥塞和传播特性，提出了模型，预测了拥塞传播的趋势和拥塞大小的峰值。通过分析系统参数与拥塞传播之间的关系，并考虑跨网络传播的影响，本文增强了当前在空域中拥塞传播的动力学模型。首先，引入异构网络模型来揭示具有不同相关度的飞机的传播过程。接下来是两个简化模型的规范，用于短期预测，只考虑了扇区容量，传播速率和耗散速率。传播率和耗散率取决于扇区的几何形状和飞机的分布。与扇区交叉口的样本数据相比，使用它们（扇区容量，传播速率和耗散率），预测模型可以准确地预测拥塞峰值的演变和传播趋势。其中，具有容量限制的模型在繁忙时间更为准确。在非繁忙时间，容量对于预测拥塞群集不敏感。此外，本文还给出了传播速率和耗散率的计算方法。最后，进行了数值分析，结果表明系统容量，传播速率和耗散速率对空域的拥塞传播有不同的影响。结果表明，低传播和高耗散率不仅是非线性的，而且降低了拥塞传播中的拥塞水平。特别是，在这三个参数中，系统容量会影响收敛速度，低容量系统会快速达到稳定状态，因此为扇区划分提供了基础。本文提出的方法应使空中交通管制员能够更好地了解拥塞及其传播的特征，从而从拥塞管理和提高效率两方面受益。重要的是，空域设计人员可以考虑拥塞传播，以在将来优化空域结构。

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