Risk prediction model and methodology of airport congestion based on probabilistic demand

被引：0

作者：

Li, Shanmei ^{[1
]}

Xu, Xiaohao ^{[2
]}

Wang, Fei ^{[2
]}

机构：

[1] School of Computer Science and Technology, Tianjin University

[2] Air Traffic Management Research Base, Civil Aviation University of China

来源：

Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University | 2013年 / 48卷 / 01期

关键词：

Airport congestion; Probabilistic distribution function; Risk prediction; Traffic demand; Uncertainty;

D O I：

10.3969/j.issn.0258-2724.2013.01.024

中图分类号：

学科分类号：

摘要：

In order to obtain the probabilistic distribution and variation of the airport traffic demand for a future time interval and quantify the uncertainty of airport demand, the influence of arrival-departure timing on traffic demand prediction was analyzed from the viewpoint of uncertainty in traffic demand. Based on the uncertainty of transformation among traffic demands of multiple intervals, a probabilistic distribution model of airport arrival and departure capacity demand for multiple intervals was established. On this basis, a risk prediction model of airport congestion was developed by matching the departure traffic demand with the arrival-departure capacity curve. In addition, specific steps and method for solving the model were presented. The proposed models were verified using the real flight data of the Atlanta (ATL) airport. The results show that the departure traffic demand values by the probabilistic demand prediction are much more closer to the real demand values than by the deterministic prediction method. The risk prediction model and method could increase the accuracy of airport congestion prediction to 80%, in comparison to the 60% accuracy of the deterministic prediction method. The validity of the proposed method was also verified using the real flight data of the San Francisco (SFO) airport with an accuracy up to 87.5%. Therefore, the proposed method can provide a theoretic foundation for airport congestion management.

引用

页码：154 / 159

页数：5

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