西南交通大学学报2013，Vol.48Issue(1)：154-159,6.DOI:10.3969/j.issn.0258-2724.2013.01.024
基于需求不确定性的机场拥挤风险预测模型与方法
Risk Prediction Model and Methodology of Airport Congestion Based on Probabilistic Demand
摘要
Abstract
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.关键词
机场拥挤/风险预测/概率分布函数/交通需求/不确定性Key words
airport congestion/ risk prediction/ probabilistic distribution function/ traffic demand/uncertainty分类
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李善梅,徐肖豪,王飞..基于需求不确定性的机场拥挤风险预测模型与方法[J].西南交通大学学报,2013,48(1):154-159,6.基金项目
国家自然科学基金重点项目(61039001) （61039001）
中央高校基本科研业务费资助项目(ZXH2012C005,ZXH2011D010) （ZXH2012C005,ZXH2011D010）
