Research on traffic congestion propagation law in terminal area based on association rule mining
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NETL
NSTL
万方数据
本文基于空中交通流运行现象建立交通拥挤传播规则挖掘模型,从数理角度分析并表征终端区交通流拥挤状态的传播现象.首先,对终端区交通流按照航段结构进行划分并给出交通状态评价指标,采用模糊C均值算法对终端区进场交通流状态进行聚类划分;其次,使用OApriori算法挖掘终端区进场交通流拥挤传播规则;最后,基于实测历史数据构建北京终端区全空域及机场模型(TAAM,total airspace and air-port modeler)仿真场景,模拟终端区在不同流量分布特征下的运行情况并进行分析,结果表明:本文模型分析所得的传播规律与实际情况相符,并发现优化终端区进场点流量分布能显著减少终端区拥挤状态的传播现象.
Based on the operation phenomenon of air traffic flow,a traffic congestion propagation rule mining model is estab-lished to analyze and characterize the propagation phenomenon of traffic flow congestion in the terminal area from a mathematical perspective.Firstly,the traffic flow in the terminal area is divided according to the segment structure and the traffic status evaluation index is given,and fuzzy C-means algorithm is applied to cluster the approach traffic flow status in the terminal area.Then,the OApriori algorithm is used to mine the congestion propagation law of approach traffic flow in the terminal area.Finally,based on the measured historical data,the total airspace and airport modeler(TAAM)simulation scene of Beijing terminal area is constructed to simulate and analyze the oper-ation of the terminal area under different flow distribution characteristics.The results show that the propagation law obtained from the proposed model is consistent with the actual situation,and it is found that optimizing the flow distribution at the entry point of the terminal area can significantly reduce the phenomenon of congestion propaga-tion in the terminal area.
air traffic flowassociation rulecongestion propagationOApriori algorithm
NETL
NSTL
万方数据
