舰船电子工程2025，Vol.45Issue(1)：135-140,6.DOI:10.3969/j.issn.1672-9730.2025.01.027
基于高斯核密度的终端区高密度交通流识别
Gaussian Kernel Density-based Identification of High-density Traffic Flows in Terminal Areas
摘要
Abstract
With the increase of flight volume terminal area congestion occurs frequently,the identification of abnormal density traffic flow has become a research hotspot.Aiming at the above problems,this paper adopts the method of Gaussian kernel density analysis based on the peak period trajectory data of the terminal area to visualize and analyze the high-density area of air traffic,re-vealing the spatio-temporal evolution law of congestion in the terminal area,and providing a reference basis for the alleviation and optimization direction of air traffic congestion.The collected terminal area aerial track data during peak hours are analyzed by gener-ating a traffic flow density map of Chengdu terminal area through Gaussian kernel density of geographic information software Arc-Map.The results show that the high-density operation areas during peak hours are all at the junction of sector 6 and sector 7,start-ing from Tianfu Airport and ending at the rightmost junction of sector 6 and sector 31 after the waypoint ZGA,and the overall trend of the high-density traffic flow develops in the northeast direction.The mining of the distribution pattern of high-density traffic flow can improve the accuracy and scientificity of the controller's grasp of the congestion situation in the terminal area.关键词
终端区/交通流识别/核密度分析/地理信息系统Key words
terminal area/traffic flow recognition/kernel density analysis/geographic information system分类
交通工程引用本文复制引用
董兵,李昕倩,罗创,刘安全,赵泽荣..基于高斯核密度的终端区高密度交通流识别[J].舰船电子工程,2025,45(1):135-140,6.基金项目
高校基本科研业务费资助项目"基于卷积循环神经网络航行通告要素智能识别及应用研究"(编号:J2023-050)资助. （编号:J2023-050）
