终端区空中交通流到达模式识别  

Arrival Pattern Recognition of Terminal Airspace Traffic Flow

作　　者：郑旭芳 王超[1] 

机构地区：[1]中国民航大学空中交通管理学院,天津300300

出　　处：《航空计算技术》2015年第3期67-71,共5页Aeronautical Computing Technique

基　　金：国家自然科学基金项目资助(61039001);国家科技支撑计划项目资助(2011BAH24B08)

摘　　要：为了实现对终端区空中交通流到达情况更加准确的分析,针对目前常用的流量统计方法中所存在的问题,提出了交通流到达模式概念,并对基于聚类思想的到达模式识别方法进行了研究。在对交通流到达时序数据提取的基础上,利用基于免疫优化算法的聚类方法实现了对交通流到达模式的识别。对交通流到达模式特征进行了分析,并结合滑动时间窗算法提出了交通高峰小时及峰值流量计算方法。通过实例分析证明了方法的可行性与准确性。To achieve a more accurate analysis of arrival traffic flow in terminal airspace and to improve the widely used statistical method of air traffic flow,the concept of air traffic flow arrival pattern is presented. Based on the concept,the method of pattern recognition of arrival pattern which based on clustering theory is investigated. The arrival time series data of each traffic flow in terminal airspace is extracted from the radar trajectory data first. The traffic flow arrival pattern is recognized by the clustering method which based on the immune optimization algorithm. The characteristics of each pattern are analyzed. The peak traffic hour and the peak traffic value of each arrival pattern are calculated by the sliding time window algorithm. The feasibility and accuracy of the proposed method are proved by the experiment analysis.

关 键 词：终端区空域 交通流分析 数据挖掘 模式识别 免疫优化算法 

分 类 号：V328[航空宇航科学与技术—人机与环境工程]