交通流时间序列模式相似性度量法  

Pattern similarity measurement of traffic flow time series

作　　者：弓晋丽[1] 彭贤武 

机构地区：[1]长沙理工大学交通运输工程学院,长沙410114 [2]三一重工股份有限公司,长沙410100

出　　处：《计算机工程与应用》2015年第6期103-107,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.50738004);公路工程教育部重点实验室开放基金资助项目(No.kfj120106)

摘　　要：针对交通流时间序列具有高维、高噪声的特性,设计了基于趋势变动、拟合优度和最小距离和百分比原则的联机分割算法用于时间序列维约简。对分割后的时间序列进行5元组分段线性表示,并据此定义五种常见的时间序列形状相似性距离。使用分层聚类算法分析它们在不同的交通流状态辨识中的效果,以此确定交通流时间序列的模式相似性度量方法。以上海南北高架东侧间部分路段固定线圈检测数据为例进行了实证分析,最终确定模式距离与欧氏距离组合方式为交通时序模式相似性度量的最佳方法。As high dimensional and high noise of traffic flow time series, the on-line segmented algorithm which is based on changing trends, goodness of fit and minimal distance/percentage principal is designed for time series dimension reduction. On the basis of segmentation results, the time-series is represented as 5 tuples piecewise linear form. Then five shapesimilarity distances of time-series are defined, and whose performance on discriminate of different traffic flow pattern are tested through cohesion hierarchical clustering. Taking the loop detector data from the eastern of Shanghai North-South expressway as an example, the method is verified. The combination of pattern distance and Euclidean distance is determined as the best method for pattern similarity measurement of traffic flow time series.

关 键 词：交通流 时间序列 模式相似性度量 

分 类 号：U491.112[交通运输工程—交通运输规划与管理]