超长公路隧道交通流异常数据检测新方法

Fuhua Yu, Hongke Xu, Qi Wang, Guoqiang Li
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引用次数: 2

摘要

研究了交通流的特点,提出了一种基于曲线拟合的交通流异常数据检测方法。首先,通过聚类分析将历史交通流数据分为高速交通流和低速交通流;然后,对历史数据进行曲线拟合,得到确定安全区域范围的算法,并从计算安全区域范围外的实时交通流数据中检测出未确定的异常数据。最后,将未确定的异常数据确认为超出可接受误差范围的异常数据。以陕西某超长公路隧道的实时交通流数据为例,应用该方法检测超长公路隧道的实时交通流数据,结果表明该方法能够高效、有效地检测出超长公路隧道的异常数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Method of Abnormal Data Detection on Traffic Flow of Extra Long Highway Tunnel
Researched on the characteristic of the traffic flow, a new method of abnormal data detection on traffic flow based on the curve-fitting is presented. First, the historical data on traffic flow are divided into the traffic flow with high speed and the traffic flow with low speed by the clustering analysis. Then, the algorithm on the determination safety zone scope is obtained by the curve-fitting on the historical data and the undetermined abnormal data can be detected from the real-time traffic flow data for out of the calculated safety zone scope. Finally, the undetermined abnormal data are confirmed as the abnormal data which are even beyond the accepted error range. The real-time traffic flow data of an extra long highway tunnel in Shaanxi are taken as examples, and the detection result by the presented method shows that the abnormal data can be efficiently and effectively detected from the real-time data on traffic flow of extra long highway tunnel.
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