@inproceedings{762441881b1746818398632f5265068a,
title = "A new method of abnormal data detection on traffic flow of extra long highway tunnel",
abstract = "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.",
keywords = "Abnormal data, Curve-fitting, Data detection, Safety zone, Traffic flow",
author = "Fuhua Yu and Hongke Xu and Qi Wang and Guoqiang Li",
year = "2010",
doi = "10.1109/LEITS.2010.5665031",
language = "英语",
isbn = "9781424487783",
series = "2010 International Conference on Logistics Engineering and Intelligent Transportation Systems, LEITS2010 - Proceedings",
pages = "59--62",
booktitle = "2010 International Conference on Logistics Engineering and Intelligent Transportation Systems, LEITS2010 - Proceedings",
note = "2010 International Conference on Logistics Engineering and Intelligent Transportation Systems, LEITS2010 ; Conference date: 26-11-2010 Through 28-11-2010",
}