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Outlier mining based automatic incident detection on urban arterial road

  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Nowadays, Floating Car Data (FCD), which is becoming an important way to acquire traffic information, has been widely taken to estimate speed or travel time on road. In this paper, we introduce the concept of outlier mining into Automatic Incident Detection (AID) based on FCD and propose a novel AID approach on urban arterial road. According to the characteristics of incident, feature vector is selected from both spatial analysis and temporal analysis. Then a multilevel detection method that consists of filtering, outlier detection, and delay monitoring is proposed. The evaluation on real incident data and FCD gives the result that DR = 81.5% while FAR = 1.83%, which proves that the approach can achieve considerable effectiveness.

源语言英语
主期刊名Proceedings of the 6th International Conference on Mobile Technology, Application and Systems, Mobility '09
DOI
出版状态已出版 - 2009
活动6th International Conference on Mobile Technology, Application and Systems, Mobility '09 - Nice, 法国
期限: 2 9月 20094 9月 2009

出版系列

姓名Proceedings of the 6th International Conference on Mobile Technology, Application and Systems, Mobility '09

会议

会议6th International Conference on Mobile Technology, Application and Systems, Mobility '09
国家/地区法国
Nice
时期2/09/094/09/09

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