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A new framework for traffic anomaly detection

文献类型：会议论文

作者Lan, Jinsong5,6; Long, Cheng2; Wong, Raymond Chi-Wing2; Chen, Youyang3; Fu, Yanjie4; Guo, Danhuai5; Liu, Shuguang7; Ge, Yong1; Zhou, Yuanchun5; Li, Jianhui5
出版日期2014
会议日期April 24, 2014 - April 26, 2014
会议地点Philadelphia, PA, United states
DOI10.1137/1.9781611973440.100
页码875-883
英文摘要Trajectory data is becoming more and more popular nowadays and extensive studies have been conducted on trajectory data. One important research direction about trajectory data is the anomaly detection which is to find all anomalies based on trajectory patterns in a road network. In this paper, we introduce a road segment-based anomaly detection problem, which is to detect the abnormal road segments each of which has its "real" traffic deviating from its "expected" traffic and to infer the major causes of anomalies on the road network. First, a deviation-based method is proposed to quantify the anomaly of reach road segment. Second, based on the observation that one anomaly from a road segment can trigger other anomalies from the road segments nearby, a diffusionbased method based on a heat diffusion model is proposed to infer the major causes of anomalies on the whole road network. To validate our methods, we conduct intensive experiments on a large real-world GPS dataset of about 23,000 taxis in Shenzhen, China to demonstrate the performance of our algorithms. Copyright © SIAM.
会议录14th SIAM International Conference on Data Mining, SDM 2014
语种英语
源URL[http://119.78.100.138/handle/2HOD01W0/9768]  
专题中国科学院重庆绿色智能技术研究院
作者单位1.University of North Carolina, Charlotte, United States
2.Hong Kong University of Science and Technology, Hong Kong, Hong Kong;
3.Beijing Institute of Technology, China;
4.Rutgers University, United States;
5.Computer Network Information Center, Chinese Academy of Sciences, China;
6.University of Chinese Academy of Sciences, China;
7.Chongqing Institutes of Green and Intelligent Technology, Chinese Academy of Sciences, China;
推荐引用方式
GB/T 7714		 Lan, Jinsong,Long, Cheng,Wong, Raymond Chi-Wing,et al. A new framework for traffic anomaly detection[C]. 见:. Philadelphia, PA, United states. April 24, 2014 - April 26, 2014.

入库方式： OAI收割

来源：重庆绿色智能技术研究院

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