Computer Science ›› 2016, Vol. 43 ›› Issue (Z6): 425-429.doi: 10.11896/j.issn.1002-137X.2016.6A.101

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Method of Traffic Anomaly Detection with Incomplete Data

WANG Yu-ling and REN Yong-gong   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Development of urbanization process has brought serious traffic problems,and traffic anomaly detection becomes one of hot spots in the field of data mining.The traditional traffic management mainly uses video monitoring which has a limited efficiency for handling traffic problems.A method of traffic anomaly detection with incomplete data(Traffic Anomaly Detection,TAD) was proposed in this paper.Firstly,the correlation clustering obtains vehicle density information from mobile phone data and reduces the computation costs of processing incomplete data.Secondly,an adaptive parameter-free detection algorithm is designed to capture the distributed dynamic anomalies with phone call volume change rate on the roads,solving the uncertainty problem of road condition.Finally,anomaly trajectory algorithm is devised to retrieve anomaly distribution route and forecast influence scope,improving the efficiency of anomaly detection.Experimental results show that TAD methods can effectively detect abnormal traffic in different experimental conditions and our algorithm is better in efficiency and scalability compared with existing algorithms.

Key words: Anomaly detection,Incomplete data,Mobile phone data,Anomaly trajectory

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