@techreport{oai:ipsj.ixsq.nii.ac.jp:00200511,
 author = {Wei, Sun and Kei, Hiroi and Takuro, Yonezawa and Nobuo, Kawaguchi and Wei, Sun and Kei, Hiroi and Takuro, Yonezawa and Nobuo, Kawaguchi},
 issue = {5},
 month = {Nov},
 note = {At present, the anomaly detection based on GPS data of buses has become a hot spot in the field of intelligent transportation. The goal of anomaly detection aims to automatically detect the abnormal situation of the city, which is also a key step to develop the intelligence of traffic system. This research aims to propose the anomaly detection at three aspects: the definition, the method, and the practical use of the detection results. In this paper, we focus on the abnormality of traffic situations, which leads to anomaly operation status (bus bunching), caused by mutation of the number of the passenger or the traffic accident. We propose a method for detecting bus bunching. We define a situation that satisfy the three conditions as bus bunching. The analysis result shows that the data of April 2017 of the city Okazaki occurred 49 times and occurred at Kouseicho stop and Daijuji stop at 6p.m frequently. After analyzing the data of the bus bunching, we plan to develop a module to predict the bus bunching., At present, the anomaly detection based on GPS data of buses has become a hot spot in the field of intelligent transportation. The goal of anomaly detection aims to automatically detect the abnormal situation of the city, which is also a key step to develop the intelligence of traffic system. This research aims to propose the anomaly detection at three aspects: the definition, the method, and the practical use of the detection results. In this paper, we focus on the abnormality of traffic situations, which leads to anomaly operation status (bus bunching), caused by mutation of the number of the passenger or the traffic accident. We propose a method for detecting bus bunching. We define a situation that satisfy the three conditions as bus bunching. The analysis result shows that the data of April 2017 of the city Okazaki occurred 49 times and occurred at Kouseicho stop and Daijuji stop at 6p.m frequently. After analyzing the data of the bus bunching, we plan to develop a module to predict the bus bunching.},
 title = {Anomaly Event Detection using Bus Management Information -Case Study of Anomaly Operation Status Detection and Its Application},
 year = {2019}
}