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  1. 研究報告
  2. モバイルコンピューティングと新社会システム(MBL)
  3. 2019
  4. 2019-MBL-093

Anomaly Event Detection using Bus Management Information -Case Study of Anomaly Operation Status Detection and Its Application

https://ipsj.ixsq.nii.ac.jp/records/200602
https://ipsj.ixsq.nii.ac.jp/records/200602
234c090b-d090-4142-a876-9f2192bbe361
名前 / ファイル ライセンス アクション
IPSJ-MBL19093005.pdf IPSJ-MBL19093005.pdf (1.7 MB)
Copyright (c) 2019 by the Information Processing Society of Japan
オープンアクセス
Item type SIG Technical Reports(1)
公開日 2019-11-13
タイトル
タイトル Anomaly Event Detection using Bus Management Information -Case Study of Anomaly Operation Status Detection and Its Application
タイトル
言語 en
タイトル Anomaly Event Detection using Bus Management Information -Case Study of Anomaly Operation Status Detection and Its Application
言語
言語 eng
キーワード
主題Scheme Other
主題 WiP
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_18gh
資源タイプ technical report
著者所属
Graduate School of Engineering, Nagoya University
著者所属
Graduate School of Engineering, Nagoya University/Institute of Innovation for Future Society, Nagoya University
著者所属
Graduate School of Engineering, Nagoya University/Institute of Innovation for Future Society, Nagoya University
著者所属
Graduate School of Engineering, Nagoya University/Institute of Innovation for Future Society, Nagoya University/Location Information Service Research Agency
著者所属(英)
en
Graduate School of Engineering, Nagoya University
著者所属(英)
en
Graduate School of Engineering, Nagoya University / Institute of Innovation for Future Society, Nagoya University
著者所属(英)
en
Graduate School of Engineering, Nagoya University / Institute of Innovation for Future Society, Nagoya University
著者所属(英)
en
Graduate School of Engineering, Nagoya University / Institute of Innovation for Future Society, Nagoya University / Location Information Service Research Agency
著者名 Wei, Sun

× Wei, Sun

Wei, Sun

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Kei, Hiroi

× Kei, Hiroi

Kei, Hiroi

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Takuro, Yonezawa

× Takuro, Yonezawa

Takuro, Yonezawa

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Nobuo, Kawaguchi

× Nobuo, Kawaguchi

Nobuo, Kawaguchi

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著者名(英) Wei, Sun

× Wei, Sun

en Wei, Sun

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Kei, Hiroi

× Kei, Hiroi

en Kei, Hiroi

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Takuro, Yonezawa

× Takuro, Yonezawa

en Takuro, Yonezawa

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Nobuo, Kawaguchi

× Nobuo, Kawaguchi

en Nobuo, Kawaguchi

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論文抄録
内容記述タイプ Other
内容記述 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.
論文抄録(英)
内容記述タイプ Other
内容記述 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.
書誌レコードID
収録物識別子タイプ NCID
収録物識別子 AA11851388
書誌情報 研究報告モバイルコンピューティングとパーベイシブシステム(MBL)

巻 2019-MBL-93, 号 5, p. 1-5, 発行日 2019-11-13
ISSN
収録物識別子タイプ ISSN
収録物識別子 2188-8817
Notice
SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
出版者
言語 ja
出版者 情報処理学会
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