Visual Analytic Method for Metro Anomaly Detection and Diffusion
Joint Authors
Li, Yunhui
Shi, He
Zhang, Yong
Yin, Baocai
Wei, Yun
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-01
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
With the rapid development of urbanization in recent years, thousands of people have flooded into the city, which has brought tremendous pressure on the supervision and operation of relevant traffic management departments.
In particular, the unexpected events in the urban rail transit system have caused great troubles for city managers.
Aiming at the problem of abnormal passenger flow in the metro, this paper proposes a visual analytic method to support the abnormal passenger flow detection, verification, and diffusion analysis in the metro system.
The method provides an intuitive visual metaphor and allows users to perform simple interactive operations to verify abnormal passenger flow.
In addition, the method reveals the diffusion law of abnormal passenger flow in time and space in a two-dimensional diffusion view.
The Beijing Rail Transit AFC data are used to validate the developed system, and two reliable analysis cases are presented.
The system can help users quickly grasp the abnormal propagation rules and help them to develop different scheduling strategies for different anomalous propagation paths.
American Psychological Association (APA)
Li, Yunhui& Zhang, Yong& Shi, He& Wei, Yun& Yin, Baocai. 2020. Visual Analytic Method for Metro Anomaly Detection and Diffusion. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1181059
Modern Language Association (MLA)
Li, Yunhui…[et al.]. Visual Analytic Method for Metro Anomaly Detection and Diffusion. Journal of Advanced Transportation No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1181059
American Medical Association (AMA)
Li, Yunhui& Zhang, Yong& Shi, He& Wei, Yun& Yin, Baocai. Visual Analytic Method for Metro Anomaly Detection and Diffusion. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1181059
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181059