Real-Time Passenger Flow Anomaly Detection Considering Typical Time Series Clustered Characteristics at Metro Stations

Author:

Gu Jinjing1,Jiang Zhibin2,Fan Wei “David”3ORCID,Wu Jiameng4,Chen Jingjing5

Affiliation:

1. Postdoctoral, Dept. of Computer Science and Technology, Key Laboratory of Embedded System and Service Computing, Ministry of Education, College of Transportation Engineering, Tongji Univ., Shanghai 201804, China; Key Laboratory of Road and Traffic Engineering of the State Ministry of Education, Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety, Tongji Univ., 4800 Cao’an Rd., Jiading District, Shanghai 201804, China.

2. Associate Professor, College of Transportation Engineering, Key Laboratory of Road and Traffic Engineering of the State Ministry of Education, Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety, Tongji Univ., 4800 Cao’an Rd., Jiading District, Shanghai 201804, China.

3. Director, USDOT Center for Advanced Multimodal Mobility Solutions and Education; Professor, Dept. of Civil and Environmental Engineering, Univ. of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223 (corresponding author). ORCID: .

4. Master Candidate, College of Transportation Engineering, Key Laboratory of Road and Traffic Engineering of the State Ministry of Education, Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety, Tongji Univ., 4800 Cao’an Rd., Jiading District, Shanghai 201804, China.

5. Senior Engineer, Shanghai No. 4 Metro Operation Co., Ltd., 288 North Zhongshan Rd., Zhabei District, Shanghai 200070, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

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