Rail Transit User Classification Using Mobile Phone Data: A Case Study of Three Communities in Shanghai, China

Rail transit system is an important part of urban and regional transportation. Understanding rail transit users in terms of travel characteristics benefits the planning and design of better services. Mobile phone data is a novel dataset which enables the analysis of rail transit users’ travel behavior in the context of individual activity both in and out of the rail transit system. This paper investigated the classification of rail transit users with similar pattern profiles and the interpretation of passenger segmentation through the analysis of individual activity patterns. A mobile-phone-based methodology was proposed for the identification and characterization of rail transit travel behavior and individual activity. To determine the passenger segmentation, a classification of weekday rail transit users was developed based on the defined rail transit travel characteristics. Moreover, the individual activity patterns were subsequently analyzed to improve the interpretation of passenger segmentation. Due to the huge memory cost and running time resulting from the large-scale mobile phone dataset, a case study of three typical communities in Shanghai was carried out to prove the feasibility of the proposed method. Conclusions can be drawn that mobile phone data could be applied to determine the rail transit user segmentation. The analysis of individual activity patterns could benefit the overall understanding of user segmentation and help identify the possible bias in the rail transit use behavior of specific groups of interest. The proposed method and conclusion in this study could support more precise operational and strategic decisions.

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• Supplemental Notes:
  • This paper was sponsored by TRB committee AP065 Standing Committee on Rail Transit Systems.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Li, Weifeng
  • Cheng, Xiaoyun
  • Li, Jian
  • Yang, Dongyuan
• Conference:
  • Transportation Research Board 95th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2016-1-10 to 2016-1-14
• Date: 2016

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 23p
• Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Activity choices; Case studies; Cellular telephones; Rail transit; Transit riders; Travel behavior; Weekdays
• Geographic Terms: Shanghai (China)
• Subject Areas: Data and Information Technology; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01588164
• Record Type: Publication
• Report/Paper Numbers: 16-1307
• Files: PRP, TRIS, TRB, ATRI
• Created Date: Jan 28 2016 8:58AM