Unveiling Urban Commuting Structure from Mobile Phone Data: A Case Study in Shanghai, China

City commuting structure has always been a core research topic in transportation and urban planning. The emergence of pervasive, geospatial data from individuals allow us to study the job-housing relationship and explore the urban functional structure. Using mobile phone data, the authors study the commuting pattern of residents to unveil the commuting structure of Shanghai. First of all, the authors identify the residents and commuters and extract their home and job anchor points. Then, they built a complex network on traffic analysis zones based on their job-housing relationships and apply community detection method to decompose the network into communities. The community detection algorithm iterates twice and depicts a two-level hierarchical commuting structure for Shanghai. The result show that residential commuting behaviors highly restricted by the administrative boundaries, especially in suburban area. The commuting structure in Shanghai can be simplify into a combination of concentric, sector and multiple nuclei structure. Comparing the metro line with the communities, the authors find that metro line network plays an important role in forming the city commuting structure. Finally, they study the impact of missing data, and find that it will not significantly influence the result of community detection. This study provides insights into commuting patterns and city commuting structures, which could potentially help to understand the residential commuting demand and support urban transportation planning.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABJ30 Standing Committee on Urban Transportation Data and Information Systems.
• Authors:
  • Yu, Qing
  • Li, Weifeng
  • Duan, Zhengyu
  • Yang, Dongyuan
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; References; Tables;
• Pagination: 7p

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Case studies; Communities; Commuters; Commuting; Mobile telephones; Origin and destination; Rapid transit; Traffic data; Travel patterns; Urban transit
• Geographic Terms: Shanghai (China)
• Subject Areas: Data and Information Technology; Passenger Transportation; Planning and Forecasting; Safety and Human Factors;

Filing Info

• Accession Number: 01657459
• Record Type: Publication
• Report/Paper Numbers: 18-00784
• Files: TRIS, TRB, ATRI
• Created Date: Jan 24 2018 9:24AM