Understanding the Heterogeneity of Human Mobility Patterns: User Characteristics and Modal Preferences

Characterizing individual mobility is critical to understand urban dynamics and develop high-resolution mobility models. Previously, large-scale trajectory datasets have been used to characterize universal human mobility patterns. However, due to the limit of the underlying datasets, these studies could not investigate how mobility patterns change over user characteristics. In this paper, the authors analyze a large-scale Automatic Fare Collection (AFC) dataset of the main transit system of Seoul, South Korea and investigate how mobility patterns change over user characteristics and modal preferences. The authors identify users' commuting locations and estimate the statistical distributions required to characterize their spatio-temporal mobility patterns. The findings show the heterogeneity of mobility patterns across demographic user groups. This result will significantly impact future mobility models based on trajectory datasets.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABJ30 Standing Committee on Urban Transportation Data and Information Systems.
• Authors:
  • Wu, Laiyun
  • Hasan, Samiul
  • Kang, Jee Eun
  • Chung, Younshik
• 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; References; Tables;
• Pagination: 9p

Subject/Index Terms

• TRT Terms: Commuting; Demographics; Distributions (Statistics); Fares; Location; Mobility; Mode choice; Travel patterns
• Geographic Terms: Seoul (Korea)
• Subject Areas: Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01658658
• Record Type: Publication
• Report/Paper Numbers: 18-03832
• Files: TRIS, TRB, ATRI
• Created Date: Jan 31 2018 4:58PM