Imputing Socio-Demographics for Mobile Trajectors

Ubiquitous mobile devices have resulted in massive amount of location- and time-stamped traces that can be used to infer people’s mobility patterns for various applications. Unlike household travel survey data that is small but rich (short but wide data), mobile data, is often massive but shallow (long but thin data) whose meanings in terms of people’s travel patterns must be inferred. Not only being massive, it is also longitudinal, or to be precise: the data is continuous. These two key features hold great promises for a wide range of applications that cannot achieved with the traditional household travel survey data. Examples include: just in time or real time policy evaluations, a closed-loop from real time demand forecasting to service provision and then back to demand monitoring, and creation of digital twins for whole-city simulations. This study addresses a critical challenge that needs to be overcome in order to realize the great promises that the big, passively-generated mobile data offers. That is: to impute socio-demographics from the census data with the mobile trajectories generated from the big data. The novelty of the proposed project lies in that the proposed model will explicitly recognize the uncertainty that exists in the linkage between socio-demographics and travel behaviors.

• Record URL:
  • https://tbd.ctr.utexas.edu/research-product/imputing-socio-demographics-for-mobile-trajectors/

Language

• English

Project

• Status: Active
• Funding: $332,045.00
• Contract Numbers:

  69A3552344815

  69A3552348320

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Understanding Future of Travel Behavior and Demand

  University of Texas
  Austin, TX  United States 
• Project Managers:

  Bhat, Chandra

• Performing Organizations:

  University of Washington, Seattle

  Civil and Environmental Engineering Department
  201 More Hall, Box 352700
  Seattle, WA  United States  98195-2700
• Principal Investigators:

  Chen, Cynthia

• Start Date: 20240601
• Expected Completion Date: 20260531
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Data collection; Demographics; Mobile applications; Travel behavior
• Subject Areas: Data and Information Technology; Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 01954943
• Record Type: Research project
• Source Agency: Center for Understanding Future of Travel Behavior and Demand
• Contract Numbers: 69A3552344815, 69A3552348320
• Files: UTC, RIP
• Created Date: May 13 2025 7:27PM