Characteristics of Pooled Trips Offered by Ride-sourcing Services in Chicago

In this project, the research team will analyze data from a new database from the City of Chicago on ridesourcing services to understand the spatial and temporal patterns of Uber and Lyft usage across the region. The work will be innovative because the database is the most comprehensive publicly-available information that has ever been published on ridesourcing services by any municipality in the United States. The research team's analysis will focus on the trip database which includes detailed pricing information, trip length, Census Tract of trip origin and destination, date and time of trip, whether the trip was requested to be “split” with other users, and whether the request to split was fulfilled. The research team will build on the similar research undertaken in NYC, noting that they will be able to expand that analysis because the Chicago data are far more extensive. Having pricing data for regular as well as “split” trips that are taken with other users will help the research team to answer a broader range of questions pertaining to the way that these services are being incorporated into existing transportation system. The team's research project is motivated by the overarching research question (RQ): “How do ridesourcing services change the landscape of accessibility, for whom, and at what cost?” The research team will operationalize this with three smaller RQs: RQ1) What are the spatial and temporal patterns of ridesourcing usage in Chicago for both pooled and non-pooled rides? RQ2) How does ridesourcing usage vary according to neighborhood characteristics (comprised of a vector of three factors (a) socio-economic and demographic variables; (b) population and employment density; and (c) and availability of other modes of transportation including vehicle ownership and public transit)? RQ3) How does spending on ridesourcing in Chicago compare to spending on other modes of transportation, in absolute terms, and as a percentage of household income? The findings from these three research questions will be synthesized to generate data about per capita spending across the study area on transportation, and identify areas suffering from transportation inequity, defined as spending a high proportion of their income on transportation. This will provide a jumping off point for a subsequent study involving identifying ways to alleviate this inequity.

Language

• English

Project

• Status: Completed
• Funding: $90007
• Contract Numbers:

  69A3551747133

• Sponsor Organizations:

  Center for Advanced Multimodal Mobility Solutions and Education

  University of North Carolina, Charlotte
  Charlotte, NC  United States  28223

  Office of the Assistant Secretary for Research and Technology

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

  University of North Carolina, Charlotte

  Department of Civil and Environmental Engineering
  9201 University City Boulevard
  Charlotte, NC  United States  28223-0001
• Project Managers:

  Fan, Wei

• Performing Organizations:

  University of Connecticut, Storrs

  Storrs, CT  United States  06268-5202
• Principal Investigators:

  Garrick, Norman

  Atkinson-Palombo, Carol

• Start Date: 20201001
• Expected Completion Date: 20220930
• Actual Completion Date: 20220930

Subject/Index Terms

• TRT Terms: Databases; Equity; Mobility; Ridesourcing; Spatial analysis; Travel
• Identifier Terms: Lyft; Transportation Equity Act for the 21st Century; Uber
• Geographic Terms: Chicago (Illinois)
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; Society;

Filing Info

• Accession Number: 01754809
• Record Type: Research project
• Source Agency: Center for Advanced Multimodal Mobility Solutions and Education
• Contract Numbers: 69A3551747133
• Files: UTC, RIP
• Created Date: Oct 17 2020 2:07PM