Can Ridesharing Help the Disadvantaged Get Moving?

In many cities and towns throughout the United States, citizens with lower levels of education and skill confront challenges when seeking employment. The jobs best suited for their skills may be located in a different part of the metro area from their homes, and the existing public transportation system may not provide them with a practical way of interviewing for these jobs or commuting to them on a long-term basis. The rapid rise of ride sharing services, like Uber and Lyft, may provide a new opportunity to address these longstanding needs in a more cost-effective way. The public and private sectors may be able to share the costs of making the excess capacity in these ridesharing systems available to disadvantaged citizens whose needs are not being served by the existing public transportation system. Such a creative partnership could connect the least advantaged citizens to new opportunities while also connecting employers and businesses to human resources in an increasingly tight labor market. To examine the effectiveness of this new technology in expanding the mobility of citizens with special transportation needs, the research team plans to combine a large-scale field experiment with sophisticated data analysis to evaluate the impact of ridesharing on individual mobility, employment outcomes, and access to training and social services. The team intends to conduct such an experiment by combining the resources requested from Mobility 21 with existing funding already obtained from the Hillman Foundation and Metro 21. The team plans to recruit a large number (approximately 500-600) of low-income women with children residing in the Pittsburgh area who have limited access to a car; the team will randomly select these participants into two treatment groups that each receive access to free ridesharing for varying lengths of time and a control group that does not. The GPS features built into modern cellular phones allow the mobility of ridesharing fund recipients to be tracked with great accuracy across time and geographic space. These patterns could be analyzed and compared carefully to the mobility patterns of similar individuals who did not receive access to free ridesharing services. Surveys and pickup and dropoff data from a partner ridesharing company provide additional insight into the impact of this transportation resource on participants, allowing the team to measure the impact of access to ridesharing on interviews, job offers, and wages. The interdisciplinary research team provides a unique blend of faculty expertise that will allow the team to run a state-of-the-art experiment and conduct follow-up mobility trajectory data analysis, building on the most recent advances in information technology, statistics and machine learning, transportation engineering, and behavioral economics. The Pittsburgh region offers an ideal context in which to undertake this experiment, because there are flows of workers from city neighborhoods to jobs on the periphery of the metro area, and there are also smaller communities located far from the urban core that send workers into the city. Like other American cities, Pittsburgh has seen some rejuvenation in its urban center, but a decline in the fortunes of many of the surrounding communities that are linked to it, and there are few existing public transportation links connecting some of these disadvantaged communities to the rest of the region. Thus, an experiment in the Pittsburgh region could have broad implications for the rest of the country and even for metro areas outside the United States.

Language

  • English

Project

  • Status: Active
  • Funding: $90000
  • Contract Numbers:

    69A3551747111

  • Sponsor Organizations:

    Carnegie Mellon University

    Mobility 21 National UTDOT for Mobility of Goods and People
    ,    

    Office of the Assistant Secretary for Research and Technology

    University Transportation Program
    ,    
  • Managing Organizations:

    Carnegie Mellon Univeristy

    Mobility 21 National UTDOT for Mobility of Goods and People
    ,    
  • Project Managers:

    Schweyer, Lisa Kay

  • Performing Organizations:

    Carnegie Mellon University

    ,    
  • Principal Investigators:

    Branstetter, Lee

  • Start Date: 20170807
  • Expected Completion Date: 20190630
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01677497
  • Record Type: Research project
  • Source Agency: Technologies for Safe and Efficient Transportation University Transportation Center
  • Contract Numbers: 69A3551747111
  • Files: UTC, RiP
  • Created Date: Aug 7 2018 12:04PM