| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | August 22, 2016 |
| Latest Amendment Date: | April 18, 2017 |
| Award Number: | 1647517 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Cynthia Chen
CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | September 1, 2016 |
| End Date: | August 31, 2017 (Estimated) |
| Total Intended Award Amount: | $24,999.00 |
| Total Awarded Amount to Date: | $24,999.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1109 GEDDES AVE STE 3300 ANN ARBOR MI US 48109-1015 (734)763-6438 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
MI US 48109-2150 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CIS-Civil Infrastructure Syst |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
The recent indefinite suspension of crowdsource-based ridesharing services in Austin, Texas provides a unique and time-limited opportunity to observe the impact of these services on the public?s travel behavior. This project investigate how the disruption of ride sourcing services impacts residents? travel demand. It will document and analyze the adaptations that ride-sharing passengers make in response to the suspension of these services. Of particular attention are trips that utilize multiple travel modes, especially where these services provide the so-called first- and last-mile links to the public transit systems. The data and analyses produced through this work will thereby contribute information that could inform policy makers in other cities in which crowdsource-based transportation services are or may become active. Research findings are expected to benefit society by providing invaluable insights on on-demand mobility as it relates to both transportation and environmental policies.
Using surveys administered online to users of these services, an assessment of the disruption on key measures of travel behavior will be made, including the number of trips, types of activities, travel mode choice, trip purpose and trip distribution. The survey, to be administered over a 6-8 week period, will utilize a systematic sampling methodology, allowing for broad participation among the population of former users. Efforts will be made to increase the response rate by utilizing social media to reach former users. Deliverables associated with the research include methodological tools and a unique dataset that will supporting modeling the resilience of multi-modal transportation systems.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
On May 7, 2016, Austin residents voted 56 percent to 44 percent against Proposition 1, whichwould have allowed ride-sourcing companies to continue using their own background check systems for drivers rather than utilizing the system mandated by the City of Austin. In responseto this public decision, Uber and Lyft suspended services in Austin indefinitely. This suspension has had a direct impact on passengers, who have faced a reduced menu of mobility options.Shortly after the May 7, 2016, vote, several informal community efforts sprang up to offer ridesourcing services. As many as 12 app-based service providers were launched to fill the void leftby Uber and Lyft in Austin. While many of these platforms have subsequently closed shop,several are still in business.
Regression analyses, modeled to capture both the before and after travel behavioralpattern of the suspension, were used to test our hypothesis of the impact of the service suspension on travel behavior along three dimensions—mode choice, trip frequency, and vehicle ownership. Our analysis finds that 42 percent of respondents who had used Uber orLyft to make a trip prior to the suspension reported transitioning to another TNC as themeans by which similar trips were most often made after the suspension. A near equal proportion (41 percent) reported transitioning to a personal vehicle, while 3 percenttransitioned to public transit. The analysis also suggests that, when looking at tripsmade for the same purpose pre and post suspension, individuals that transitioned fromUber or Lyft to a personal vehicle were more likely (23 percent more likely) to make more trips than individuals transitioning from Uber or Lyft to another TNC. Additionally,approximately 9 percent reported purchasing an additional vehicle in response to the service suspension. The vehicle acquisition trend was driven primarily by respondentswho were inconvenienced by the service suspension—the odds of acquiring a car foran inconvenienced respondent was more than five times that of an individual who was not.
These results suggest that TNCs may contribute to reduced car ownership and tripmaking.This study was one of the first (if not the first) to utilize a natural experiment to assess the impact of an unanticiapted service disruption in ride sharing services on regional travel behavior. The results of this study provide data-based information which can be used by policy makers to help them go about establishing a TNC regulatory framework.
Last Modified: 10/02/2017
Modified by: Robert C Hampshire
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