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Title: Analyzing the Effect of Autonomous Ridehailing on Transit Ridership: Competitor or Desirable First-/Last-Mile Connection?
Accession Number: 01763746
Record Type: Component
Record URL: Availability: Find a library where document is available Abstract: Ridehailing services (e.g., Uber or Lyft) may serve as a substitute or a complement—or some combination thereof—to transit. Automation as an emerging technology is expected to further complicate the current complex relationship between transit and ridehailing. This paper aims to explore how US commuters’ stated willingness to ride transit is influenced by the price of ridehailing services and whether the service is provided by an autonomous vehicle. To that end, a stated preference survey was launched around the US to ask 1,500 commuters how they would choose their commute mode from among choices including their current mode and other conventional modes as well as asking them to choose between their current mode and an autonomous mode. Using a joint stated and revealed preference dataset, a mixed logit model was developed and analyzed. The results show that ridehailing per se might not be a significant competitor to transit, especially if it is integrated with transit as a first-/last-mile service. The total share of transit (transit-only riders plus those who use transit in connection with first-/last-mile ridehailing) remains substantially flat as set against conventional ridehailing services, even if ridehailing fares decrease. On the other hand, when the ridehailing price is significantly reduced by automation, our analysis suggests a decline in total transit ridership and an increase in ridehailing, especially for solo ridehailing. Also, it was found that autonomous pooled ridehailing might not be as appealing to commuters as autonomous solo ridehailing.
Supplemental Notes: Andisheh Ranjbari https://orcid.org/0000-0003-2108-7953
© National Academy of Sciences: Transportation Research Board 2021.
Report/Paper Numbers: TRBAM-21-04383
Language: English
Authors: Khaloei, MoeinRanjbari, AndishehLaberteaux, KenMacKenzie, DonPagination: pp 1154-1167
Publication Date: 2021-11
Serial:
Transportation Research Record: Journal of the Transportation Research Board
Volume: 2675 Media Type: Digital/other
Features: Figures; References
(43)
; Tables
TRT Terms: Subject Areas: Operations and Traffic Management; Planning and Forecasting; Public Transportation; Vehicles and Equipment
Files: TRIS, TRB, ATRI
Created Date: Dec 23 2020 11:10AM
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