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作者

Anne Brown

来源

JOURNAL OF THE AMERICAN PLANNING ASSOCIATION,Vol.85,Issue2,P.83-95

语言

英文

关键字

car access,equity,ride-hail,ridesource,transportation network company

作者单位

摘要

AbstractProblem, research strategy, and findings: Ride-hail services such as Uber and Lyft have the potential to redefine car access and travel, but unclear associations with the built environment and resident characteristics have undermined planners’ abilities to make informed decisions. I use detailed data of 6.3 million Lyft trips in Los Angeles (CA) to examine the associations between Lyft travel, the built environment, and neighborhood socioeconomic characteristics. Although data are limited to one American city, findings present a comprehensive understanding of Lyft use across an array of built environments. I find that, far from being limited to dense urban cores, Lyft provides automobility in suburban and even rural neighborhoods. Findings suggest that unlike taxis, ride-hailing does not exclude low-income neighborhoods and communities. Instead, Lyft provides car access in neighborhoods where its closest substitute, the household car, is scarcest. Most travelers use ride-hailing to fill an occasional rather than regular travel need, but a small share of users made the most ride-hail trips. Travelers without smartphones or bank accounts, however, may be excluded from ride-hailing.Takeaway for practice: Widespread Lyft use demonstrates that planners should anticipate ride-hailing not just in urban centers but across a wide array of built environments. Negative associations between Lyft travel and off-street parking suggest that ride-hailing can provide new modal options where parking is already constrained or where new parking restrictions are introduced. Planners should work with communities and transit agencies to adopt strategies or enter partnerships that extend ride-hail, or other technology-enabled mobility services, to travelers without smartphones or bank accounts.Keywords: car access, equity, ride-hail, ridesource, transportation network companyAdditional informationAuthor informationAnne BrownANNE BROWN (abrown33@uoregon.edu) is an assistant professor in the School of Planning, Public Policy, and Management at the University of Oregon.Research SupportThis research was supported by UCLA Institute of Transportation Services and UCLA Graduate Division.Supplemental MaterialSupplemental data for this article can be found on the publisher’s website.Notes1 Low-density neighborhoods are those in the bottom quartile of neighborhood activity density (residents plus workers) in Los Angeles County. High-density neighborhoods are those in the top activity density quartile.