Parking spaces in the age of shared autonomous vehicles: how much parking will we need and where?
Abstract
The world is on the cusp of a new era in mobility given that the enabling technologies for autonomous vehicles (AVs) are almost ready for deployment and testing. Although the technological frontiers for deploying AVs are being crossed, transportation planners and engineers know far less about the potential impact of such technologies on urban form and land use patterns. This paper attempts to address those issues by simulating the operation of shared AVs (SAVs) in the city of Atlanta, Georgia, by using the real transportation network with calibrated link-level travel speeds and a travel demand origin–destination matrix. The model results suggest that the SAV system can reduce parking land by 4.5% in Atlanta at a 5% market penetration level. In charged-parking scenarios, parking demand will move from downtown to adjacent low-income neighborhoods. The results also reveal that policy makers may consider combining charged-parking policies with additional regulations to curb excessive vehicle miles traveled and alleviate potential social equity problems.
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A reduction of 4.5% is suggested for a penetration of 5%, with each SAV freeing more than 20 parking spots.
“Zhang & Guhathakurta (2017) suggest a reduction of 4.5% for a penetration of 5%, mentioning that each SAV can free more than 20 parking spots.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Zhang & Guhathakurta, 2017
Zhang & Guhathakurta (2018) integrates a residential location choice model with the SAV simulation model of Zhang & Guhathakurta (2017).
“In this study, a residential location choice model (developed using 2011 Atlanta Travel Survey & Zillow home sales data) is integrated with the SAV simulation model of Zhang & Guhathakurta (2017).”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Zhang & Guhathakurta (2017)
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- Authors
- Zhang, W., & Guhathakurta, S.
- Affiliations
- Georgia Institute of Technology (US)
- Corresponding author
- Guhathakurta, Subhrajit
- Venue
- Transportation Research Record: Journal of the Transportation Research Board
- Publisher
- SAGE Publications
- Published
- 2017-01
- Volume
- 2651
- Issue
- 1
- Pages
- 80-91
- ISSN
- 0361-1981 (ISSN-L)
- 2169-4052
- OpenAlex
- W2767127672
- Cited by
- 180
- References
- 10
- Citations by year
- 2026: 13 · 2025: 17 · 2024: 21 · 2023: 27 · 2022: 30 · 2021: 26 · 2020: 26 · 2019: 9 · 2018: 9 · 2017: 2
- FWCI
- 7.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Transportation Research Record Journal of the Transportation Research Board (publishedVersion)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
- Physical Sciences › Engineering › Building and Construction › Smart Parking Systems Research
- Social Sciences › Transportation › Transportation Planning and Optimization
- Keywords
- shared autonomous vehicles, parking demand, urban form, travel demand simulation, market penetration, vehicle miles traveled, social equity, land use change, Atlanta
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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