Cited by 224Transportation and Mobility InnovationsElectric Vehicles and InfrastructureTransportation Planning and Optimization

Shared autonomous electric vehicle (SAEV) operations across the Austin, Texas network with charging infrastructure decisions

Loeb, Benjamin, Kockelman, Kara M., Liu, Jun·2018·Transportation Research Part C: Emerging Technologies

Integrity signals

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Crossref · 10.1016/j.trc.2018.01.019

Cites

3 of 3 references verified0 citation errors · 0 not checkable

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  • Suburban areas will be under-served and the quality of service will be better in urban areas.

    “Loeb et al. (2018), Lokhandwala & Cai (2018) and Zhang & Guhathakurta (2018) conclude that suburban areas will be under-served and the quality of service will be better in urban areas.”

    From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Loeb et al., 2018

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Authors
Loeb, B., Kockelman, K. M., & Liu, J.
Affiliations
  • The University of Texas at Austin (US)
  • Virginia Department of Transportation (US)
Corresponding author
Kockelman, Kara M.
Venue
Transportation Research Part C: Emerging Technologies
Publisher
Elsevier BV
Published
2018-04
Volume
89
Pages
222-233
ISSN
0968-090X (ISSN-L)
OpenAlex
W2789764619
Cited by
224
References
3
Citations by year
2026: 17 · 2025: 17 · 2024: 20 · 2023: 26 · 2022: 26 · 2021: 38 · 2020: 38 · 2019: 31 · 2018: 9 · 2017: 1 · 2016: 1
FWCI
15.40
Type
journal article
Language
en
Open access
closed
Locations
Transportation Research Part C Emerging Technologies (publishedVersion)
Funders
Texas Department of Transportation
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
  • Social Sciences › Transportation › Transportation Planning and Optimization
Keywords
shared autonomous electric vehicles, driving range, charging time, fleet size, response time, Austin, Texas

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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.

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