Cited by 616Transportation and Mobility InnovationsTransportation Planning and OptimizationTraffic control and management

Dynamic ride-sharing and fleet sizing for a system of shared autonomous vehicles in Austin, Texas

Fagnant, Daniel J., Kockelman, Kara M.·2018·Transportation

Integrity signals

Registry

Crossref · 10.1007/s11116-016-9729-z

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Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Fagnant & Kockelman (2018) builds on Fagnant & Kockelman (2014) by including a Dynamic Ride-Sharing (DRS) module.

    “This study builds on Fagnant & Kockelman (2014), by including a Dynamic Ride-Sharing (DRS) module.”

    From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Fagnant & Kockelman (2018)

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Authors
Fagnant, D. J., & Kockelman, K. M.
Affiliations
The University of Texas at Austin (US)
Corresponding author
Kockelman, Kara M.
Venue
Transportation
Published
2016-08-22
Volume
45
Issue
1
Pages
143-158
ISSN
  • 0049-4488 (ISSN-L)
  • 1572-9435
OpenAlex
W2515943586
Cited by
616
References
0
Citations by year
2026: 39 · 2025: 42 · 2024: 65 · 2023: 53 · 2022: 66 · 2021: 112 · 2020: 107 · 2019: 79 · 2018: 36 · 2017: 13 · 2016: 3 · 2015: 1
FWCI
38.05
Type
journal article
Language
en
Open access
closed
Locations
  • Transportation (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
  • Social Sciences › Transportation › Transportation Planning and Optimization
  • Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
Keywords
shared autonomous vehicles, dynamic ridesharing, fleet sizing, vehicle miles traveled, travel cost, service time, operator profitability, return on investment, urban transport, congestion, Austin, Texas

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.

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