Cited by 74Transportation and Mobility InnovationsTraffic Prediction and Management TechniquesTransportation Planning and Optimization

Evaluating the impact of spatio-temporal demand forecast aggregation on the operational performance of shared autonomous mobility fleets

Open access
Dandl, Florian, Hyland, Michael, Bogenberger, Klaus, Mahmassani, Hani S.·2019·Transportation

Integrity signals

Registry

Crossref · 10.1007/s11116-019-10007-9

Cites

36 of 36 references verified0 citation errors · 0 not checkable

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  • Higher spatial disaggregation of demand forecast leads to better fleet performance in terms of user wait time and empty fleet miles, though demand forecast quality is decreased at higher disaggregation.

    “They conclude that higher the spatial disaggregation of demand forecast, better is the fleet performance in terms of user wait time and empty fleet miles, though the demand forecast quality is decreased at higher disaggregation.”

    From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Dandl et al. (2019)

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Authors
Dandl, F., Hyland, M., Bogenberger, K., & Mahmassani, H. S.
Affiliations
  • Universität der Bundeswehr München (DE)
  • University of California, Irvine (US)
  • Northwestern University (US)
Corresponding author
Mahmassani, Hani S.
Venue
Transportation
Published
2019-05-04
Volume
46
Issue
6
Pages
1975-1996
ISSN
  • 0049-4488 (ISSN-L)
  • 1572-9435
OpenAlex
W2944404766
Cited by
74
References
36
Citations by year
2026: 12 · 2025: 1 · 2024: 7 · 2023: 15 · 2022: 9 · 2021: 12 · 2020: 16 · 2019: 2
FWCI
4.45
Type
journal article
Language
en
Open access
Locations
  • Transportation (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion, other-oa)
Funders
  • Bundesministerium für Umwelt, Naturschutz, Bau und Reaktorsicherheit
  • U.S. Department of Transportation
  • Northwestern University Transportation Center
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
  • Physical Sciences › Engineering › Building and Construction › Traffic Prediction and Management Techniques
  • Social Sciences › Transportation › Transportation Planning and Optimization
Keywords
shared autonomous vehicles, agent-based modeling, taxi data, on-demand mobility services

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