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Autonomous Vehicle Fleet Sizes Required to Serve Different Levels of Demand
Open accessAbstract
Automated vehicles (AVs) promise many benefits for future mobility. One of them is a reduction of the required total vehicle fleet size, especially if AVs are used predominantly as shared vehicles. This paper presents research on this potential reduction for the greater Zurich, Switzerland, region. Fleets of shared AVs serving a predefined demand were simulated with a simulation framework introduced in the paper. Scenarios combining levels of demand for AVs with levels of supply (i.e., AV fleet sizes) were created. An important contribution of this study is the use of travel demand at highly detailed spatial and temporal resolutions that goes beyond the simplifications used in previous studies on the topic. This detailed travel demand provides a more solid basis for the ongoing discussion about the future fleet size. It was found that for a given fleet performance target (here, the target was for 95% of all transport requests to be served within 5 min), the relationship between served demand and required fleet size was nonlinear and the ratio increased as demand increased. A scale effect was detected. This effect has the important implication that for different levels of demand the fleet is used more or less efficiently. This study also found that if waiting times of up to 10 min were accepted, a reduction of up to 90% of the total vehicle fleet could be possible even without active fleet management, like vehicle redistribution. Such effects require, however, that a large eno…
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“The modelling method from Bösch et al. (2016) is used for simulation of SAV operations.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Bösch et al. (2016)
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Metadata
- Authors
- Boesch, P. M., Ciari, F., & Axhausen, K. W.
- Affiliations
- Institut für Verkehrsplanung und Transportsysteme, Eidgenössische Technische Hochschule Zürich, CH-8093 Zurich, Switzerland
- ETH Zurich (CH)
- Venue
- Transportation Research Record: Journal of the Transportation Research Board
- Publisher
- SAGE Publications
- Published
- 2016-01
- Volume
- 2542
- Issue
- 1
- Pages
- 111-119
- ISSN
- 0361-1981 (ISSN-L)
- 2169-4052
- OpenAlex
- W2405705374
- Cited by
- 253
- References
- 12
- Citations by year
- 2026: 7 · 2025: 13 · 2024: 17 · 2023: 30 · 2022: 29 · 2021: 45 · 2020: 39 · 2019: 34 · 2018: 26 · 2017: 11 · 2016: 2
- FWCI
- 21.20
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- Transportation Research Record Journal of the Transportation Research Board (publishedVersion)
- Repository for Publications and Research Data (ETH Zurich) (acceptedVersion, other-oa)
- PolyPublie (École Polytechnique de Montréal) (submittedVersion)
- ETH Zürich Research Collection
- Topics
- Social Sciences › Transportation › Transportation and Mobility Innovations
- Social Sciences › Transportation › Transportation Planning and Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Keywords
- autonomous vehicles, shared mobility, vehicle fleet size, fleet size reduction, demand level, scale effects, fleet management, travel demand, Zürich region
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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