Shared autonomous vehicle simulation and service design
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4-seater SAVs are more suitable than 2- and 6-seater SAVs for the Rouen Normandie metropolitan area in France.
“Vosooghi et al. (2019) concludes that 4-seater SAVs are more suitable than 2-and 6-seater SAVs for Rouen Normandie metropolitan area in France.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Vosooghi et al., 2019
The Vehicle capacity section (pp. 12–13) says a four-seat car may be the best-performing ridesharing option and seems more compatible with the proposed service than a six-seat minivan. The Discussion and conclusion (p. 18) identifies the 3,000-vehicle shared-ride scenario as the best considered. The citing sentence presents that tentative, scenario-specific finding as an unqualified conclusion that four-seat SAVs are more suitable than both alternatives. (LLM, conf=0.86)
Experimental — accuracy not yet measuredA 20% price difference between car-sharing SAV system ($0.56/km) and ride-sharing SAV system ($0.44/km) can persuade travellers to shift from individual rides to shared rides, leading to improvements in performance indicators; larger differences do not cause proportionate improvements.
“The results from Vosooghi et al. (2019) show that a 20% 510 difference in price between car-sharing SAV system ($0.56/km) and ride-sharing SAV system ($0.44/km)can persuade travellers to shift from individual rides to shared rides, leading to improvements in the performance indicators.However, larger differences do not cause proportionate improvements in performance indicators.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Vosooghi et al., 2019
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Experimental — accuracy not yet measuredThe SAV service is able to reduce at most 1.7% of cars in the network.
“Vosooghi et al. (2019) conclude that the SAV service is able to reduce at most 1.7% cars in the network.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Vosooghi et al., 2019
Section 4.1 (p. 7) reports that some travelers shift from cars to SAVs, and Table 2 shows lower car mode shares in the simulated SAV scenarios. It does not establish that the number of cars in the network falls by at most 1.7%; the reported measure is mode share, not a car count. (LLM, conf=0.83)
Experimental — accuracy not yet measuredUsage of more realistic models shows comparatively lower benefits from SAV services.
“As concluded by Levin et al. (2017) and Vosooghi et al. (2019), usage of more realistic models shows comparatively lower benefits from SAV services.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Vosooghi et al. (2019)
Prior research (p. 4) describes this study as a comprehensive simulation of a real-world SAV scenario, and the Discussion and conclusion (p. 17) says its dynamic-demand results differ from simulations with predefined or static demand. But the paper does not conclude that more realistic models generally show lower SAV-service benefits than less realistic models; the reported difference concerns a specific waiting-time result. (LLM, conf=0.78)
Experimental — accuracy not yet measuredVehicle redistribution has a significant effect on service performance, such as modal share and fleet usage, but empty VMT/VKT increases significantly.
“Vosooghi et al. (2019) conclude that redistributing vehicles has a significant effect on service performance, such as modal share and fleet usage.However, empty VMT/VKT increases significantly.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Vosooghi et al. (2019)
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Cites
Zhang, W., Guhathakurta, S., Fang, J., & Zhang, G. (2015) · Sustainable Cities and Society · doi:10.1016/j.scs.2015.07.006 · Cited by 422 · see citing works
Autonomous vehicle fleet sizes required to serve different levels of demand
Boesch, P. M., Ciari, F., & Axhausen, K. W. (2016) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.3141/2542-13 · Cited by 253 · see citing works
Heilig, M., Hilgert, T., Mallig, N., Kagerbauer, M., & Vortisch, P. (2017) · Transportation Research Procedia · doi:10.1016/j.trpro.2017.07.004 · Cited by 79 · see citing works
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Research works printed but not linked: 9
- Agatz, N.A.H., Erera, A.L., Savelsbergh, M.W.P., Wang, X., 2011. Dynamic ride-sharing: A simulation study in metro Atlanta. Transp. Res. Part B Methodol. 45, 1450-1464. https://doi.org/10.1016/J.TRB.2011.05.017 · DOI
- Alonso-Mora, J., Samaranayake, S., Wallar, A., Frazzoli, E., Rus, D., 2017. On-demand high-capacity ride-sharing via dynamic tripvehicle assignment. Proc. Natl. Acad. Sci. 114, 462-467. https://doi.org/10.1073/pnas.1611675114 · DOI
- Auld, J., Sokolov, V., Stephens, T.S., 2017. Analysis of the Effects of Connected-Automated Vehicle Technologies on Travel Demand. Transp. Res. Rec. J. Transp. Res. Board 2625, 1-8. https://doi.org/10.3141/2625-01 · DOI
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- Vosooghi, R., Kamel, J., Puchinger, J., Leblond, V., Jankovic, M., 2019. Robo-Taxi service fleet sizing: assessing the impact of user trust and willingness-to-use. Transportation (Amst). https://doi.org/10.1007/s11116-019-10013-x · DOI
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Cited by
Sorted by citations
Shared autonomous vehicle services: A comprehensive review
Narayanan, S., Chaniotakis, E., & Antoniou, C. (2020) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2019.12.008 · Cited by 691 · see citing works
Gueriau, M., Cugurullo, F., Acheampong, R. A., & Dusparic, I. (2020) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2020.3014417 · Cited by 15 · see citing works
- Authors
- Vosooghi, R., Puchinger, J., Jankovic, M., & Vouillon, A.
- Affiliations
- Université Paris-Saclay (FR)
- Renault (France) (FR)
- Corresponding author
- Vosooghi, Reza
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 2019-10
- Volume
- 107
- Pages
- 15-33
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W2949407720
- Cited by
- 155
- References
- 3
- Citations by year
- 2026: 15 · 2025: 18 · 2024: 16 · 2023: 29 · 2022: 20 · 2021: 33 · 2020: 22 · 2019: 2
- FWCI
- 8.78
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Transportation Research Part C Emerging Technologies (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- HAL (submittedVersion, other-oa)
- arXiv (Cornell University)
- Funders
- Investissements d’Avenir
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
- Social Sciences › Transportation › Transportation Planning and Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Keywords
- shared autonomous vehicles, autonomous vehicles, ride-sharing, fleet size, vehicle rebalancing, dynamic demand, multimodal transport, vehicle capacity, pricing schemes, driving range, charging station deployment, urban mobility services
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