Operations of Shared Autonomous Vehicle Fleet for Austin, Texas, Market
Abstract
The emergence of automated vehicles holds great promise for the future of transportation. Although commercial sales of fully self-driving vehicles will not commence for several more years, once these sales are possible a new transportation mode for personal travel promises to arrive. This new mode is the shared autonomous (or fully automated) vehicle (SAV), combining features of short-term, on-demand rentals with self-driving capabilities: in essence, a driverless taxi. This investigation examined the potential implications of the SAV at a low level of market penetration (1.3% of regional trips) by simulating a feet of SAVs serving travelers in the 12-mi by 24-mi regional core of Austin, Texas. The simulation used a sample of trips from the region's planning model to generate demand across traffic analysis zones and a 32,272-link network. Trips called on the vehicles in 5-min departure time windows, with link-level travel times varying by hour of day based on MATSIM's dynamic traffic assignment simulation software. Results showed that each SAV could replace about nine conventional vehicles within the 24-mi by 12-mi area while still maintaining a reasonable level of service (as proxied by user wait times, which averaged just 1 min). Additionally, approximately 8% more vehicle miles traveled (VMT) may be generated because of SAV's ability to journey unoccupied to the next traveler or relocate to a more favorable position in anticipation of its next period demand.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Cited by
Sorted by citations
Cost-based analysis of autonomous mobility services
Bösch, P. M., Becker, F., Becker, H., & Axhausen, K. W. (2018) · Transport Policy · doi:10.1016/j.tranpol.2017.09.005 · Cited by 585 · see citing works
Faisal, A., Yigitcanlar, T., Kamruzzaman, M., & Currie, G. (2019) · Journal of Transport and Land Use · doi:10.5198/jtlu.2019.1405 · Cited by 427 · see citing works
Shen, Y., Zhang, H., & Zhao, J. (2018) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2018.04.004 · Cited by 330 · see citing works
Cost, Energy, and Environmental Impact of Automated Electric Taxi Fleets in Manhattan
Bauer, G. S., Greenblatt, J. B., & Gerke, B. F. (2018) · Environmental Science & Technology · doi:10.1021/acs.est.7b04732 · Cited by 195 · see citing works
Unintended effects of autonomous driving: a study on mobility preferences in the future
Pakusch, C., Stevens, G., Boden, A., & Bossauer, P. (2018) · Sustainability · doi:10.3390/su10072404 · Cited by 182 · see citing works
Parking spaces in the age of shared autonomous vehicles: how much parking will we need and where?
Zhang, W., & Guhathakurta, S. (2017) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.3141/2651-09 · Cited by 180 · see citing works
Basu, R., Araldo, A., Akkinepally, A. P., Nahmias Biran, B. H., Basak, K., Seshadri, R., Deshmukh, N., Kumar, N., Azevedo, C. L., & Ben-Akiva, M. (2018) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.1177/0361198118758630 · Cited by 138 · see citing works
Flexible mobility on-demand: an environmental scan
Liyanage, S., Dia, H., Abduljabbar, R., & Bagloee, S. (2019) · Sustainability · doi:10.3390/su11051262 · Cited by 111 · see citing works
Residential Location Choice in the Era of Shared Autonomous Vehicles
Zhang, W., & Guhathakurta, S. (2021) · Journal of Planning Education and Research · doi:10.1177/0739456x18776062 · Cited by 107 · see citing works
Anticipating the regional impacts of connected and automated vehicle travel in Austin, Texas
Zhao, Y., & Kockelman, K. M. (2018) · Journal of Urban Planning and Development · doi:10.1061/(asce)up.1943-5444.0000463 · Cited by 95 · see citing works
Self-citationMapping Two Decades of Autonomous Vehicle Research: A Systematic Scientometric Analysis
Faisal, A., Yigitcanlar, T., Kamruzzaman, M., & Paz, A. (2021) · Journal of Urban Technology · doi:10.1080/10630732.2020.1780868 · Cited by 85 · see citing works
Dandl, F., Hyland, M., Bogenberger, K., & Mahmassani, H. S. (2019) · Transportation · doi:10.1007/s11116-019-10007-9 · Cited by 74 · see citing works
Mendes, L. M., Bennàssar, M. R., & Chow, J. Y. J. (2017) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.3141/2650-17 · Cited by 40 · see citing works
- Authors
- Fagnant, D. J., Kockelman, K. M., & Bansal, P.
- Affiliations
- University of Utah (US)
- The University of Texas at Austin (US)
- Corresponding author
- Kockelman, Kara M.
- Venue
- Transportation Research Record: Journal of the Transportation Research Board
- Publisher
- SAGE Publications
- Published
- 2016-01
- Volume
- 2563
- Issue
- 1
- Pages
- 98-106
- ISSN
- 0361-1981 (ISSN-L)
- 2169-4052
- OpenAlex
- W2160865385
- Cited by
- 314
- References
- 0
- Citations by year
- 2026: 8 · 2025: 23 · 2024: 11 · 2023: 37 · 2022: 30 · 2021: 50 · 2020: 44 · 2019: 39 · 2018: 34 · 2017: 28 · 2016: 10
- FWCI
- 24.76
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Transportation Research Record Journal of the Transportation Research Board (publishedVersion)
- 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, autonomous vehicles, vehicle miles traveled, vehicle replacement, on-demand ride-hailing, dynamic traffic assignment, MATSim, trip generation, travel demand simulation, vehicle relocation, 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.
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 ›
Are you an author, or do you see a problem with this page? Request a review
