The DOI matches its Crossref record; 29 of the 30 references it cites were found in a registry or an index, and 1 are not checked yet.
EVALUATING THE IMPACT OF AUTONOMOUS VEHICLES ON ACCESSIBILITY USING AGENT-BASED SIMULATION —A CASE STUDY OF GUNMA PREFECTURE
Open accessAbstract
The emergence of autonomous vehicles is expected to shape the urban transportation system in various ways. In this study, a large-scale agent-based disaggregate simulation model, MATSim, is employed to measure the impact of autonomous vehicles on accessibility changes. This study used disaggregate spatial data from the Gunma Prefecture Person Trip Survey as the initial travel demand input for the model. Two new autonomous transport modes, namely shared autonomous vehicle (SAV) and private autonomous vehicle (PAV), are included in the simulation, in addition to the existing human-driven private vehicles. A scenario analysis is conducted using fleet size of SAV, ownership of PAV, operation cost, value of time changes as the key variables in the scenario setting. Based on the final travel demand results, a Hansen-type accessibility analysis is conducted, providing quantitative evidence to measure the potential impact of autonomous vehicles on accessibility changes in Japanese regional cities. Results suggest a considerable market share of AVs in scenarios with positive assumptions, and an overall accessibility increase in the scenario where PAVs were introduced. Particularly, suburban areas seemed to enjoy more accessibility gains, which might result in further urban sprawl in the future.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Private AVs are by far the most important factor expected to increase accessibility in suburban and rural areas (e.g., [5,50,51]).”
From Implications of Autonomous Vehicles for Accessibility and Transport Equity: A Framework Based on Literature (2021) · cites this paper as [50]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Besides private AVs, the spread of shared AVs with low fares could increase accessibility in suburban and rural areas (e.g., [9,50,52]).”
From Implications of Autonomous Vehicles for Accessibility and Transport Equity: A Framework Based on Literature (2021) · cites this paper as [50]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
How Accessibility Shapes Land Use
Hansen, W. G. (1959) · Journal of the American Institute of Planners · doi:10.1080/01944365908978307 · Cited by 4,139
WHAT ABOUT PEOPLE IN REGIONAL SCIENCE?
Hägerstrand, T. (1970) · Papers of the Regional Science Association · doi:10.1111/j.1435-5597.1970.tb01464.x · Cited by 3,532
Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations
Fagnant, D. J., & Kockelman, K. (2015) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2015.04.003 · Cited by 3,214
Fagnant, D. J., & Kockelman, K. M. (2014) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2013.12.001 · Cited by 1,177
Assessing public opinions of and interest in new vehicle technologies: An Austin perspective
Bansal, P., Kockelman, K. M., & Singh, A. (2016) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2016.01.019 · Cited by 1,025
Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies
Bansal, P., & Kockelman, K. M. (2016) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2016.10.013 · Cited by 736
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
Autonomous vehicles: The next jump in accessibilities?
Meyer, J., Becker, H., Bösch, P. M., & Axhausen, K. W. (2017) · Research in Transportation Economics · doi:10.1016/j.retrec.2017.03.005 · Cited by 371
Using an Activity-Based Model to Explore the Potential Impacts of Automated Vehicles
Childress, S., Nichols, B., Charlton, B., & Coe, S. (2015) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.3141/2493-11 · Cited by 319
Operations of Shared Autonomous Vehicle Fleet for Austin, Texas, Market
Fagnant, D. J., Kockelman, K. M., & Bansal, P. (2016) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.3141/2536-12 · Cited by 314
Research works printed but not linked: 3
- 12) Gucwa, M. : Mobility and energy impact of automated cars, Proceedings of the Automated Vehicles Symposium, San Francisco, 2014.
- 19) Horni, A., Nagel, K. and Axhausen, K. W. (Eds.) : The Multi-Agent Transport Simulation MATSim, London: Ubiquity Press, 2016.
- 39) Ciari, F., Balmer, M. and Axhausen, K. W. : A new mode choice model for a multi-agent transport simulation, Arbeitsberichte Verkehrs-und Raumplanung, Vol. 529, 2008.
Cited by
Sorted by citations
Dianin, A., Ravazzoli, E., & Hauger, G. (2021) · Sustainability · doi:10.3390/su13084448 · Cited by 59
“Also in later works (as [50,51]), accessibility sprawl is often expected.”
BackgroundMethodInfluentialShared autonomous vehicles and agent based models: a review of methods and impacts
Karolemeas, C., Tsigdinos, S., Moschou, E., & Kepaptsoglou, K. L. (2024) · European Transport Research Review · doi:10.1186/s12544-024-00644-2 · Cited by 44
Maheshwari, T., & Axhausen, K. W. (2021) · Sustainability · doi:10.3390/su13063013 · Cited by 26
Sarri, P., Kaparias, I., Preston, J. M., & Simmonds, D. (2023) · Transport Policy · doi:10.1016/j.tranpol.2023.03.012 · Cited by 24
Modeling the effect of autonomous vehicles (AVs) on the accessibility of the transportation network
Mirzahossein, H., & Mashhadloo, M. (2024) · Scientific Reports · doi:10.1038/s41598-024-60069-8 · Cited by 24
Potential Travel Time Reduction with Autonomous Vehicles for Different Types of Travellers
Hamadneh, J., & Esztergár‐Kiss, D. (2021) · PROMET - Traffic&Transportation · doi:10.7307/ptt.v33i1.3585 · Cited by 24
Zakeri, S., Konstantas, D., Sorooshian, S., & Chatterjee, P. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10917-w · Cited by 22
Luo, L., Parady, G., & Takami, K. (2022) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2022.100717 · Cited by 15
Self-citationLuo, L., Portugal‐Pereira, J., Takami, K., & Parady, G. (2024) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2024.104298 · Cited by 15
Self-citationReconsidering AVs future: A socio-spatial perspective
Lee, J., & Gim, T. T. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102618 · Cited by 10
Dianin, A., Gidam, M., Ravazzoli, E., & Hauger, G. (2024) · International Journal of Transportation Science and Technology · doi:10.1016/j.ijtst.2024.11.004 · Cited by 6
Luo, L., Parady, G., & Takami, K. (2024) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2024.104281 · Cited by 6
Self-citationHamadneh, J., & Esztergár‐Kiss, D. (2022) · Transport · doi:10.3846/transport.2022.16322 · Cited by 6
Equilibrium analysis of trip demand for autonomous taxi services in Nagoya, Japan
Mori, K., Miwa, T., Abe, R., & Morikawa, T. (2022) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2022.10.009 · Cited by 5
Mohebbi, S., & Murali, P. S. (2022) · Winter Simulation Conference · doi:10.1109/wsc57314.2022.10015452 · Cited by 5
Individual accessibility impacts of public transport automation on (groups of) rural dwellers
Dianin, A., Gidam, M., Ravazzoli, E., Stawinoga, A. E., & Hauger, G. (2024) · Journal of Public Transportation · doi:10.1016/j.jpubtr.2024.100098 · Cited by 5
Kamijo, Y., Luo, L., Parady, G., & Takami, K. (2026) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2026.102244 · Cited by 2
Self-citationToshikatsu, M. O. R. I., Mizokami, S., Kanamori, R., & Liu, Q. (2022) · International Journal of Intelligent Transportation Systems Research · doi:10.1007/s13177-022-00337-x · Cited by 1
Kamijo, Y., Fujigaki, Y., Parady, G., Takami, K., & Harata, N. (2023) · Japanese Journal of JSCE · doi:10.2208/jscejj.22-00244
Self-citationThe Impact of Technology on Transportation in the United States
(2024) · Quality - Access to Success · doi:10.47750/qas/25.202.02
Digital Twins for Assessing the Impact of Autonomous Vehicles on Built-Environment Changes
Aghaabbasi, M., Sabri, S., & Rajabifard, A. (2024) · Springer eBooks · doi:10.1007/978-3-031-67778-6_6
Sarri, P., Kaparias, I., & Preston, J. M. (2025) · Lecture notes in intelligent transportation and infrastructure · doi:10.1007/978-3-031-82714-3_35
Implications of collective transport automation for rural accessibility
Dianin, A. (2025) · reposiTUm (TU Wien) · doi:10.34726/hss.2025.138800
Abe, R., NIIKURA, A., Gouto, R., Park, H., & Fukuda, D. (2026) · Multimodal Transportation · doi:10.1016/j.multra.2026.100336
Metadata
- Authors
- LUO, L., TRONCOSO PARADY, G., TAKAMI, K., & HARATA, N.
- Affiliations
- The University of Tokyo (JP)
- Dept. of Urban Eng., The University of Tokyo
- Venue
- Journal of JSCE
- Publisher
- Japan Society of Civil Engineers
- Published
- 2019
- Volume
- 7
- Issue
- 1
- Pages
- 100-111
- ISSN
- 2187-5103 (ISSN-L)
- OpenAlex
- W2962769664
- Cited by
- 24
- References
- 29
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 10 · 2023: 2 · 2022: 6 · 2021: 3
- FWCI
- 1.03
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Journal of JSCE (publishedVersion)
- Topics
- Social Sciences › Transportation › Transportation and Mobility Innovations
- Social Sciences › Transportation › Transportation Planning and Optimization
- Social Sciences › Transportation › Urban Transport and Accessibility
- Keywords
- autonomous vehicles, accessibility (transport and spatial geography), shared autonomous vehicles, MATSim, agent-based modeling, travel demand, value of time, fleet size, urban sprawl, regional cities, Gunma Prefecture
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
