The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies
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Citations
Cites
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
Self-citationAssessing 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
Self-citationPreferences for shared autonomous vehicles
Krueger, R., Rashidi, T. H., & Rose, J. M. (2016) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2016.06.015 · Cited by 861
Schoettle, B., & Sivak, M. V. (2014) · Deep Blue (University of Michigan) · Cited by 406
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
Self-citationAre we ready to embrace connected and self-driving vehicles? A case study of Texans
Bansal, P., & Kockelman, K. M. (2018) · Transportation · doi:10.1007/s11116-016-9745-z · Cited by 296
Self-citationEvolution of the Light-Duty Vehicle Fleet
Paul, B. M., Kockelman, K. M., & Musti, S. (2011) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/2252-14 · Cited by 18
Self-citation
Cited by
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
Self-citationWhat drives people to accept automated vehicles? Findings from a field experiment
Xu, Z., Zhang, K., Min, H., Wang, Z., Zhao, X., & Liu, P. (2018) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2018.07.024 · Cited by 631
Faisal, A., Yigitcanlar, T., Kamruzzaman, M., & Currie, G. (2019) · Journal of Transport and Land Use · doi:10.5198/jtlu.2019.1405 · Cited by 427
“…disruptive effects is fairly limited (Bagloee, Tavana, Asadi, & Oliver, 2016; Gruel & Stanford, 2016; Truong, De Gruyter, Currie, & Delbosc, 2017), despite a recent prediction suggests that by 2045, AVs would account for up to half of all road travel (Bansal & Kockelman, 2017; Litman, 2017).”
BackgroundLiterature review on surveys investigating the acceptance of automated vehicles
Becker, F., & Axhausen, K. W. (2017) · Transportation · doi:10.1007/s11116-017-9808-9 · Cited by 418
External Human-Machine Interfaces on Automated Vehicles: Effects on Pedestrian Crossing Decisions
de Clercq, K., Dietrich, A., Núñez Velasco, J. P., de Winter, J., & Happee, R. (2019) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720819836343 · Cited by 359
Metadata
- Authors
- Bansal, P., & Kockelman, K. M.
- Venue
- Transportation Research Part A: Policy and Practice
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 95
- Pages
- 49-63
- ISSN
- 0965-8564 (ISSN-L)
- OpenAlex
- W2286716912
- Cited by
- 731
- References
- 7
- FWCI
- 42.72
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies. https://app.cochat.ai/papers/10.1016/j.tra.2016.10.013
- The paper
- Bansal, P., & Kockelman, K. M. (2017). Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies. Transportation Research Part A: Policy and Practice. https://doi.org/10.1016/j.tra.2016.10.013
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
