Mapping Two Decades of Autonomous Vehicle Research: A Systematic Scientometric Analysis
Abstract
Autonomous vehicles (AV) have become a symbol of futuristic and intelligent transport innovation. This new driving technology has received heightened attention from academic, public, and private sectors. Nonetheless, a big challenge limiting a clear understanding of AV research is its scale. A large volume of literature is produced—covering various fields. This paper aims to map out the research on AV for a better understanding of the trends, patterns, and interconnections, and it critically reflects on their implications for research. A scientometric analysis technique is applied to analyze 4,645 papers published between 1998 and 2017. The findings disclose that (a) 87.7 percent of the AV studies was conducted by educational institutes; (b) Europe is the most productive continent in AV research with a 35.9 percent share of publications; (c) North America is the most influential continent in AV research, receiving 41.1 percent of the citations; (d) Over 50 percent of the studies were conducted during the last three years of the analysis period; (e) Urban and social contexts of AV research are still at their early stage; and (f) Relatively limited collaboration and knowledge sharing between academia and industry exist.
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AI applications are being used in areas ranging from marketing to banking and finance, from agriculture to healthcare and security, from space exploration to robotics and transport, and from chatbots to artificial creativity and manufacturing.
“AI applications are being used in areas ranging from marketing to banking and finance, from agriculture to healthcare and security, from space exploration to robotics and transport, and from chatbots to artificial creativity and manufacturing [6,7].”
From The sustainability of artificial intelligence: an urbanistic viewpoint from the lens of smart and sustainable cities (2020) · cites this paper as [7]
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- Authors
- Faisal, A., Yigitcanlar, T., Kamruzzaman, M., & Paz, A.
- Affiliations
- Queensland University of Technology (AU)
- School of Built Environment, Queensland University of Technology, Australia
- Venue
- Journal of Urban Technology
- Publisher
- Informa UK Limited
- Published
- 2020-08-11
- Volume
- 28
- Issue
- 3-4
- Pages
- 45-74
- ISSN
- 1063-0732 (ISSN-L)
- 1466-1853
- OpenAlex
- W3037903581
- Cited by
- 85
- References
- 86
- Citations by year
- 2026: 6 · 2025: 17 · 2024: 14 · 2023: 10 · 2022: 21 · 2021: 7 · 2020: 9 · 2013: 1
- FWCI
- 7.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Urban Technology (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- autonomous vehicles, research trends, research collaboration, academia-industry collaboration, citation analysis, urban mobility
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.
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