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Autonomous vehicles: scientometric and bibliometric review

Author

Listed:
  • Rodrigo Marçal Gandia
  • Fabio Antonialli
  • Bruna Habib Cavazza
  • Arthur Miranda Neto
  • Danilo Alves de Lima
  • Joel Yutaka Sugano
  • Isabelle Nicolai
  • Andre Luiz Zambalde

Abstract

This paper presents a scientometric and bibliometric review of the research on autonomous vehicles (AVs) to identify its main characteristics, evolution, and potential trends for future studies. Relevant articles were searched on WoS, yielding a research corpus of 10,580 papers, and the software CiteSpace was subsequently used for analysis. The results showed that AV research is heterogeneous and registered a growing demand over time. Multidisciplinarity is present, with 96 science fields being identified. As in any other sector, it is necessary to understand broader aspects of this industry such as the market factors surrounding it, as well as other economic and managerial issues. In this sense, we observed a migration of the research field from multidisciplinarity to pluridisciplinarity with a greater number of studies focusing on the latter. We understand that terminology standardisation contributes to achieving pluridisciplinarity. As such, it is important to highlight that sustainability, public policies, liability, and safety, as well as business issues such as performance and business models are some of the tendencies in the field of AVs. For future studies, we suggest a more in-depth analysis of publications in terms of individual search terms, as well as the sub-areas identified as trends in this paper.

Suggested Citation

  • Rodrigo Marçal Gandia & Fabio Antonialli & Bruna Habib Cavazza & Arthur Miranda Neto & Danilo Alves de Lima & Joel Yutaka Sugano & Isabelle Nicolai & Andre Luiz Zambalde, 2019. "Autonomous vehicles: scientometric and bibliometric review," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 9-28, January.
    • Handle: RePEc:taf:transr:v:39:y:2019:i:1:p:9-28
    DOI: 10.1080/01441647.2018.1518937
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    2. Fabio Antonialli & Bruna Habib Cavazza & Rodrigo Gandia & Isabelle Nicolaï & Arthur de Miranda Neto & Joel Sugano & André Luiz Zambalde, 2020. "Human or machine driving? Comparing autonomous with traditional vehicles value curves and motives to use a car," Post-Print halshs-03687616, HAL.
    3. Raj, Alok & Kumar, J. Ajith & Bansal, Prateek, 2020. "A multicriteria decision making approach to study barriers to the adoption of autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 122-137.
    4. Shuang Kan & Wei Lyu & Shiyu Zhao, 2022. "Evaluation of the Environmental Effect of Automated Vehicles Based on IVIULWG Operator Development," Sustainability, MDPI, vol. 14(15), pages 1-14, August.
    5. Kroesen, Maarten & Milakis, Dimitris & van Wee, Bert, 2023. "Automated Vehicles: Changes in expert opinions over time," Transport Policy, Elsevier, vol. 136(C), pages 1-10.
    6. Alberto Dianin & Elisa Ravazzoli & Georg Hauger, 2021. "Implications of Autonomous Vehicles for Accessibility and Transport Equity: A Framework Based on Literature," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
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    8. Tianlong Yu & Hao Yang & Xiaowei Luo & Yifeng Jiang & Xiang Wu & Jingqi Gao, 2021. "Scientometric Analysis of Disaster Risk Perception: 2000–2020," IJERPH, MDPI, vol. 18(24), pages 1-19, December.
    9. Du, Manqing & Zhang, Tingru & Liu, Jinting & Xu, Zhigang & Liu, Peng, 2022. "Rumors in the air? Exploring public misconceptions about automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 237-252.
    10. Kassens-Noor, Eva & Dake, Dana & Decaminada, Travis & Kotval-K, Zeenat & Qu, Teresa & Wilson, Mark & Pentland, Brian, 2020. "Sociomobility of the 21st century: Autonomous vehicles, planning, and the future city," Transport Policy, Elsevier, vol. 99(C), pages 329-335.
    11. Cohen, Tom & Jones, Peter, 2020. "Technological advances relevant to transport – understanding what drives them," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 80-95.
    12. Jiao Zhang & Qian Wang & Yiping Xia & Katsunori Furuya, 2022. "Knowledge Map of Spatial Planning and Sustainable Development: A Visual Analysis Using CiteSpace," Land, MDPI, vol. 11(3), pages 1-24, February.
    13. Fabio Antonialli, 2019. "International benchmark on experimentations with Autonomous Shuttles for Collective Transport," Post-Print hal-02489797, HAL.
    14. Muhammad Azam & Sitti Asmah Hassan & Othman Che Puan, 2022. "Autonomous Vehicles in Mixed Traffic Conditions—A Bibliometric Analysis," Sustainability, MDPI, vol. 14(17), pages 1-34, August.
    15. Alexandros Nikitas & Kalliopi Michalakopoulou & Eric Tchouamou Njoya & Dimitris Karampatzakis, 2020. "Artificial Intelligence, Transport and the Smart City: Definitions and Dimensions of a New Mobility Era," Sustainability, MDPI, vol. 12(7), pages 1-19, April.
    16. Amalia Polydoropoulou & Ioannis Tsouros & Nikolas Thomopoulos & Cristina Pronello & Arnór Elvarsson & Haraldur Sigþórsson & Nima Dadashzadeh & Kristina Stojmenova & Jaka Sodnik & Stelios Neophytou & D, 2021. "Who Is Willing to Share Their AV? Insights about Gender Differences among Seven Countries," Sustainability, MDPI, vol. 13(9), pages 1-19, April.
    17. Fabio Antonialli & Danielle Attias, 2019. "Social and economic impacts of Autonomous Shuttles for Collective Transport: an in- depth benchmark study," Post-Print hal-02489808, HAL.
    18. Ishant Sharma & Sabyasachee Mishra, 2023. "Ranking preferences towards adopting autonomous vehicles based on peer inputs and advertisements," Transportation, Springer, vol. 50(6), pages 2139-2192, December.
    19. Maria Cieśla & Aleksander Sobota & Marianna Jacyna, 2020. "Multi-Criteria Decision Making Process in Metropolitan Transport Means Selection Based on the Sharing Mobility Idea," Sustainability, MDPI, vol. 12(17), pages 1-21, September.

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