Autonomous vehicles: Scientometric and bibliometric studies.

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Purpose: Many IT-related industries are emerging in the second information revolution based on mobile information technology, which is sometimes called the fourth industrial revolution (Rifkin, 2011; Schwab, 2017). In this context, the first car-like robot (truly autonomous) appeared in the mid-1980s with Carnegie Mellon University's Navlab, the ALV projects in 1984 and Mercedes-Benz and Bundeswehr University Munich's Eureka Prometheus Project in 1987. Since then, several advances have been made in this area and numerous major companies and research institutions have developed Autonomous Vehicles (AVs) prototypes. In this sense, AVs have been gained more and more attention. Countless companies, such as Tesla, Google, Uber, BMW, GM, and Ford, have been standing out in a “race” for the lead in the innovation process regarding the AVs. Even though, there has been an establishment of a theoretical field regarding AVs, it is not yet evident the main aspects that permeate the field, as well as its conceptual foundation, trends, and characteristics. Regarding such considerations, the following questions emerged as guidelines for this paper: How does the AVs study field perform? What are the main trends of analysis? In this sense, this paper aims to identifying – from a scientometric and systematic literature review of AVs studies indexed in the Web of Science database – the main characteristics of this domain, as well as its evolution, in order to highlight potential gaps for prospective studies. There are several contributions on the subject, and the transition from a long-established industry (automotive) to a new configuration (autonomy) is still surrounded by uncertainties as to the inherent aspects of regulatory factors, technology, business models and market. Through the investigation and mapping of the main aspects that permeate this object (AVs), a studies’ panorama can be established in order to contribute to the field and build a context that meets the agenda of a global development.
Design: This study was guided by a scientometric systematic literature review, carried out during the months of November – 2016 to February – 2017. The methodological approach was composed by the following steps: 1) delimitation of the scope of analysis and selection of papers; 2) descriptive analysis of papers based on Web of Science metadata; 3) in-depth analysis of papers based on CiteSpace; 4) interpretation and discussion of results. A total of 6,711 papers were found, therefore constituting the research corpus of the present study.
Findings: A great heterogeneity was observed among the authors that published the most. Based on Web of Science results, a sum of 6,944 authors was responsible for 6,711 papers published in the analyzed period. From this result, a parallel with Price's Elitism Law (1976) was made, where we observed that the AVs field is still incipient considering the reduced number of works-per-author, not being observed yet, the existence of considerable productive elite. As for the number of publications, we carried out Bradford’s dispersion Law (1934) analysis. This analysis demonstrated that only 34 sources (3%) were responsible for approximately 33% (2,247) of all field’s publications. Still regarding the number of publications, it was observed that from the total of documents, approximately 66% are proceedings papers against 34% of journal articles, which may explain a recent recurrence of AVs in academia. This result also evidences that the discussion about AV are far from being exhausted, characterizing AVs as a trending topic among researchers. By the keywords burst and authors co-citation analyses, it was evident that “infrastructure”, “problem-solving”, “human factors”, “choice”, “safety”, “behavior”, and “information” are areas that could help the AVs advance and are still incipient. The categories analysis indicated that most articles belong to the “Engineering” category (3,676), followed by “Computer Science” (2,791). Although there are studies related to “Business”, “Economics”, and “Management”, we observed a slight evolution of these domains regarding AVs. The countries’ analysis demonstrated that the numbers of papers in the field were more representative in areas where public administration stimulated and attracted stakeholders setting the conditions to undertake tests and authorizing the use of automated vehicles on roads (e.g. USA, China, and EU).
Practical Implications: We observed that the AV’s “race” goes beyond technological issues or as a battle between OEMs around the world. We have analyzed the Department of Transportation’s Reports about AV around the world and observed that governments’ battle really exists. For instance, the Pathway to Driverless Car report from the UK shows us, in the very early pages that; “We are setting out the best possible framework to support the testing of automated vehicles, to encourage the largest global businesses to come to the UK to develop and test their technologies” (Department for transport, 2015 p. 5). Noteworthy, there is a consensus that technological factors are essential for the field’s evolution and these should not be neglected at all. However, other areas are also essential for dissemination of the field and must pursue opportunities and needs of this emerging topic. It is evident the technological evolution of AVs’ field. However, as in any other sector, there is a need to understand broader aspects of this industry such as market factors surrounding it, as well as other economic and managerial issues. The keywords burst analysis corroborates the recent requirements of the field to extrapolate the technological areas, indicating market plans; in this sense, business model plays an extremely important role in the events that precede the advancement of AV in society (Yun et al., 2016). Finally, we would like to emphasize the numerous research possibilities detached from this work, indicated by the co-citation map, that presented a powerful research tool for highlighting the main subjects related to AVs.