Abstract
Autonomous driving has become an increasingly relevant issue for policymakers, the industry, service providers, infrastructure companies, and science. This study shows how bibliometrics can be used to identify the major technological aspects of an emerging research field such as autonomous driving. We examine the most influential publications and identify research fronts of scientific activities until 2017 based on a bibliometric literature analysis. Using the science mapping approach, publications in the research field of autonomous driving were retrieved from Web of Science and then structured using the bibliometric software BibTechMon by the AIT (Austrian Institute of Technology). At the time of our analysis, we identified four research fronts in the field of autonomous driving: (I) Autonomous Vehicles and Infrastructure, (II) Driver Assistance Systems, (III) Autonomous Mobile Robots, and (IV) IntraFace, i.e., automated facial image analysis. Researchers were working extensively on technologies that support the navigation and collection of data. Our analysis indicates that research was moving towards autonomous navigation and infrastructure in the urban environment. A noticeable number of publications focused on technologies for environment detection in automated vehicles. Still, research pointed at the technological challenges to make automated driving safe.
Highlights
An early identification of new technologies is essential for the development of corporate strategies in which upcoming trends should be considered
Using the science mapping approach, publications in the research field of autonomous driving were retrieved from Web of Science and structured using the bibliometric software BibTechMon by the AIT (Austrian Institute of Technology)
Based on the analyses and results obtained via Web of Science (WoS) and BibTechMon, several frequency distributions as well as main research areas in the field of autonomous driving are presented in this chapter
Summary
An early identification of new technologies is essential for the development of corporate strategies in which upcoming trends should be considered. The early recognition of new technologies aims at the identification of upcoming developments in relevant technological areas and at evidence-based technology-related management decisions. All information that might influence the (future) corporate environment should be gathered and provided as early as possible If a corporate institution is taken by surprise due to upcoming technological changes, its competitive position could be jeopardized. The rapid growth of the world’s knowledge is a challenge for the early identification of new technologies. Since human beings are not able to process the volume of all available data by themselves, organisations need to acquire competencies in data management for business intelligence in order to stay competitive. The high complexity – as well as the lack of transparency – is, not to be underestimated (Wellensiek et al, 2010, p. 89ff.)
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