Artificial Intelligence in Self-Driving Cars Research and Innovation: A Scientometric and Bibliometric Analysis

Abstract

This paper presents a scientometric and bibliometric analysis of research and innovation on self-driving cars. Through an examination of quantitative empirical evidence, we explore the importance of Artificial Intelligence (AI) as machine learning, deep learning and data mining on self-driving car research and development as measured by patents and papers. Alongside the exponential growth in the rate of inventive activities and scholarly efforts, we find evidence for a rapid and meaningful shift in the application of the technologies related to data gathering and processing for the purpose of self-driving cars after 2009. We show that this shift mirrors major changes in the landscape of innovators as well as increasing scholarly attention to the ethical, legal and social aspects of self-driving cars. Research and innovation relating to self-driving seem to be increasingly defined in terms of artificial intelligence, which neglects some aspects of future socio-technical systems that may be required to realise the potential of the technology.

Keywords: self-driving cars; research; innovation; artificial intelligence; bibliometric; scientometric.

JEL Classification: O30; O33