Mind the Gap: Developments in Autonomous Driving Research and the Sustainability Challenge

Mora, Luca; Wu, Xinyi; Panori, Anastasia

Abstract

Scientific knowledge on autonomous-driving technology is expanding at a faster-than-ever pace. As a result, the likelihood of incurring information overload is particularly notable for researchers, who can struggle to overcome the gap between information processing requirements and information processing capacity. We address this issue by adopting a multi-granulation approach to latent knowledge discovery and synthesis in large-scale research domains. The proposed methodology combines citation-based community detection methods and topic modeling techniques to give a concise but comprehensive overview of how the autonomous vehicle (AV) research field is conceptually structured. Thirteen core thematic areas are extracted and presented by mining the large data-rich environments resulting from 50 years of AV research. The analysis demonstrates that this research field is strongly oriented towards examining the technological developments needed to enable the widespread rollout of AVs, whereas it largely overlooks the wide-ranging sustainability implications of this sociotechnical transition. On account of these findings, we call for a broader engagement of AV researchers with the sustainability concept and we invite them to increase their commitment to conducting systematic investigations into the sustainability of AV deployment. Sustainability research is urgently required to produce an evidence-based understanding of what new sociotechnical arrangements are needed to ensure that the systemic technological change introduced by AV-based transport systems can fulfill societal functions while meeting the urgent need for more sustainable transport solutions.

• Journal Article Type: Article
• Acceptance Date: Aug 31, 2020
• Online Publication Date: Sep 11, 2020
• Publication Date: 2020-12
• Deposit Date: Sep 16, 2020
• Publicly Available Date: Sep 12, 2021
• Journal: Journal of Cleaner Production
• Print ISSN: 0959-6526
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 275
• Article Number: 124087
• DOI: https://doi.org/10.1016/j.jclepro.2020.124087
• Keywords: autonomous vehicle, research developments, text mining, topic modeling, sustainability, knowledge gap
• Public URL: http://researchrepository.napier.ac.uk/Output/2685949