Abstract Autonomous Vehicle (AV) technology is a disruptive transportation technology that promises to revolutionize how people travel. Due to their potential mobility benefits and associated impacts on public health and the environment, they have received massive attention from transportation experts. To date, there have been numerous academic research conducted regarding AVs, and many attempts have been made to summarize these research documents by manually reviewing them. Nevertheless, due to the vast nature of the existing literature, it is challenging to synthesize the themes in AV-related research and to explore their trends to inform future research direction. This study aims to utilize an advanced natural language processing technique to provide a comprehensive overview of the recent developments in AV-related research. The abstracts of 3292 articles published in transportation-based journals from January 2016 to October 2022 were collected and used for this study. A Structural Topic Model (STM) was employed to explore the dominant research themes hidden in the extant literature on AV research, examine their evolution over time, and determine the topics highly associated with developing and developed economies. Overall, the study highlighted that the least common themes in the literature are in the areas of the development of complex vehicle designs, safety, environmental benefits, and the impact of AVs on transportation infrastructure. Nevertheless, themes concerning AV safety and the environment are emerging as hot topics since late 2021. Topics related to investigating user perceptions, policies/approaches to increase user demand, and AV control/stability are highly studied. Besides, they predominantly originated from developed countries. The research themes, their associated trends, and the key policy suggestions drawn from the study are potentially useful for making well-informed research funding decisions, setting research priorities for countries, and guiding the future research endeavours of researchers.

    Highlights This paper explores the developments in Autonomous Vehicle-related research. Topics regarding user perceptions and vehicle stability are predominantly discussed. Safety issues and the impact of AVs on road infrastructure are less matured topics. High prevalent topics were mostly studied by authors in developed countries. Object detection and environmental perception have remained hot topics since 2016.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Discovering latent topics and trends in autonomous vehicle-related research: A structural topic modelling approach


    Contributors:

    Published in:

    Transport Policy ; 139 ; 1-20


    Publication date :

    2023-06-01


    Size :

    20 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Research topics and trends in the maritime transport: A structural topic model

    Bai, Xiwen / Zhang, Xiunian / Li, Kevin X. et al. | Elsevier | 2020




    Discovering latent activity patterns from transit smart card data: A spatiotemporal topic model

    Zhao, Zhan / Koutsopoulos, Haris N. / Zhao, Jinhua | Elsevier | 2020


    Discovering Latent Domains for Multisource Domain Adaptation

    Hoffman, J. / Kulis, B. / Darrell, T. et al. | British Library Conference Proceedings | 2012