TY - JOUR
T1 - Discovering latent topics and trends in autonomous vehicle-related research
T2 - A structural topic modelling approach
AU - Tamakloe, Reuben
AU - Park, Dongjoo
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/8
Y1 - 2023/8
N2 - 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.
AB - 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.
KW - Autonomous vehicle
KW - Environment
KW - Machine learning
KW - Structural topic model
KW - Transport policy
KW - Transportation
UR - http://www.scopus.com/inward/record.url?scp=85161039816&partnerID=8YFLogxK
U2 - 10.1016/j.tranpol.2023.06.001
DO - 10.1016/j.tranpol.2023.06.001
M3 - Article
AN - SCOPUS:85161039816
SN - 0967-070X
VL - 139
SP - 1
EP - 20
JO - Transport Policy
JF - Transport Policy
ER -
