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Analyzing Trends and Framework Models for Autonomous Vehicle Transition Strategies

Journal of the Civil Engineering Forum · Vol. 12 No. 3 (2026) · pp. 323–348

DOI
10.22146/jcef.26609
ISSN
2549-5925, 2581-1037
Published
2026-07-01
Publisher
Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada
Language
eng

Abstract

The shift from traditional human-driven to autonomous vehicles represents a transformation that is not merely technological, but also social. Currently, the deployment of autonomous vehicles remains largely at level where the human driver continues to be the primary decisionmaker. However, this dynamic is expected to change significantly as higher levels of autonomy are achieved. This study aims to identify the impacts that occur during process transition through emerging trends and theoretical lens of transition studies. The initial stage involved mapping trends in Autonomous Vehicle (AV) research to identify key related topics. This study uses bibliometric analysis of 82 key articles selected through a screening process in a systematic review. VOSviewer and CiteSpace were employed to map the research landscape, identify dominant topics, and trace the evolution of AV studies over time. The analysis highlights both well-established research areas and underexplored gaps. Furthermore, the articles were classified into categories based on transition study dimensions and key actors involedinvolved in facilitating a successful transition. The findings reveal a dominant research focus on users, human factors, and mobility behavior, whereas studies concerning vulnerable road users and the industry transition remain limited. To address this gap, this study investigates the socio-technical factors arising from the identified trends and transition studies while also exploring the roles of key stakeholders. This approach aims to achieve a more balanced perspective. Specifically, the study proposes a novel framework that connects critical actors with core socio-technical dimensions to support a sustainable autonomous ve-hicle transition. This research thus provides a strategic framework designed to guide and accelerate the shift toward autonomous mobility.

Keywords

Collaboration network of the authors

26 authors · 67 co-authorship links · 13 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Bandung Institute of Technology
  • Universitas Airlangga
  • Binus University
  • Universitas Halu Oleo
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Reza Ashari NasutionBandung Institute of Technology2
Lidia MayangsariBandung Institute of Technology2
Satria Fadil PersadaBinus University1
Michelle FericaBandung Institute of Technology1
Nila Armelia WindasariBandung Institute of Technology1
Nisful LailaUniversitas Airlangga1
Abdurrahman AbdurrahmanBandung Institute of Technology1
Aurik GustomoBandung Institute of Technology1
Sonny RustiadiBandung Institute of Technology1
Faridatus SaidahAffiliation unknown1
Sudarso Kaderi WiryonoAffiliation unknown1
Raden Aswin RahadiAffiliation unknown1
Annisa Rahmani QastharinAffiliation unknown1
Christoforine Agatha SetiawanAffiliation unknown1
Dimas Bayu Endrayana DharmowijoyoAffiliation unknown1
Bambang PramonoUniversitas Halu Oleo1
Liane OkdinawatiBandung Institute of Technology1
M. Setyawan SantosoAffiliation unknown1
Indira Ayu AdzhaniAffiliation unknown1
Mohamed Yusuf Faridian WirayatAffiliation unknown1
Muhammad Rafi FathurahmanAffiliation unknown1
Mursyid Hasan BasriAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jurnal.ugm.ac.id/v3/jcef/oai, first harvested 9 Nov 2026, last seen 9 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Analyzing Trends and Framework Models for Autonomous Vehicle Transition Strategies</dc:title>
	<dc:creator>Nurliyana, Cintia</dc:creator>
	<dc:creator>Lestari, Yuliani Dwi </dc:creator>
	<dc:creator>Prasetio, Eko Agus</dc:creator>
	<dc:creator>Belgiawan, Prawira Fajarindra</dc:creator>
	<dc:subject xml:lang="en-US">Autonomous vehicle</dc:subject>
	<dc:subject xml:lang="en-US">Transition</dc:subject>
	<dc:subject xml:lang="en-US">Bibliometric</dc:subject>
	<dc:description xml:lang="en-US">The shift from traditional human-driven to autonomous vehicles represents a transformation that is not merely technological, but also social. Currently, the deployment of autonomous vehicles remains largely at level where the human driver continues to be the primary decisionmaker. However, this dynamic is expected to change significantly as higher levels of autonomy are achieved. This study aims to identify the impacts that occur during process transition through emerging trends and theoretical lens of transition studies. The initial stage involved mapping trends in Autonomous Vehicle (AV) research to identify key related topics. This study uses bibliometric analysis of 82 key articles selected through a screening process in a systematic review. VOSviewer and CiteSpace were employed to map the research landscape, identify dominant topics, and trace the evolution of AV studies over time. The analysis highlights both well-established research areas and underexplored gaps. Furthermore, the articles were classified into categories based on transition study dimensions and key actors involedinvolved in facilitating a successful transition. The findings reveal a dominant research focus on users, human factors, and mobility behavior, whereas studies concerning vulnerable road users and the industry transition remain limited. To address this gap, this study investigates the socio-technical factors arising from the identified trends and transition studies while also exploring the roles of key stakeholders. This approach aims to achieve a more balanced perspective. Specifically, the study proposes a novel framework that connects critical actors with core socio-technical dimensions to support a sustainable autonomous ve-hicle transition. This research thus provides a strategic framework designed to guide and accelerate the shift toward autonomous mobility.</dc:description>
	<dc:publisher xml:lang="en-US">Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada</dc:publisher>
	<dc:date>2026-07-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jurnal.ugm.ac.id/v3/JCEF/article/view/26609</dc:identifier>
	<dc:identifier>10.22146/jcef.26609</dc:identifier>
	<dc:source xml:lang="en-US">Journal of the Civil Engineering Forum; Vol. 12 No. 3 (September 2026); 323-348</dc:source>
	<dc:source>2549-5925</dc:source>
	<dc:source>2581-1037</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jurnal.ugm.ac.id/v3/JCEF/article/view/26609/7239</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 The Author(s)</dc:rights>
</oai_dc:dc>