REVIEW article
Front. Future Transp.
Sec. Transportation Systems Modeling
Volume 6 - 2025 | doi: 10.3389/ffutr.2025.1627426
This article is part of the Research TopicAdvancements in Traffic Safety: Data-Driven Insights and Emerging TechnologiesView all articles
A Bibliometric Analysis of Multi-source Information Fusion Mechanisms in Intelligent Transportation Big Data: Applications and Efficiency Perspectives
Provisionally accepted
- School of Computing, Faculty of Engineering, University Technology Malaysia, Johor Bahru, Malaysia
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The Multi-source Information Fusion (MSIF) mechanism and its applications involving big data in Intelligent Transportation Systems (ITS) represent a major research focus in current studies. This paper conducts a bibliometric analysis to summarize and evaluate developments in this domain. Initially, it categorizes the main application areas within ITS, then identifies the types and structures of data commonly involved, as well as frequently used datasets and evaluation metrics. It further explores specific MSIF applications in ITS, including road traffic management, traffic control, and transportation engineering computations. In particular, MSIF has demonstrated significant potential in enhancing transportation efficiency-such as reducing congestion, optimizing traffic signal coordination, and improving route planning-as well as improving energy efficiency by enabling eco-driving strategies and minimizing unnecessary fuel consumption. Based on the bibliometric findings, the study highlights current research challenges and key issues, while offering insights into future directions of MSIF development in intelligent transportation big data. This analysis aims to provide researchers and practitioners with a comprehensive overview and valuable guidance on the MSIF mechanism and its applications in ITS.
Keywords: Intelligent transportation system, big data, Multi-source information fusion, Information Fusion Mechanism, Intelligent transportation applications, bibliometric analysis
Received: 14 May 2025; Accepted: 19 Jun 2025.
Copyright: © 2025 Li, Mohd Adham Isa, Khatibsyarbini, Abdull Hamed and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
MinSong Li, School of Computing, Faculty of Engineering, University Technology Malaysia, Johor Bahru, Malaysia
Dr. Mohd Adham Isa, School of Computing, Faculty of Engineering, University Technology Malaysia, Johor Bahru, Malaysia
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