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Cognition of road traffic signs: a systematic literature review


Citation

Mohamed, Raihani and Peizhi, Wang and Manshor, Noridayu and Mustapha, Norwati (2024) Cognition of road traffic signs: a systematic literature review. Journal of Theoretical and Applied Information Technology, 102 (7). pp. 3040-3058. ISSN 1992-8645; eISSN: 1817-3195

Abstract

As a research hotspot in computer vision, traffic sign recognition has made remarkable progress in the past few years. This study provides a systematic review of the field of traffic sign recognition. Thirty-nine papers relevant to this study were manually selected for exploration from four well-known databases (IEEE Xplore, ScienceDirect, Scopus, and Google Scholar). Five questions were proposed to describe general trends in traffic sign recognition. These questions are answered by the literature review. Specifically, first, determine the literature review method and select the papers to be analyzed. Next, various algorithms and commonly used data sets for traffic sign recognition are analyzed in detail. Then, the advantages and disadvantages of various algorithms are compared, and the challenges faced in traffic sign recognition are discussed in depth. Finally, the application fields of traffic sign recognition were deeply explored. This review helps provide guidance and comprehensive information to researchers in this field.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
Publisher: Little Lion Scientific
Keywords: Traffic sign recognition; Deep learning; Localization; Classification; Datasets
Depositing User: Ms. Zaimah Saiful Yazan
Date Deposited: 07 Aug 2025 01:39
Last Modified: 07 Aug 2025 01:39
URI: http://psasir.upm.edu.my/id/eprint/119167
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