TRAFFIC-SIGN RECOGNITION

Marcel Prodan (), Gabriel Dorobantu (), Narcis Ionita (), Mihai-Lucian Voncila (), Nicolae Tarba, Costin-Anton Boiangiu () and Nicolae Goga ()
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Costin-Anton Boiangiu: National University of Science and Technology POLITEHNICA Bucharest, Romania
Nicolae Goga: National University of Science and Technology POLITEHNICA Bucharest, Romania

Journal of Information Systems & Operations Management, 2024, vol. 18, issue 1, 186-205

Abstract: Traffic-sign recognition is critical for vehicle safety applications, especially as self-driving cars become a reality. This paper proposes a solution based on existing approaches, utilizing deep learning and computer vision preprocessing to create a real-time algorithm that addresses the limitations of previous methods. The proposed algorithm aims to overcome as many drawbacks as possible and serve as a core component of advanced driver- assistance systems (ADAS). The proposed method is evaluated using the German Traffic Sign Recognition Benchmark (GTSRB) and the Belgium Traffic Sign Dataset (BTSD). This study concludes with a fully functional pipeline that can inspire the development of driving assistants and advance the future of self-driving cars.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:rau:jisomg:v:18:y:2024:i:1:p:186-205

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