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March 13, 2026Applied SciencesOpen Access

ADAS-TSR: A Deep Learning-Based Traffic Sign Recognition System with Voice Alerts for Andean Historic City Centers

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Authors

EUEduardo J. Urbina-DominguezHAHemerson Lizarbe AlarcónYGYuri Galvez-Gastelu

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Overview

This research introduces a deep learning system that enhances traffic sign recognition in historic city centers, improving road safety.

Key Points

  • The study aims to develop an advanced driver assistance system for traffic sign recognition in colonial city centers.
  • Constructed a dataset of 2250 images with 2450 instances of 14 traffic sign classes.
  • Conducted a benchmark experiment comparing four CNN-based and one transformer-based detector.
  • Implemented a voice alert system with five priority levels for detected signs.
  • Performed validation across five urban circuits totaling 14.11 km.
  • YOLO26s achieved the highest performance with mAP@0.5 of 0.994.
  • Detection rate of 94.7% in validation circuits.
  • Uncertainty analysis showed high prediction confidence with mean > 0.90 for modern architectures.
  • Reduced redundant alerts by 73% through a rule-based filtering system.

Cite This Study

Urbina-Dominguez et al. (2026) studied this question.

synapsesocial.com/papers/69b3ab4c02a1e69014ccc1b1https://doi.org/10.3390/app16062664
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