Performance Analysis of Yolo Versions on Road Environment

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YOLOv5x achieved the highest accuracy with a mean average precision of 76.2%, demonstrating its effectiveness.
YOLOv8n provided the fastest inference time at 2.2 milliseconds, which is crucial for real-time applications.
The study identified that small object detection challenges significantly hindered overall model performance.
Dataset class imbalance emerged as a notable issue affecting detection accuracy across all tested YOLO versions.

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Evaluation reveals YOLOv5's superior accuracy and YOLOv8n's fastest inference in autonomous driving applications.

Ikmel et al. (2025) studied this question.

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