Refining Road Damage Detection Using YOLOv8 for Enhanced Safety

Addressing the demand for efficient road maintenance, especially for automated vehicles, this research introduces a YOLOv8-based approach to road damage detection. Utilizing YOLOv8’s real-time capabilities enhances the precision and reliability of anomaly detection, crucial for safety and maintenance optimization. Experimental results demonstrate YOLOv8’s superior accuracy. Integrating YOLOv8 represents a significant advancement toward deploying automated vehicles, enhancing road safety, and optimizing maintenance. Practical considerations include data privacy and regulatory compliance. In summary, this system enhances road safety and aligns with the evolving landscape of automated transportation, supporting safe and efficient navigation by automated vehicles.