Abstract:

With the rapid advancement of technology, artificial intelligence (AI) is increasingly used in various sectors like education, health, security, and defense. A critical application of AI is in highway management, especially with the rise of autonomous vehicles. The focus of this study is to address the issue of deformations in highway marking lines, which pose challenges for autonomous vehicles and impact traffic safety. The research involves using an unmanned aerial vehicle (UAV) to create an original image dataset of highway lines. This dataset will undergo processing with image enhancement techniques and deep learning models. The initial phase involves cleaning the images of impurities. Subsequently, deep learning models will identify potential line deformations. These models will be refined and trained for optimal accuracy using various performance metrics. The final goal is to implement a real-time system, combining the UAV with a ground computer system, to accurately detect and report any discrepancies in highway lines. This will ensure timely notification to authorities, helping prevent traffic safety issues related to line deformations. This approach demonstrates the practical applications of AI in enhancing road safety and autonomous vehicle navigation.

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