Mask R-CNN Approach to Real-Time Lane Detection for Autonomous Vehicles

Abdrakhmanov R. Elemesova M. Zhussipbek B. Bainazarova I. Turymbetov T. Mendibayev Z.
2023 Science and Information Organization

International Journal of Advanced Computer Science and Applications
2023 #14 Issue 5 549 - 556 pp.

The accurate and real-time detection of road lanes is crucial for the safe navigation of autonomous vehicles (AVs). This paper presents a novel approach to lane detection by leveraging the capabilities of the Mask Region-based Convolutional Neural Network (Mask R-CNN) model. Our method adapts Mask R-CNN to specifically address the challenges posed by diverse traffic scenarios and varying environmental conditions. We introduce a robust, efficient, and scalable architecture for lane detection, which segments the lane markings and generates precise boundaries for AVs to follow. We augment the model with a custom dataset, consisting of images collected from different geographical locations, weather conditions, and road types. This comprehensive dataset ensures the models generalizability and adaptability to real-world conditions. We also introduce a multi-scale feature extraction technique, which improves the models ability to detect lanes in both near and far fields of view. Our proposed method significantly outperforms existing state-of-the-art techniques in terms of accuracy, processing speed, and adaptability. Extensive experiments were conducted on public datasets and our custom dataset to validate the performance of the proposed method. Results demonstrate that our Mask R-CNN-based approach achieves high precision and recall rates, ensuring reliable lane detection even in complex traffic scenarios. Additionally, our models real-time processing capabilities make it an ideal solution for implementation in AVs, enabling safer and more efficient navigation on roads.

autonomous vehicle , deep learning , detection , lane , Mask R-CNN , Road

Text of the article Перейти на текст статьи

International University of Tourism and Hospitality, Turkistan, Kazakhstan
Bachelor Student, International University of Tourism and Hospitality, Turkistan, Kazakhstan
Korkyt Ata Kyzylorda University, Kyzylorda, Kazakhstan
M. Auezov South Kazakhstan University, Shymkent, Kazakhstan
Khoja Akhmet Yassawi International Kazakh, Turkish University, Turkey
Al-Farabi Kazakh National University, Almaty, Kazakhstan

International University of Tourism and Hospitality
Bachelor Student
Korkyt Ata Kyzylorda University
M. Auezov South Kazakhstan University
Khoja Akhmet Yassawi International Kazakh
Al-Farabi Kazakh National University

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026