Vasumathi Raman, Subhadeep Kumar, Aayush Ranawat, Ramkrishna Pasumarthy, Nirav Bhatt. Vision-based Lane Detection in Scaled-Down Testbed: A Comprehensive Pipeline with Experimental Insights. IFAC-PapersOnLine, Volume 59, Issue 30, 2025, Pages 623-628, ISSN 2405-8963.
Abstract: This paper presents a robust, vision-based lane detection pipeline tailored for a scaled-down electric vehicle (DEFT) and traffic testbed that replicates real-world traffic scenarios. The proposed method systematically benchmarks three edge detection algorithms (Gabor, Canny and Sobel) and adopts the Sobel filter to balance detection accuracy with computational efficiency on embedded hardware. By integrating HSV-based color masking, morphological operations, and hyperbolic model fitting, the method achieves reliable lane characterization even under occlusions and discontinuities. Experimental validation of the proposed method shows smoother trajectories and improved yaw stability compared to predefined waypoint-based navigation, reducing significant lap time. The approach dynamically adapts to lane geometry without reliance on pre-mapped waypoints or external localization aids, supporting real-time deployment in resource-constrained environments.
Published paper: https://www.sciencedirect.com/science/article/pii/S2405896325030174