Abstract
Increased safety and reduction of road accidents, thus saving lives is one of the most popular aspects of Advanced Driver Assistance Systems (ADAS).When it comes to lane recognition and curve lane detection, accuracy has been a main focus of research. Focusing on detecting yellow and white lines, this paper focuses on a new lane detection method. This method includes setting the lower and upper thresholds for the Canny Edge detector which will cover both white and yellow lane lines. We also introduce a method that differentiates between the left and right lane change by analyzing the slope of the lanes detected.Traffic sign detection and recognition are crucial in the development of smart vehicles. The challenges to implementing this feature are: the illumination changes due to sun in day and streetlight at night, damaged traffic sign, and shadowed traffic sign. In this paper, we introduce an improved method to overcome these challenges and obtain an accuracy of approximately 98.27%.
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