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Unstructured Road Detection Segmentation for Autonomous Car
Zainuddin Z.
Aip Conference Proceedings
Abstract
One of the important things in Autonomous Car technology is detecting the road so that it remains on the right lane, therefore this paper aims to be able to detect unstructured roads based on the results of the HSY color space segmentation on the road then produce vehicle position information from the center of the lane (center offset). In marking the roadside boundary, the method used is the Hough transform based on the resulting edge lines using an edge detector, then the coordinates of the left and right curb lines which represent the width of the road. The results of this paper indicate that the system’s ability to distinguish road and non-road areas on several roads with an average percentage of 99.59% for accuracy, 99.49% for precision and 98.84% for recall and the system’s ability to mark areas. The average road reaches 99.27% and the percentage error and accuracy obtained provide information on the position of the car from the center (center offset) based on the actual value and prediction results of 16.05% and 84.14%.