Novel Stop Sign Detection Algorithm Based on Vehicle Speed Profile

Automated driving technology involves various modern in-vehicle systems that are designed to increase road traffic safety by helping drivers gain a better awareness of the road and its potential hazards as well as other drivers around them. Stop sign detection module is an integral part of these systems as it has great utility in automated or assisted driving applications. Although promising results have been achieved in the areas of stop sign detection and classification, these methods are heavily dependent on images and image processing algorithms and detection problem in the real world remains a challenging issue. In this paper, we propose a method to detect the stop sign, based on statistical analysis of data obtained by drive history, a project conducted by Ford Motor Company. Our detection algorithm is based on the speed profile where speed is zero or close to zero. Then, we apply clustering to our data set to extract the points with this common feature. In the end, results demonstrate that our algorithm can improve the stop sign detection efficiency and afford high precision where other algorithms are prone to failure.