DETECTION AND RECOGNITION OF TRAFFIC SIGNS FROM DATA COLLECTED BY THE MOBILE MAPPING SYSTEM

Autonomous vehicles and high-resolution maps are key elements of future transport systems. Detection and recognition of traffic signs is an important element for the safe driving of autonomous vehicles and the development of high-resolution maps. In this study, it is aimed to accurately detect and identify traffic signs based on the data collected by the mobile mapping system in order to ensure the safe movement of autonomous vehicles in traffic. A low-cost method is proposed with the ResNet-50 model for an autonomous vehicle to automatically detect and recognise traffic signs while moving on the road. As a result of the model training, 0.99 accuracy and 0.016 loss were obtained. The success of the method was first observed on images randomly selected from the dataset. Then, a real-time test was performed on a low-cost webcam. The tests showed that the handled method detects and identifies the traffic sign quickly and accurately.