An Automatic Vehicle Speed Controlling based on Traffic Signs Recognition using Convolutional Neural Network

Autonomous driving systems and applications in the real time are the trending field these days. To carry out all the necessary operations in accordance with the requirements, these systems do require sophisticated algorithms. One of the most challenging constraints in performing actions by autonomous driving systems is controlling road speed. The novel method proposed for motor controlling speed in accordance with speed stipulations uses a Convolutional Neural Network (CNN) algorithm to scan speed limit sign boards. The effectiveness of our system is contingent on CNNs' ability to properly recognize and classify objects in images, which are then used to extract speed limit information from sign boards. The pace of the robot chassis is regulated by an Arduino microcontroller using the CNN’s output. Through simulations and tests on a real testbed, we show how effective our method is and show that it can maintain the desired speed with a tolerable degree of error.