AI-BASED ROAD SIGN DETECTION AND AUTONOMOUS SPEED CONTROL SYSTEM FOR ELECTRIC VEHICLES

Abstract

Road traffic accidents caused by overspeeding and delayed driver response remain major challenges in modern transportation systems. Although electric vehicles (EVs) provide environmentally friendly mobility, ensuring safe driving through intelligent speed regulation has become increasingly important. Conventional speed control systems depend primarily on driver awareness, which may result in delayed reactions to road signs, especially in high-speed or congested traffic conditions. Recent advancements in Artificial Intelligence (AI), Computer Vision, and Deep Learning have enabled the development of intelligent driver assistance systems capable of automatically recognizing road signs and controlling vehicle speed in real time. This project presents an AI-Based Road Sign Detection and Automatic Speed Control System for Electric Vehicles. The proposed framework employs a camera mounted on the vehicle to continuously capture road images during driving. The acquired images undergo preprocessing operations including noise removal, resizing, and contrast enhancement before being processed by a deep learning model such as Convolutional Neural Network (CNN) or YOLO (You Only Look Once) for road sign detection and classification. The AI model accurately recognizes traffic signs including speed limits, school zones, stop signs, no-entry signs, pedestrian crossings, and warning signs. Based on the detected speed limit, the intelligent controller automatically adjusts the speed of the electric vehicle by regulating the motor drive without requiring driver intervention. The system continuously monitors vehicle speed and road conditions to ensure safe operation while providing visual and audio alerts whenever necessary. Experimental evaluation demonstrates high road sign detection accuracy, reliable speed control performance, and rapid response under different driving conditions. The proposed intelligent framework improves road safety, reduces human driving errors, enhances compliance with traffic regulations, and supports the development of autonomous and intelligent electric transportation systems. Keywords: Artificial Intelligence, Road Sign Detection, Automatic Speed Control, Electric Vehicle, Computer Vision, Deep Learning, Convolutional Neural Network (CNN), YOLO, Intelligent Transportation System, Advanced Driver Assistance System (ADAS).