Buse PehlivanCeren KahramanDeniz KurtelMert NakıpCüneyt GüzelişKurtel, DenizKahraman, CerenGuzelis, CuneytPehlivan, BuseNakip, Mert2025-10-062020978172819136210.1109/ASYU50717.2020.92598302-s2.0-85097926177https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097926177&doi=10.1109%2FASYU50717.2020.9259830&partnerID=40&md5=24a706d49742da4791014e34af1af31chttps://gcris.yasar.edu.tr/handle/123456789/9152https://doi.org/10.1109/ASYU50717.2020.9259830In this paper in order to realize a prototype of an autonomous vehicle we present a framework that consists of convolutional neural networks and image processing methods. The study is comprised of two main parts as software and hardware. In the hardware part a small-sized smart video car kit is used as the prototype of the autonomous car. This programmable tool consists of Raspberry Pi servo motors and a USB webcam whose angle of vision is equal to 120°. In the software part we propose an algorithm in which we use Convolutional Neural Networks to detect the objects (vehicles pedestrians and traffic signs) and Hough transformation to detect the road lanes. Based on the outputs of the object and lane detections the system decides the speed and the direction of the car in real-time. In our results the vehicle performs autonomous driving in the scaled real-world application. © 2020 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessAutonomous Car, Convolutional Neural Networks, Lane Detection, Object Detection, Convolution, Convolutional Neural Networks, Intelligent Systems, Object Detection, Real Time Control, Traffic Signs, Autonomous Driving, Hough Transformation, Image Processing - Methods, Lane Detection, Real-time Implementations, Single Shots, Software And Hardwares, Software Parts, Autonomous VehiclesConvolution, Convolutional neural networks, Intelligent systems, Object detection, Real time control, Traffic signs, Autonomous driving, Hough Transformation, Image processing - methods, Lane detection, Real-time implementations, Single shots, Software and hardwares, Software parts, Autonomous vehiclesAutonomous CarObject DetectionConvolutional Neural NetworksLane DetectionConference Object