Autonomous Car using Raspberry PI and Ml
Yasir A1, Aiman Salim2, Arya Dileep3, Anjana S4
1Prof Yasir A *, Department of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India.
2Aiman Salim, BTech Student, Department of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India.
3Arya Dileep, BTech Student, Department of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India.
4Anjana S, BTech Student, Department of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India.
Manuscript received on May 25, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 30, 2020. | PP: 1067-1071 | Volume-9 Issue-2, July 2020. | Retrieval Number: B4033079220/2020©BEIESP | DOI: 10.35940/ijrte.B4033.079220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Proposed system’s goal is to represent an Autonomous car prototype which uses Raspberry Pi as the core functioning chip and our system use Open CV and Machine learning technology. The proposed system will move automatically without any human help to the destination by itself. The car uses the core processing system as Raspberry Pi, which is interfaced with the Pi camera module, will stream the video to the Monitor as the local host. Based on which the detection like pedestrians, vehicles or road sign and signals are done and corresponding commands are sent to the Arduino serially to operate the car. The Raspberry Pi has functionalities like, traffic signal detection, vehicle detection, pedestrian detection, road sign detection, which aids the proposed system in arriving the proposed or specified place cautiously and timely. Every process is completed using the Raspberry Pi with C++ programming. The methods used for achieving autonomous movement of car are Gaussian Blur, CED and Region of Interest. Assembled robot body by assembling the chassis and wheels of robot car, soldering the motors and fixed them in the chassis, fixed Raspberry Pi, Arduino Uno, motor driver and made the required circuit connections. The proposed system will be a helping hand in the vehicle industry as it will aid in easing the observation needed and tension taken, thereby easing human efforts while driving and minimizes the chance of collisions arising out of human error or law breaking driving resulting in large mortality rates.
Keywords: Raspberry Pi, Machine Learning.