Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{159204,
        author = {Astha Singh  and Yash Bhadreshwara  and Aditya Deshpande  and Shivam Mane and Dhanashri Pannase},
        title = {Self driving car: using openCV Library and Python},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {11},
        pages = {545-549},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159204},
        abstract = {The project uses the most recent OpenCV and Machine Learning technology to simulate a prototype of a self-driving car with monocular vision. Self-driving cars are autonomous vehicles that would reduce the need for human involvement, lowering the danger of accidents, and improving the safety, comfort, and accessibility of transportation. The car model will have the ability to recognise the lane path, sign boards, traffic light signals, and react to moving traffic in real time. The Raspberry Pi central processing unit, in conjunction with peripherals like the, L298 H-Bridge, and Raspberry Pi Cam2, is what gives our car the appropriate level of control. To give the car the necessary functionalities, computer vision is combined with algorithms like lane detection and object detection.},
        keywords = {Open CV, Machine Learning, Raspberry pi, Lane Detection, Object Detection, Canny Edge Detection.},
        month = {},
        }