International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Automatic Vehicle Speed Controlling System by Detecting Traffic sign boards, Potholes and Speed bumps

Author(s) Salma P S, Minu Mohan
Country India
Abstract In an effort to reduce accidents and promote adherence to traffic laws, this study attempts to detect and identify potholes, speed bumps, and traffic sign boards in a variety of backgrounds and lighting conditions. The "Automatic Vehicle Speed Controlling System by Detecting Traffic Sign Boards, Potholes, and Speed Bumps" is a cutting-edge automotive safety and control system designed to increase road safety and manage vehicle speed. To enable autonomous real-time recognition and interpretation of potholes, speed bumps, and traffic signs, as well as to regulate the vehicle speed in accordance with the detected feature, the system incorporates advanced technologies such as computer vision, deep learning, and embedded systems. This work provides a novel solution to these issues by autonomously detecting potholes, speed bumps, and traffic sign boards on highways by utilizing deep learning algorithms and image processing capabilities. In this technology, photos captured by cameras mounted on vehicles are analysed using computer vision algorithms. By using a deep learning algorithm, the system can accurately identify and classify traffic sign boards and abnormalities in the road, including potholes and speed bumps, from the recorded data. Based on this classification, the system may adjust the vehicle's speed.
Keywords Deep Learning, Computer vision, Open CV, Automatic Vehicle Speed Controlling System (AVSCS)
Field Engineering
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-06-02
Cite This Automatic Vehicle Speed Controlling System by Detecting Traffic sign boards, Potholes and Speed bumps - Salma P S, Minu Mohan - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.21913
DOI https://doi.org/10.36948/ijfmr.2024.v06i03.21913
Short DOI https://doi.org/gtxrn6
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