Detection of Lane and Speed Breaker Warning System for Autonomous Vehicles using Machine Learning Algorithm

Authors: Prof. N. L. Bhale, Mayur Bhamare, Vikas Darade, Neha Nisal, Shital Kutke

Country: India

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Abstract: With the rapid advancement of autonomous vehicle technologies, ensuring the safety of these vehicles on roads has become a paramount concern. One of the critical aspects of safe autonomous driving is the accurate detection of lanes and potential road hazards, such as speed breakers. In this study, we propose a Lane and Speed Breaker Warning System (LSBWS) that employs machine learning algorithms to enhance the perception capabilities of autonomous vehicles.The LSBWS utilizes a combination of computer vision and machine learning techniques to detect and analyze road lanes and speed breakers in real-time. The system utilizes a camera sensor to capture the road scene ahead and then employs image processing algorithms to identify lane markings and speed breakers. A convolutional neural network (CNN) is employed to accurately detect and classify these features within the captured images.

Keywords: Lane detection, Speed breaker detection, Autonomous vehicles, Machine learning algorithms, Convolutional neural network, Road safety.

Paper Id: 230671

Published On: 2024-05-28

Published In: Volume 12, Issue 3, May-June 2024

Cite This: Detection of Lane and Speed Breaker Warning System for Autonomous Vehicles using Machine Learning Algorithm - Prof. N. L. Bhale, Mayur Bhamare, Vikas Darade, Neha Nisal, Shital Kutke - IJIRMPS Volume 12, Issue 3, May-June 2024.

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