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Detection Of Lane And Speed Breaker Using Machine Learning Algorithm

  • Unique Paper ID: 164908
  • Volume: 10
  • Issue: 12
  • PageNo: 1751-1754
  • 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 analyse 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
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  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 1751-1754

Detection Of Lane And Speed Breaker Using Machine Learning Algorithm

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