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The project aims to focus on improving object detection and safety measures for autonomous vehicles by combining LiDAR and camera data. The main goal is to increase object detection accuracy and resilience by combining LiDAR data with the advanced object detection model YOLOv5. The system detects objects, recognizes and tracks cars, and uses a simple depth estimation technique based on bounding box width to determine how far away vehicles stand. To provide more accurate object localization in 3D space, bounding boxes are constructed around identified objects, and the related depth information is computed using the LiDAR data. A safety function that improves the situational awareness of the autonomous vehicle by generating an audio alert when a vehicle is spotted too close is also included in the system.

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Object Detection Using Camera and LiDAR Sensors in Autonomous Vehicles

  • 会议论文

  • 发表日期：

    2026年

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  • Prerana Savant,
  • V. S. Nandana,
  • Vaishnavi Harlapur,
  • Vidhi Agarwal,
  • Jyoti Devaji Patil

摘要

The project aims to focus on improving object detection and safety measures for autonomous vehicles by combining LiDAR and camera data. The main goal is to increase object detection accuracy and resilience by combining LiDAR data with the advanced object detection model YOLOv5. The system detects objects, recognizes and tracks cars, and uses a simple depth estimation technique based on bounding box width to determine how far away vehicles stand. To provide more accurate object localization in 3D space, bounding boxes are constructed around identified objects, and the related depth information is computed using the LiDAR data. A safety function that improves the situational awareness of the autonomous vehicle by generating an audio alert when a vehicle is spotted too close is also included in the system.