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Sensor Fusion Method for Object Detection and Distance Estimation in Assisted Driving Applications.

Stefano Favelli1,2, Meng Xie2, Andrea Tonoli1,2

  • 1Center for Automotive Research and Sustainable Mobility (CARS@PoliTO), Politecnico di Torino, 10129 Torino, Italy.

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Summary

This study introduces an open-source framework for fusing camera, radar, and LiDAR data to accurately estimate distances to road objects. This enhances Advanced Driving Assistance Systems (ADAS) for safer autonomous driving.

Keywords:
ADASLiDARROScameraenvironment perceptionobject detectionsensor fusion

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Area of Science:

  • Computer Vision
  • Robotics
  • Sensor Fusion

Background:

  • Real-time sensor data fusion is critical for autonomous and assisted driving systems.
  • Accurate object classification and relative position estimation are essential for high-level controllers.

Purpose of the Study:

  • To present an open-source framework for estimating distances to road objects using fused camera, radar, and LiDAR data.
  • To enable Advanced Driving Assistance Systems (ADAS) with enhanced environmental perception for speed planning and obstacle avoidance.

Main Methods:

  • A low-level sensor fusion approach using geometrical projection to map 3D point clouds to 2D camera images.
  • Integration of a Yolov7 detector for object identification and distance estimation.
  • An open-source pipeline in ROS including sensor calibration, point cloud processing, and 3D-to-2D transformation.

Main Results:

  • The framework successfully estimates the distance of detected road objects with good accuracy.
  • The pipeline achieves real-time performance at 5 Hz on an embedded Nvidia Jetson AGX.
  • Demonstrated effectiveness in real-world urban driving scenarios using commercial hardware.

Conclusions:

  • The proposed framework offers a flexible and resource-efficient method for data association from automotive sensors.
  • It provides a promising solution for improving environment perception capabilities in assisted driving applications.
  • The system enables accurate object identification and distance estimation, crucial for ADAS functionality.