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Lane-Level Map-Matching Method for Vehicle Localization Using GPS and Camera on a High-Definition Map.

Jeong Min Kang1, Tae Sung Yoon2, Euntai Kim1

  • 1Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Korea.

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|April 16, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel camera-based system for precise vehicle localization. The method achieves lane-level accuracy by integrating high-definition maps with GPS data, enhancing autonomous driving safety.

Keywords:
GNSSHD mapautonomous drivinglane detectionlocalizationmap-matching

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Area of Science:

  • Computer Vision
  • Robotics
  • Geospatial Information Systems

Background:

  • Accurate vehicle localization is critical for autonomous driving and advanced driver-assistance systems.
  • Global Navigation Satellite Systems (GNSS) alone often lack the required lane-level precision.
  • High-definition (HD) maps offer a promising avenue for enhancing localization accuracy.

Purpose of the Study:

  • To propose a novel map-based vehicle localization method using a single camera.
  • To achieve lane-level accuracy by leveraging road link information from HD maps.
  • To enhance the reliability of localization for autonomous systems.

Main Methods:

  • Image processing via inverse perspective mapping to visualize the entire road.
  • Hough transform for detecting lane lines and acquiring driving link information.
  • Iterative closest point (ICP) based map-matching to align GPS trajectories with HD maps.

Main Results:

  • The proposed method successfully achieves lane-level position accuracy.
  • Experimental validation using sophisticated GPS/inertial navigation system data confirms the findings.
  • Demonstrated robustness in estimating vehicle position by matching GPS and HD map data.

Conclusions:

  • The single-camera, map-based localization method provides lane-level accuracy.
  • This approach enhances the precision of vehicle localization beyond traditional GNSS methods.
  • The technique is suitable for improving the safety and performance of autonomous vehicles.