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Related Concept Videos

Errors in Global Positioning System01:26

Errors in Global Positioning System

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Related Experiment Videos

Integrated LiDAR-Based Localization Correction Using a Dedicated Support Sign for Autonomous Vehicles.

Yuseung Oh1, Seungyeon Jang1, Ilseung Yoon2

  • 1Department of Highway and Transportation Research, Korea Institute of Civil Engineering and Building Technology, Goyang-si 10223, Republic of Korea.

Sensors (Basel, Switzerland)
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a dedicated sign and LiDAR-based method to improve vehicle localization accuracy in tunnels. The system significantly reduces errors compared to traditional Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) methods.

Keywords:
GNSS-degraded tunnel sectionLiDARautonomous vehiclededicated support signlocalization correctionpoint cloud registration

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Area of Science:

  • Autonomous Driving Systems
  • Robotics and Computer Vision
  • Geospatial Navigation Technologies

Background:

  • Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) based vehicle localization suffers from significant error accumulation in tunnels due to signal degradation.
  • Lane-level decision-making and path-following stability are compromised by inaccurate localization in GNSS-denied environments.

Purpose of the Study:

  • To propose a novel LiDAR-based localization support system using dedicated signs for enhanced accuracy in tunnels.
  • To develop a point-cloud-registration algorithm for real-time correction of localization errors.

Main Methods:

  • A dedicated localization support sign was designed and installed in a tunnel environment.
  • A PointPillars-based detector identified the dedicated sign.
  • Point cloud registration to a pre-built reference map estimated a rigid correction transform for online localization refinement.

Main Results:

  • The proposed pipeline demonstrated a substantial reduction in localization error post-sign recognition compared to a GNSS/INS-only baseline.
  • The dedicated sign provided more stable corrections than natural tunnel structures within the same registration pipeline.
  • LiDAR-based localization effectively suppressed drift in GNSS-degraded tunnel sections.

Conclusions:

  • The developed dedicated sign and LiDAR-based pipeline offer a robust solution for stable vehicle localization in tunnels.
  • This approach significantly improves localization accuracy and stability, crucial for autonomous driving functions in challenging environments.
  • The findings highlight the potential of targeted infrastructure and advanced sensor fusion for reliable navigation where GNSS is unreliable.