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Lane Marking Detection and Reconstruction with Line-Scan Imaging Data.

Lin Li1, Wenting Luo2, Kelvin C P Wang3

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This study introduces a new method for automated lane marking detection using laser images, improving road condition evaluation for autonomous driving and pavement surveys.

Keywords:
image binarizationlane marking detectionlane marking reconstructionlaser sensorline scan camerasupport vector machine (SVM)

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Area of Science:

  • Road infrastructure monitoring
  • Computer vision for autonomous systems
  • Pavement engineering

Background:

  • Lane marking detection is vital for autonomous driving and pavement surveys.
  • Existing methods primarily use camera vision, with limited use of laser imaging for road condition assessment.
  • High-resolution laser images offer potential for detailed lane marking analysis.

Purpose of the Study:

  • To present a novel methodology for automated lane marking identification and reconstruction using laser images.
  • To enhance road condition evaluation by accurately detecting and localizing lane markings.
  • To develop a robust system for processing laser-based road data.

Main Methods:

  • Acquisition of laser images using a digital highway data vehicle (DHDV).
  • Four-phase methodology: multi-box segmentation thresholding for binarization, marching squares algorithm for candidate detection, linear SVM for false positive elimination, and geometric reconstruction of damaged/dashed markings.
  • Validation through a case study.

Main Results:

  • The novel methodology demonstrates robust performance in image binarization and lane marking localization.
  • Successful identification and reconstruction of continuous lane markings from laser data.
  • The approach effectively handles damaged and dashed lane marking segments.

Conclusions:

  • The developed strategy provides a robust solution for automated lane marking analysis using laser imagery.
  • This technique is highly beneficial for road lane-based pavement condition evaluations, including rutting and crack assessments.
  • The study advances the application of laser imaging in intelligent transportation systems and road maintenance.