Lidar for maintenance of pavement reflective markings and retroreflective signs

PI: Michael J. Olsen
Co-PI: Christopher Parrish
Others: Erzhuo Che, Jaehoon Jung
Year: 2016-2018

Pavement markings and signs are important traffic control device, used to guide and regulate traffic movement through visual information presented to motorists. Signs and markings are made with retroreflective materials to enhance visibility for motorists, particularly at night. Retroreflectivity evaluation of the extensive highway network for maintenance and asset management purposes is a critical, yet challenging task for Oregon DOT. Visual evaluation can often be subjective and inconsistent while field measurement techniques can be time-consuming and dangerous. This project investigated the effectiveness of evaluating pavement marking and sign retroreflectivity with mobile lidar data. Mobile lidar datasets (pointclouds) can be used to extract quantitative, accurate estimates of retroreflectivity for pavement markings, providing a safe, cost-effective, and reliable method of performing the required evaluation.

ODOT currently tracks several metrics for compliance of pavement markings, including appearance and retroreflectivity. The Maintenance Section of ODOT uses a van, which travels the state every summer, to capture retroreflectivity values on lane markings, which are analyzed and used in creating a plan of action for maintenance (e.g., vendor replacement if covered under warranty, or in house or contracted maintenance). Unfortunately, issues arise due to the timing and frequency of the data acquisition. Often, individual hand-held reflectometer readings are required after winter months to recheck compliance, which may be risky (roadside) and staff time intensive. Sign retroreflectivity evaluations suffer from similar limitations and are more cumbersome for crews to perform the retroreflectivity measurements.

To this end, SPR799 has the following research objectives:

  • Develop a model for retroreflectivity and radiometric calibration for ODOT’s mobile lidar system.
  • Generate a set of quality control metrics for pavement marking and sign retroreflectivity based on information derived from mobile lidar data
  • Establish procedures for creating GIS data layers from the output of the above steps to support decision making by supervisors and integrate analysis results into ODOT’s overall workflows.


Result of automatic pavement marking extraction:

 

Correlation between intensity and retroreflectivity values:

 

The pavement condition maps generated in ArcGIS using mobile lidar data:

 

Reports:

  • Olsen, M. J., Parrish, C. E., Che, E., Jung, J., & Greenwood, J. (2018). Lidar for Maintenance of Pavement Reflective Markings and Retroreflective Signs: Vol. I Reflective Pavement Markings (No. FHWA-OR-RD-19-01).
  • Olsen, M. J., Parrish, C. E., Che, E., Jung, J., & Greenwood, J. (2018). LIDAR for Maintenance of Pavement Reflective Markings and Retroreflective Signs Vol. II: Retroflective Signs(No. FHWA-OR-RD-19-03).

Other Publications:

  • Che, E., Olsen, M.J., Parrish, C.E., Jung, J. (2019). Pavement Marking Reflectivity Evaluation Through Radiometric Calibration of The Leica P40 Terrestrial Laser Scanner. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. (In Press)
  • Che, E., Olsen, M.J., Parrish, C.E., Jung, J. (2019). Pavement Marking Retroreflectivity Estimation and Evaluation using Mobile Lidar Data. Photogrammetric Engineering & Remote Sensing, 85(8), 29-39. (In Press)
  • Jung, J., Che, E., Olsen, M. J., & Parrish, C. (2019). Efficient and robust lane marking extraction from mobile lidar point clouds. ISPRS Journal of Photogrammetry and Remote Sensing, 147, 1-18.
  • Che, E., & Olsen, M. J. (2019). An Efficient Framework for Mobile Lidar Trajectory Reconstruction and Mo-norvana Segmentation. Remote Sensing, 11(7), 836.
  • Che, E., Jung, J., & Olsen, M. J. (2019). Object Recognition, Segmentation, and Classification of Mobile Laser Scanning Point Clouds: A State of the Art Review. Sensors, 19(4), 810.