A Remote Sensing and GIS-Enabled Highway Asset Management System

The objective of this project is to validate the use of commercial remote sensing and spatial information (CRS&SI) technologies, including emerging 3D line laser imaging technology, mobile LiDAR, image processing algorithms, and global positioning system/geographic information system (GPS/GIS) technologies, to improve the transportation asset data collection, condition assessment, and management. Traffic sign asset and pavement asset were used for validation. For sign asset, an enhanced procedure for sign inventory was proposed; a large-scale case study was conducted on I-285; a preliminary study has been done to evaluate sign retroreflectivity using mobile LiDAR; and a prototype GIS-based sign management system was developed. The research results show that using the automatic image-processing-based sign detection and recognition algorithms and the LiDAR-based sign detection can improve the current time-consuming image-based traffic sign data collection process. For pavement asset, comprehensive validation has been done on network-level rutting measurement and isolated rutting detection; an innovative method was developed to evaluate the performance of an automatic crack detection algorithm; comprehensive lab and field tests have been done to validate the capability of 3D laser data for asphalt pavement crack detection; and a crack propagation study has also been done using the long-term monitoring data. Based on the research results, conclusions were made and recommendations were suggested.


  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Appendices; Figures; Maps; Photos; References; Tables;
  • Pagination: 463p

Subject/Index Terms

Filing Info

  • Accession Number: 01599221
  • Record Type: Publication
  • Report/Paper Numbers: GA-15-1008
  • Contract Numbers: RP 10-08
  • Created Date: May 10 2016 2:39PM