GRADE AND CROSS SLOPE ESTIMATION FROM LIDAR-BASED SURFACE MODELS

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR (light detection and ranging) to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three-dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.

• Record URL:
  http://www.ctre.iastate.edu/mtc/reports/LIDAR_Grade.pdf
• Record URL:
  http://www.ctre.iastate.edu/reports/mrd.pdf
• 
• Supplemental Notes:
  • This report was prepared as part of the following project: Application of Advanced Remote Sensing Technology to Asset Management, co-sponsored by the Iowa Department of Transportation (CTRE Project 01-98).
• Corporate Authors:

  Midwest Transportation Consortium

  Iowa State University, 2711 South Loop Drive, Suite 4700
  Ames, IA  United States  50010-8664

  Research and Special Programs Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590

  Iowa Department of Transportation

  800 Lincoln Way
  Ames, IA  United States  50010
• Authors:
  • Souleyrette, R
  • Hallmark, S
  • Pattnaik, S
  • O'Brien, M
  • Veneziano, D
• Publication Date: 2003-10

Language

• English

Media Info

• Features: Appendices; Figures; References; Tables;
• Pagination: 76 p.

Subject/Index Terms

• TRT Terms: Asset management; Data collection; Laser radar; Methodology; Pilot studies; Remote sensing
• Uncontrolled Terms: Cross slope; Grade (Highways)
• Subject Areas: Design; Highways; Planning and Forecasting; I21: Planning of Transport Infrastructure;

Filing Info

• Accession Number: 00969853
• Record Type: Publication
• Report/Paper Numbers: MTC Project 2001-02,, Final Report
• Files: TRIS, USDOT, STATEDOT
• Created Date: Feb 11 2004 12:00AM