Use of “Big Data” and Automated Valuation Models to expedite Right-of-Way Acquisition processes within the Federal-aid program across the nation

The purpose of this research is to compare traditional valuations / appraisals prepared for two completed state department of transportation (DOT) right-of-way acquisition projects in each of three states (Georgia, North Carolina, and Ohio) against the selected automated valuation models (AVMs) valuations of those same properties. The valuations will include estimates for the whole property, and the land unit value conclusions. This research project will result in a report that will inform Federal Highway Administration (FHWA) and its partners / stakeholder agencies about how the use of AVMs may be applicable and appropriate for Federal-aid highway program use.

Language

• English

Project

• Status: Active
• Funding: $204551
• Contract Numbers:

  HEPR210005PR; 693JJ321F000211

• Sponsor Organizations:

  Federal Highway Administration

  Office of Planning, Environment and Realty (HEP)
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Managing Organizations:

  Federal Highway Administration

  Office of Planning, Environment and Realty (HEP)
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Project Managers:

  Feldman, Arnold

• Performing Organizations:

  Cambridge Systematics, Incorporated

  150 Cambridge Park Drive, Suite 4000
  Cambridge, MA  United States  02140-2369
• Start Date: 20210713
• Expected Completion Date: 20221212
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Automation; Data analysis; Right of way (Land); Valuation
• Identifier Terms: Georgia Department of Transportation; North Carolina Department of Transportation; Ohio Department of Transportation
• Subject Areas: Data and Information Technology; Finance; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01835166
• Record Type: Research project
• Source Agency: Federal Highway Administration
• Contract Numbers: HEPR210005PR; 693JJ321F000211
• Files: RIP, USDOT
• Created Date: Feb 1 2022 10:39AM