Automated Identification and Extraction of Horizontal Curve Information from Geographic Information System Roadway Maps

Roadway horizontal alignment has long been recognized as one of the most significant contributing factors to lane departure crashes. Knowledge of the location and geometric information of horizontal curves can greatly facilitate the development of appropriate countermeasures. When curve information is unavailable, obtaining curve data in a cost-effective way is of great interest to practitioners and researchers. To date, many approaches have been developed to extract curve information from commercial satellite imagery, Global Positioning System survey data, laser-scanning data, and AutoCAD digital maps. As geographic information system (GIS) roadway maps become more accessible and more widely used, they become another cost-effective source for extraction of curve data. This paper presents a fully automated method for the extraction of horizontal curve data from GIS roadway maps. A specific curve data–extraction algorithm was developed and implemented as a customized add-in tool in ArcMap. With this tool, horizontal curves could be automatically identified from GIS roadway maps. The length, radius, and central angle of the curves were also computed automatically. The only input parameter of the proposed algorithm was calibrated to have the least curve identification errors. Finally, algorithm validation was conducted through a comparison of the algorithm-extracted curve data with the ground truth curve data for 76 curves that were obtained from Bing aerial maps. The validation results indicated that the proposed algorithm was very effective and that it identified completely 96.7% of curves and computed accurately their geometric information.

• Record URL:
  https://doi.org/10.3141/2291-10
• Summary URL:
  http://scholar.google.com/scholar_lookup?title=Automated+Identification+and+Extraction+of+Horizontal+Curve+Information+from+Geographic+Information+System+Roadway+Maps&author=Z.+Li&author=M.+Chitturi&author=A.+Bill&author=D.+Noyce&publication_year=2012
• Availability:
  • Find a library where document is available. Order URL: http://www.trb.org/Main/Blurbs/168380.aspx
• Authors:
  • Li, Zhixia
  • Chitturi, Madhav V
  • Bill, Andrea R
  • Noyce, David A
• Publication Date: 2012

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References;
• Pagination: pp 80-92
• Monograph Title: Information Systems, Geographic Information Systems, and Advanced Computing 2012
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Issue Number: 2291
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Algorithms; Automatic data collection systems; Detection and identification; Geographic information systems; Geometric design; Highway curves; Location; Maps; Ran off road crashes
• Uncontrolled Terms: Data extraction; Horizontal alignment
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I82: Accidents and Transport Infrastructure;

Filing Info

• Accession Number: 01468758
• Record Type: Publication
• ISBN: 9780309223355
• Report/Paper Numbers: 12-3971
• Files: TRIS, TRB, ATRI
• Created Date: Jan 10 2013 8:38AM