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ROCA – An ArcGIS toolbox for road alignment identification and horizontal curve radii computation

Author

Listed:
  • Michal Bíl
  • Richard Andrášik
  • Jiří Sedoník
  • Vojtěch Cícha

Abstract

We present the ROCA (ROad Curvature Analyst) software, in the form of an ESRI ArcGIS Toolbox, intended for vector line data processing. The software segments road network data into tangents and horizontal curves. Horizontal curve radii and azimuth of tangents are then automatically computed. Simultaneously, additional frequently used road section characteristics are calculated, such as the sinuosity of a road section (detour ratio), the number of turns along an individual road section and the average cumulative angle for a road section. The identification of curves is based on the naïve Bayes classifier and users are allowed to prepare their own training data files. We applied ROCA software to secondary roads within the Czech road network (9,980 km). The data processing took less than ten minutes. Approximately 43% of the road network in question consists of 42,752 horizontal curves. The ROCA software outperforms other existing automatic methods by 26% with respect to the percentage of correctly identified curves. The segmented secondary roads within the Czech road network can be viewed on the roca.cdvgis.cz/czechia web-map application. We combined data on road geometry with road crashes database to develop the crash modification factors for horizontal curves with various radii. We determined that horizontal curves with radii of 50 m are approximately 3.7 times more hazardous than horizontal curves with radii accounting for 1000 m. ROCA software can be freely downloaded for noncommercial use from https://roca.cdvinfo.cz/ website.

Suggested Citation

  • Michal Bíl & Richard Andrášik & Jiří Sedoník & Vojtěch Cícha, 2018. "ROCA – An ArcGIS toolbox for road alignment identification and horizontal curve radii computation," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-15, December.
  • Handle: RePEc:plo:pone00:0208407
    DOI: 10.1371/journal.pone.0208407
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