The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B4-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2020, 307–312, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-307-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2020, 307–312, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-307-2020

  25 Aug 2020

25 Aug 2020

DEFINITION OF A METHODOLOGY TO DERIVE ROAD NETWORK FUNCTIONAL HIERARCHY CLASSES USING CAR TRACKING DATA

A. Ajmar, E. Arco, and P. Boccardo A. Ajmar et al.
  • Politecnico di Torino – DIST, Viale Pier Andrea Mattioli, 39, Torino, Italy

Keywords: Location-based services, Floating Car Data, Vehicle Tracking, Road network hierarchy, Traffic analysis, Generalization

Abstract. Road network functional hierarchy classifies individual roads into several levels, for efficient traffic management and road network generalization purposes. Automatic and semi-automatic road network extraction methods exist, but the generated products normally lack information on its functional hierarchy. This paper presents a methodology for automatically retrieve functional hierarchy for an OpenStreetMap derived road network from Floating Car Data, obtaining evenly distributed (e.g. for generalization purposes) or dynamic (e.g. to take into account differences in traffic volumes in different moments of the day) classifications. Road network elements are classified in function of vehicle speed values: the class distribution generated with the proposed methodology follows a linear distribution that can be better exploited for generalization purposes. Furthermore, the methodology allows to clearly distinguish different distributions in different moments of the day and days of the week, supporting traffic management activities.