Arvee: Automatic Road Geometry Extraction System for Mobile Mapping

Land-based mobile mapping systems have yielded an enormous time saving in road networks and their surrounding utilities survey. However, the manual extraction of the road information from the mobile mapping data is still a time-consuming task. This paper presents ARVEE (Automated Road Geometry Vectors Extraction Engine)), a robust automatic road geometry extraction system developed at the University of Calgary. The extracted road information includes the 3D lane lines, road edges as well as lane lines attributes. There are three innovations in this work. First, all the visible lane lines in the georeferenced image sequences are extracted, instead of only extracting the central lane line or the nearby lane line pair. Second, the lane line types are recognized, so the output is a functional description of the road geometry. Third, the output is the absolute-georeferenced model of lane lines in mapping coordinates, and is compatible to the GIS databases. Four steps are included: First, extract the linear features in each image. Second, the linear features are filtered and grouped into lane line segments (LLS). Geometric and radiometric characteristics are extracted for each LLS. Third, a Multiple-Hypothesis Analysis (MHA) method is used to link the LLSs into long lane lines 3D model. Finally, each lane line is classified into a lane line type based on the synthetic analysis of the included LLSs’ features. The system has been tested on large number of VISATTM mobile mapping data. The experiments on massive real MMS data sets demonstrate that ARVEE can deliver accurate and robust 3D continuous functional road geometry model. Full automatic processing result from ARVEE can replace most of the human efforts in road geometry modelling. * Corresponding author.