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Virtual running model for locating road intersections using GPS trajectory data

Map construction from vehicle trajectories has been an active challenge topic due to the progress of positioning technologies and high cost of map constructions since last decades. In our work, we focus on road network generation from a massive GPS data collected from a large number of vehicles, particularly the detection of intersections which provide the connectivity information of road network. Among several methods to detect intersections, image processing, observing the distribution of GPS points, and finding the behavioral characteristics of trajectories have been widely studied. However, actual roads are in three-dimensional space and there are overpass or underpass roads that can be falsely detected as intersections. In order to solve this problem, we extend our previous algorithm, Virtual Run [16] to the Bidirectional Virtual Run algorithm to detect the split point among roads. Moreover, by reversing the Virtual Run algorithm, this new algorithm can find the joining point of roads. For the evaluation, we used about 2000 actual vehicle trajectories gathered up with taxies in three metropolitan cities - Seoul, Pusan, and Sungnam in Korea.