With the wide application of GPS-enabled electronic devices, huge amounts of positional information data have been accumulated, so that it's critical to discover inherent knowledge from such massive data. In this paper, we address this topic by proposing two issues, including how to discover the underpasses for pedestrians to cross the roads, and how to discover the tunnels providing passageways for vehicles. Subsequently, we propose a three-step framework to deal with the issues, including an incremental clustering phase, a sub-trajectory detecting phase and a cluster filtering phase. Experiments upon real-life data sets demonstrate the effectiveness and efficiency of the proposed framework.
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