Collecting and managing network-matched trajectories of moving objects in databases

Abstract

To track network-matched trajectories of moving objects is important in a lot of applications such as trajectory-based traffic-flow analysis and trajectory data mining. However, current network-based location tracking methods for moving objects need digital maps installed at the moving object side, which is not realistic in a lot of circumstances. In this paper, we propose a new moving objects database framework, Euclidean-batch-sampling and Network-matched-trajectory based Moving Objects Database (EuNetMOD) model, to support network-matched trajectory tracking without digital maps installed at the moving object side. © 2011 Springer-Verlag Berlin Heidelberg.