Ahmed Kharrat
ABSTRACT
Managing and mining data derived from moving objects is becoming an important issue in the last years. In this paper, we are interested in mining trajectories of moving objects such as vehicles in the road network. We propose a method for dense route discovery by clustering similar road sections according to both traffic and location in each time period. The traffic estimation is based on the collected spatiotemporal trajectories. We also propose a characterization approach of the temporal evolution of dense routes by a graph of route connection over consecutive time periods. This graph is labelled by a degree of evolution. We have implemented and tested the proposed algorithms, which have shown their effectiveness and efficiency.
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Index Terms
- Caractérisation de la densité de trafic et de son évolution à partir de trajectoires d'objets mobiles
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