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Authors: Ahmed Kharrat 1 ; Karine Zeitouni 1 ; Iulian Sandu-Popa 1 and Sami Faiz 2

Affiliations: 1 University of Versailles, France ; 2 Ecole Nationale D’ingénieurs de Tunis, Tunisia

Keyword(s): Moving object databases, Spatiotemporal data mining, Similarity, Clustering, Density analysis.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Clustering and Classification Methods ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

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 discovering dense routes 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 connecting dense routes over consecutive time periods. This graph is labeled by a degree of evolution. We have implemented and tested the proposed algorithms, which have shown their effectiveness and efficiency.

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Paper citation in several formats:
Kharrat, A.; Zeitouni, K.; Sandu-Popa, I. and Faiz, S. (2009). CHARACTERIZING THE TRAFFIC DENSITY AND ITS EVOLUTION THROUGH MOVING OBJECT TRAJECTORIES. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2009) - KDIR; ISBN 978-989-674-011-5; ISSN 2184-3228, SciTePress, pages 319-322. DOI: 10.5220/0002309403190322

@conference{kdir09,
author={Ahmed Kharrat. and Karine Zeitouni. and Iulian Sandu{-}Popa. and Sami Faiz.},
title={CHARACTERIZING THE TRAFFIC DENSITY AND ITS EVOLUTION THROUGH MOVING OBJECT TRAJECTORIES},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2009) - KDIR},
year={2009},
pages={319-322},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002309403190322},
isbn={978-989-674-011-5},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2009) - KDIR
TI - CHARACTERIZING THE TRAFFIC DENSITY AND ITS EVOLUTION THROUGH MOVING OBJECT TRAJECTORIES
SN - 978-989-674-011-5
IS - 2184-3228
AU - Kharrat, A.
AU - Zeitouni, K.
AU - Sandu-Popa, I.
AU - Faiz, S.
PY - 2009
SP - 319
EP - 322
DO - 10.5220/0002309403190322
PB - SciTePress

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