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GeoInformatica

, Volume 14, Issue 3, pp 279–305 | Cite as

Managing sensor traffic data and forecasting unusual behaviour propagation

  • Claudia Bauzer MedeirosEmail author
  • Marc Joliveau
  • Geneviève Jomier
  • Florian De Vuyst
Article

Abstract

Sensor data on traffic events have prompted a wide range of research issues, related with the so-called ITS (Intelligent Transportation Systems). Data are delivered for both static (fixed) and mobile (embedded) sensors, generating large and complex spatio-temporal series. This scenario presents several research challenges, in spatio-temporal data management and data analysis. Management issues involve, for instance, data cleaning and data fusion to support queries at distinct spatial and temporal granularities. Analysis issues include the characterization of traffic behavior for given space and/or time windows, and detection of anomalous behavior (either due to sensor malfunction, or to traffic events). This paper contributes to the solution of some of these issues through a new kind of framework to manage static sensor data. Our work is based on combining research on analytical methods to process sensor data, and data management strategies to query these data. The first aspect is geared towards supporting pattern matching. This leads to a model to study and predict unusual traffic behavior along an urban road network. The second aspect deals with spatio-temporal database issues, taking into account information produced by the model. This allows distinct granularities and modalities of analysis of sensor data in space and time. This work was conducted within a project that uses real data, with tests conducted on 1,000 sensors, during 3 years, in a large French city.

Keywords

Intelligent Transportation Systems Traffic sensor data Traffic modelling Sensor networks Time series 

Notes

Acknowledgements

This work was partially financed by CNPq (Brazil) and by the French Research Program “ACI Masse de Données 2003”. The authors thank INRETS (Laboratoire GRETIA) for providing real data and some of the problems discussed.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Claudia Bauzer Medeiros
    • 1
    Email author
  • Marc Joliveau
    • 2
  • Geneviève Jomier
    • 3
  • Florian De Vuyst
    • 4
  1. 1.ICUniversity of Campinas, UNICAMPCampinasBrazil
  2. 2.CIRRELTUniversité de MontréalMontréalCanada
  3. 3.LAMSADEUniversité Paris-DauphineParis Cedex 16France
  4. 4.Laboratoire Mathématiques Appliquées aux SystèmesEcole Centrale ParisChatenay-Malabry CedexFrance

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