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Architecture for Intelligent Transportation System Based in a General Traffic Ontology

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Computer and Information Science 2015

Part of the book series: Studies in Computational Intelligence ((SCI,volume 614))

Abstract

Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is that vehicles can exchange information not only among themselves but with other elements in the road infrastructure through different applications. For the success of this exchange of information, a common framework of knowledge that allows interoperability is needed. In this paper an ontology-based system to provide roadside assistance is proposed, providing drivers making decisions in different situations, taking into account information on different traffic-related elements such as routes, traffic signs, traffic regulations and weather elements.

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Acknowledgments

This work was partially supported by Research and Development on Utilization and Fundamental Technologies for Social Big Data by NICT (National Institute of Information and Communications Technology), and the Fund for Strengthening and Facilitating the National University Reformations by Ministry of Education, Culture, Sports, Science, and Technology, Japan.

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Authors and Affiliations

  1. University of Alcala. Alcalá de Henares, Madrid, Spain

    Susel Fernandez

  2. Nagoya Institute of Technology, Nagoya, Japan

    Takayuki Ito & Rafik Hadfi

Authors
  1. Susel Fernandez
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  2. Takayuki Ito
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  3. Rafik Hadfi
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Corresponding author

Correspondence to Susel Fernandez .

Editor information

Editors and Affiliations

  1. Software Engineering and Information Institute, Central Michigan University, Mount Pleasant, Michigan, USA

    Roger Lee

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© 2016 Springer International Publishing Switzerland

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Fernandez, S., Ito, T., Hadfi, R. (2016). Architecture for Intelligent Transportation System Based in a General Traffic Ontology. In: Lee, R. (eds) Computer and Information Science 2015. Studies in Computational Intelligence, vol 614. Springer, Cham. https://doi.org/10.1007/978-3-319-23467-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-23467-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23466-3

  • Online ISBN: 978-3-319-23467-0

  • eBook Packages: EngineeringEngineering (R0)

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