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Automating the Process of Traffic Orientation Through Mobile Devices and Ontologies

Author

Listed:
  • Iancu, Bogdan
  • Zamfiroiu, Alin

Abstract

Mobile devices are used in all activities undertaken by users and 90% of them have used at least once a mobile device to search for local information navigation and acted on the basis of data. In this material is presented the use of mobile applications for traffic navigation or assistance and how they can contribute to the automation of orientation in traffic through traffic signs. Traffic signs around the globe are very different, even if some countries ratified conventions or adopted common specifications. In addition to that, a part of traffic signs differ from country to country even if they have the same road signal convention. This paper work aims to establish a global knowledge base with traffic signs and traffic rules dictated by them. In this way when a driver travels in foreign countries by car he can be helped by the mobile device in order to recognize the traffic signs. The ontology design is made by using Protégé software together with an RDF/RDFS approach. It uses a class hierarchy with classes like RoadSign and TrafficRule in the top of it. SPAQRL is the query language used to clean the knowledge base. At the beginning it will be populated with traffic signs from Romania. Ontology will be the backend of the mobile application that provides recognition of traffic signs and assists drivers from around the world in traffic navigation. In order to motivate the users to be active in the community and add new signs in the application a gamification approach is used.

Suggested Citation

  • Iancu, Bogdan & Zamfiroiu, Alin, 2015. "Automating the Process of Traffic Orientation Through Mobile Devices and Ontologies," MPRA Paper 97728, University Library of Munich, Germany, revised 2015.
  • Handle: RePEc:pra:mprapa:97728
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    File URL: https://mpra.ub.uni-muenchen.de/97728/1/MPRA_paper_97728.pdf
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    References listed on IDEAS

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    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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