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Machine Learning-Assisted Cognition of Driving Context and Avoidance of Road Obstacles

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Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1222))

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Abstract

In the vehicle of the future, an intelligent vehicle should be able to recognize the driving context so as it would be able to perform the necessary actions to continue the trip up to its intended destination. Moreover, such intelligent vehicle should also be able to detect and recognize road obstacles, as it is the failure to recognize an obstacle and avoid it that often lead to road accident, normally causing human fatalities. In this paper, knowledge engineering related to the cognitive processes of driving context detection, perception, decision and optimal action related to the driving context and avoiding road obstacles. Ontology and formal specifications are used to describe such mechanism. Different supervised learning algorithms are used for cognition of driving context and in recognizing and classifying obstacles. The avoidance of obstacles is implemented using reinforcement learning. The work is validated using driving simulator in the laboratory. This work is a contribution to the ongoing research in safe driving, and the application of machine learning leading to prevention of road accidents.

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Author information

Authors and Affiliations

  1. ECE Paris School of Engineering, 37 quai de Grenelle, 75015, Paris, France

    Manolo Dulva Hina, Andrea Ortalda & Assia Soukane

  2. Université de Versailles Paris-Saclay, 10-12 Avenue de l’Europe, 78140, Velizy, France

    Amar Ramdane-Cherif

Authors
  1. Manolo Dulva Hina
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  2. Andrea Ortalda
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  3. Assia Soukane
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  4. Amar Ramdane-Cherif
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Corresponding author

Correspondence to Manolo Dulva Hina .

Editor information

Editors and Affiliations

  1. Instituto de Telecomunicações, University of Lisbon, Lisbon, Portugal

    Ana Fred

  2. Federal University of Pernambuco, Recife, Brazil

    Ana Salgado

  3. University of Madeira, Funchal, Portugal

    David Aveiro

  4. Delft University of Technology, Delft, The Netherlands

    Jan Dietz

  5. University of Coimbra, Coimbra, Portugal

    Jorge Bernardino

  6. Polytechnic Institute of Setúbal/INSTIC, Setúbal, Portugal

    Joaquim Filipe

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Hina, M.D., Ortalda, A., Soukane, A., Ramdane-Cherif, A. (2020). Machine Learning-Assisted Cognition of Driving Context and Avoidance of Road Obstacles. In: Fred, A., Salgado, A., Aveiro, D., Dietz, J., Bernardino, J., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2018. Communications in Computer and Information Science, vol 1222. Springer, Cham. https://doi.org/10.1007/978-3-030-49559-6_7

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  • DOI: https://doi.org/10.1007/978-3-030-49559-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49558-9

  • Online ISBN: 978-3-030-49559-6

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