Ontological and Machine Learning Approaches for Managing Driving Context in Intelligent Transportation

Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif

Abstract

In this paper, a novel approach of managing driving context information in smart transportation is presented. The driving context refers to the ensemble of parameters that make up the contexts of the environment, the vehicle and the driver. To manage this rich information, knowledge representation using ontology is used and through it, such information becomes a source of knowledge. When this context information (i.e. basically a template or model) is instantiated with actual instances of objects, we can describe any kind of driving situation. Furthermore, through ontological knowledge management, we can find the answers related to various queries of the given driving situation. A smart vehicle is equipped with machine learning functionalities that are capable of classifying any driving situation, and accord assistance to the driver or the vehicle or both to avoid accident, when necessary. This work is a contribution to the ongoing research in safe driving, and a specific application of using data from the internet of things.

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Paper Citation


in Harvard Style

Hina M., Thierry C., Soukane A. and Ramdane-Cherif A. (2017). Ontological and Machine Learning Approaches for Managing Driving Context in Intelligent Transportation.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, ISBN 978-989-758-272-1, pages 302-309. DOI: 10.5220/0006580803020309


in Bibtex Style

@conference{keod17,
author={Manolo Dulva Hina and Clement Thierry and Assia Soukane and Amar Ramdane-Cherif},
title={Ontological and Machine Learning Approaches for Managing Driving Context in Intelligent Transportation},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,},
year={2017},
pages={302-309},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006580803020309},
isbn={978-989-758-272-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,
TI - Ontological and Machine Learning Approaches for Managing Driving Context in Intelligent Transportation
SN - 978-989-758-272-1
AU - Hina M.
AU - Thierry C.
AU - Soukane A.
AU - Ramdane-Cherif A.
PY - 2017
SP - 302
EP - 309
DO - 10.5220/0006580803020309