Modelling and Detection of Driver's Fatigue using Ontology
- URL: http://arxiv.org/abs/2208.14694v1
- Date: Wed, 31 Aug 2022 08:42:28 GMT
- Title: Modelling and Detection of Driver's Fatigue using Ontology
- Authors: Alexandre Lambert, Manolo Dulva Hina, Celine Barth, Assia Soukane and
Amar Ramdane-Cherif
- Abstract summary: Road accidents are the eight leading cause of death all over the world.
Various factors cause driver's fatigue.
Ontological knowledge and rules for driver fatigue detection are to be integrated into an intelligent system.
- Score: 60.090278944561184
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Road accidents have become the eight leading cause of death all over the
world. Lots of these accidents are due to a driver's inattention or lack of
focus, due to fatigue. Various factors cause driver's fatigue. This paper
considers all the measureable data that manifest driver's fatigue, namely those
manifested in the vehicle measureable data while driving as well as the
driver's physical and physiological data. Each of the three main factors are
further subdivided into smaller details. For example, the vehicle's data is
composed of the values obtained from the steering wheel's angle, yaw angle, the
position on the lane, and the speed and acceleration of the vehicle while
moving. Ontological knowledge and rules for driver fatigue detection are to be
integrated into an intelligent system so that on the first sign of dangerous
level of fatigue is detected, a warning notification is sent to the driver.
This work is intended to contribute to safe road driving.
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