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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

Predictive Analysis of Alertness Related Features for Driver Drowsiness Detection

verfasst von : Sachin Kumar, Anushtha Kalia, Arjun Sharma

Erschienen in: Intelligent Systems Design and Applications

Verlag: Springer International Publishing

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Abstract

Drowsiness during driving is a major cause of accidents of drivers which has socio-economic and psychological impact on the affected person. In Intelligent Transportation Systems (ITS), the detection of the drowsy and alert state of the driver is an interesting research problem. This paper proposed a novel method to detect the drowsy state of the driver based on three parameters, namely physiological, environmental and vehicular. The undertaken model proposes a simplistic approach and achieves comparable results to the state of the art with an ROC score of 81.28 and also elaborates on the specificity and sensitivity metrics.

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Vorheriges Kapitel Automated Detection of Diabetic Retinopathy Using Weighted Support Vector Machines
Nächstes Kapitel Association Rules Transformation for Knowledge Integration and Warehousing
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Metadaten
Titel
Predictive Analysis of Alertness Related Features for Driver Drowsiness Detection
verfasst von
Sachin Kumar
Anushtha Kalia
Arjun Sharma
Copyright-Jahr
2018
Buch
Intelligent Systems Design and Applications

Print ISBN: 978-3-319-76347-7

Electronic ISBN: 978-3-319-76348-4

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-76348-4_36