An Efficient Approach to Detect Driver Distraction during Mobile Phone Usage

Sawhney, Medha and Acharya, Vasundhara and Prakasha, Krishna (2018) An Efficient Approach to Detect Driver Distraction during Mobile Phone Usage. International Journal of Engineering and Technology(UAE), 7 (4.41). pp. 86-90. ISSN 2227-524X

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Abstract

A distracted driver is an invitation to a fatal vehicle accident. People lose their lives every day due to distracted driving and using mobile phones while driving is one of the primary reasons behind road accidents. Hence, detection of mobile phone usage to alert the driver or for an autonomous system to take over becomes extremely important. In an attempt to solve this issue of distracted driving, the authors proposed a Convolution Neural Network (CNN) based model to detect mobile phone usage by the driver. The proposed work presents not only a practical solution to the problem but also a comparison between traditional approaches (Support Vector Machine with HOG) and a CNN based model. The traditional methods are both implemented and tested by the authors. The presented model performs input segmentation to achieve an efficient accuracy of 97%. Deep learning was found to be the best solution to detect driver distraction while on a call accurately

Item Type: Article
Uncontrolled Keywords: Convolutional Neural Network; Distracted Driver detection; Mobile phone usage of driver; Image classification; Object detection.
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Depositing User: MIT Library
Date Deposited: 09 Jan 2019 05:36
Last Modified: 09 Jan 2019 05:36
URI: http://eprints.manipal.edu/id/eprint/152771

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