NDLI: Real-time detection of distracted driving based on deep learning

Content Provider	IET Digital Library
Author	Tran, Duy Do, Ha Manh Sheng, Weihua Bai, He Chowdhary, Girish
Abstract	Driver distraction is a leading factor in car crashes. With a goal to reduce traffic accidents and improve transportation safety, this study proposes a driver distraction detection system which identifies various types of distractions through a camera observing the driver. An assisted driving testbed is developed for the purpose of creating realistic driving experiences and validating the distraction detection algorithms. The authors collected a dataset which consists of images of the drivers in both normal and distracted driving postures. Four deep convolutional neural networks including VGG-16, AlexNet, GoogleNet, and residual network are implemented and evaluated on an embedded graphic processing unit platform. In addition, they developed a conversational warning system that alerts the driver in real-time when he/she does not focus on the driving task. Experimental results show that the proposed approach outperforms the baseline one which has only 256 neurons in the fully-connected layers. Furthermore, the results indicate that the GoogleNet is the best model out of the four for distraction detection in the driving simulator testbed.
Starting Page	1210
Ending Page	1219
Page Count	10
ISSN	1751956X
Volume Number	12
e-ISSN	17519578
Issue Number	Issue 10, Dec (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/12/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2018.5172
Journal	IET Intelligent Transport Systems
Publisher Date	2018-07-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	AlexNet Assisted Driving Testbed Camera Car Crashes Computer Vision And Image Processing Technique Conversational Warning System Deep Convolutional Neural Network Deep Learning Distracted Driving Postures Distraction Detection Algorithm Driver Distraction Detection System Driver Information System Driving Simulator Testbed Driving Task Embedded Graphic Processing Unit Platform Fully-connected Layer GoogleNet Graphics Processing Units Image Sonsor Learning in AI Neural Computing Technique Neural Nets Object Detection Optical, Image And Video Signal Processing Real-time Detection Realistic Driving Experiences Residual Network Road Accidents Road Safety Road Traffic Traffic Accident Reduction Traffic Engineering Computing Transportation Safety VGG-16
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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