Title: Real-time non-intrusive monitoring and prediction of driver distraction

Authors: Laith Dababneh; Alhossein Mostafa Sharaf; Moustafa El-Gindy

Addresses: Faculty of Engineering and Applied Science, The University of Ontario Institute of Technology (UOIT), 2000 Simcoe Street North, Oshawa, ON L1H 7K4, Canada ' Military Technical College, Egyptian Armed Forces, Cairo, Egypt ' Faculty of Engineering and Applied Science, The University of Ontario Institute of Technology (UOIT), 2000 Simcoe Street North, Oshawa, ON L1H 7K4, Canada

Abstract: This paper presents a non-intrusive algorithm for monitoring and predicting driver vigilance in real time. The proposed technique is applied to a truck driving simulator by monitoring the driver response through steering wheel and accelerator pedal. The simulation results of the truck simulator are validated with a commercial TruckSim® software using identical parameters of a given tractor semitrailer during similar driving conditions. Several distraction indicators are proposed in order to predict the driver distraction, namely the jerk profile, spikiness index and the rate of change for both the steering wheel angle and the accelerator pedal position. The results of several driving experiments emphasise the effectiveness of using steering wheel rate to estimate driver distraction. Moreover, in comparison to other techniques for predicting driver vigilance, the presented work requires low computational power and has a great potential for developing a real-time simple system that can be affordable and reliable.

Keywords: driver vigilance; driver distraction; distraction prediction; vigilance monitoring; driver alert systems; crash avoidance; collision avoidance; real-time monitoring; non-intrusive monitoring; truck driving simulation; driver response; steering wheel; accelerator pedal; tractor semitrailer; jerk profile; spikiness index; change rate.

DOI: 10.1504/IJVSMT.2016.080865

International Journal of Vehicle Systems Modelling and Testing, 2016 Vol.11 No.3, pp.193 - 216

Received: 15 Jun 2016
Accepted: 15 Jul 2016

Published online: 05 Dec 2016 *

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