Predicting driver's hypovigilance on monotonous roads: literature review.
Larue, Gregoire S., Rakotonirainy, Andry, & Pettitt, Anthony N. (2010) Predicting driver's hypovigilance on monotonous roads: literature review. In 1st International Conference on Driver Distraction and Inattention, Gothenburg, Sweden.
Drivers' ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks. Particularly, highway design reduces the driving task mainly to a lane-keeping one. It contributes to hypovigilance and road crashes as drivers are often not aware that their driving behaviour is impaired. Monotony increases fatigue, however, the fatigue community has mainly focused on endogenous factors leading to fatigue such as sleep deprivation. This paper focuses on the exogenous factor monotony which contributes to hypovigilance. Objective measurements of the effects of monotonous driving conditions on the driver and the vehicle's dynamics is systematically reviewed with the aim of justifying the relevance of the need for a mathematical framework that could predict hypovigilance in real-time. Although electroencephalography (EEG) is one of the most reliable measures of vigilance, it is obtrusive. This suggests to predict from observable variables the time when the driver is hypovigilant. Outlined is a vision for future research in the modelling of driver vigilance decrement due to monotonous driving conditions. A mathematical model for predicting drivers’ hypovigilance using information like lane positioning, steering wheel movements and eye blinks is provided. Such a modelling of driver vigilance should enable the future development of an in-vehicle device that detects driver hypovigilance in advance, thus offering the potential to enhance road safety and prevent road crashes.
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|Item Type:||Conference Paper|
|Keywords:||Monotony, Fatigue, Vigilance, Driving, Hidden Markov Models|
|Subjects:||Australian and New Zealand Standard Research Classification > PSYCHOLOGY AND COGNITIVE SCIENCES (170000) > COGNITIVE SCIENCE (170200) > Computer Perception Memory and Attention (170201)|
Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > APPLIED MATHEMATICS (010200)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
|Divisions:||Current > Research Centres > Centre for Accident Research & Road Safety - Qld (CARRS-Q)|
Current > Schools > School of Curriculum
Current > QUT Faculties and Divisions > Faculty of Health
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Psychology & Counselling
|Deposited On:||29 Oct 2009 11:02|
|Last Modified:||27 Mar 2013 01:50|
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