Driver Inattention Monitoring System for Intelligent Vehicles: A Review

In this paper, we review the state-of-the-art technologies for driver inattention monitoring, which can be classified into the following two main categories: 1) distraction and 2) fatigue. Driver inattention is a major factor in most traffic accidents. Research and development has actively been carr...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2011-06, Vol.12 (2), p.596-614
Main Authors: Yanchao Dong, Zhencheng Hu, Uchimura, K, Murayama, N
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Cameras
Computer science
control theory
systems
Distraction
Driver circuits
driver inattention
driver monitoring
Electroencephalography
Exact sciences and technology
Fatigue
Ground, air and sea transportation, marine construction
Monitoring
Road transportation and traffic
Traffic accidents & safety
Vehicles
Visualization
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Summary:In this paper, we review the state-of-the-art technologies for driver inattention monitoring, which can be classified into the following two main categories: 1) distraction and 2) fatigue. Driver inattention is a major factor in most traffic accidents. Research and development has actively been carried out for decades, with the goal of precisely determining the drivers' state of mind. In this paper, we summarize these approaches by dividing them into the following five different types of measures: 1) subjective report measures; 2) driver biological measures; 3) driver physical measures; 4) driving performance measures; and 5) hybrid measures. Among these approaches, subjective report measures and driver biological measures are not suitable under real driving conditions but could serve as some rough ground-truth indicators. The hybrid measures are believed to give more reliable solutions compared with single driver physical measures or driving performance measures, because the hybrid measures minimize the number of false alarms and maintain a high recognition rate, which promote the acceptance of the system. We also discuss some nonlinear modeling techniques commonly used in the literature.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2010.2092770