Driver Inattention Monitoring System for Intelligent Vehicles: A Review

Kumamoto University

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Abstract

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…

Citation impact

697
total citations
FWCI
30.18
Percentile
100%
References
105
Citations per year

Authors

4

Topics & keywords

Keywords
  • Distraction
  • Intelligent transportation system
  • Computer science
  • Advanced driver assistance systems
  • Engineering
  • Risk analysis (engineering)
  • Artificial intelligence
  • Transport engineering
UN Sustainable Development Goals
  • Good health and well-being
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