Review on Driver Fatigue Detection Technology
Publication: International Conference on Transportation Engineering 2007
Abstract
Driver fatigue is widely regarded as a causal factor in many traffic accidents. Actually, fatigue is a complex psychophysiology phenomenon whose mechanism has not been explicitly explored. A variety of psychophysiology parameters have been used in previous researches as indicators of fatigue, among them, the electroencephalography (EEG) and electrooculography (EOG) may be the most promising ones. Many detection equipments are in use all over the world, although mainly in laboratories. Meanwhile, many methods have been tried in fatigue feature extraction and pattern recognition, such as nonlinear dynamical method, neural network, and so on. However, no standard agreement and procedure has been reached. This review looks over the state of the art in fatigue detection, with the aim to direct our future studies and the development of fatigue countermeasures.
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Copyright
© 2007 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
ASCE Technical Topics:
- Artificial intelligence and machine learning
- Computer programming
- Computing in civil engineering
- Driver behavior
- Engineering fundamentals
- Equipment and machinery
- Fatigue (material)
- Infrastructure
- Material mechanics
- Material properties
- Materials engineering
- Mathematics
- Neural networks
- Nonlinear analysis
- Nonlinear response
- Parameters (statistics)
- Statistics
- Structural analysis
- Structural behavior
- Structural engineering
- Traffic accidents
- Traffic engineering
- Traffic management
- Transportation engineering
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