Predicting driver drowsiness using vehicle measures: Recent insights and future challenges
Driver drowsiness is a significant contributing factor to road crashes. One approach to tackling this issue is to develop technological countermeasures for detecting driver drowsiness, so that a driver can be warned before a crash occurs. The goal of this review is to assess, given the current state of knowledge, whether vehicle measures can be used to reliably predict drowsiness in real time. Several behavioral experiments have shown that drowsiness can have a serious impact on driving performance in controlled, experimental settings. However, most of those studies have investigated simple functions of performance (such as standard deviation of lane position) and results are often reported as averages across drivers, and across time. Further research is necessary to examine more complex functions, as well as individual differences between drivers. A successful countermeasure for predicting driver drowsiness will probably require the setting of multiple criteria, and the use of multiple measures.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/1800052
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Supplemental Notes:
- Abstract reprinted with permission from Elsevier
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Authors:
- Liu, Charles C
- Hosking, Simon G
- Lenne, Michael G
- Publication Date: 2009-8
Language
- English
Media Info
- Media Type: Print
- Features: References; Tables;
- Pagination: pp 239-245
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Serial:
- Journal of Safety Research
- Volume: 40
- Issue Number: 4
- Publisher: Elsevier
- ISSN: 0022-4375
- Serial URL: http://www.sciencedirect.com/science/journal/00224375
Subject/Index Terms
- TRT Terms: Behavior; Driver information systems; Drivers; Drowsiness; Fatigue (Physiological condition); Literature reviews; Real time information; Warning systems
- Subject Areas: Highways; Safety and Human Factors; I83: Accidents and the Human Factor;
Filing Info
- Accession Number: 01144667
- Record Type: Publication
- Files: TRIS
- Created Date: Nov 17 2009 2:59PM