Journal article
Sequence Analysis of Monitored Drowsy Driving
Transportation research record, Vol.2677(8), pp.553-562
08/01/2023
DOI: 10.1177/03611981231157401
Abstract
Driver monitoring systems are growing in importance as well as capability. This paper reports on drowsy driving detection models generated from multiple sources of driver monitoring data. Behavioral (driver) data were provided by a camera-based production-type driver monitoring system manufactured by Aisin Technical Center of America (from the Aisin Group). Vehicular data were recorded from the National Advanced Driving Simulator's large-excursion motion-base driving simulator. Forty participants drove the simulator for up to 3 h after being awake for at least 16 h. Periodic measurements of drowsiness were made every 10 min using both observational ratings of drowsiness by an external rater and the self-reported Karolinska Sleepiness Scale. A novel application of sequence analysis with clustering and hidden Markov models resulted in models that tracked well with the subjective drowsiness measures. The area under Receiver Operating Characteristic curves evaluating the models ranged from 0.85 to 0.87. By allowing for many distinct patterns observed in driving sequences, the hope is that the method will offer a robust way to accommodate pattern variability that naturally occurs over time and among drivers.
Details
- Title: Subtitle
- Sequence Analysis of Monitored Drowsy Driving
- Creators
- Chris Schwarz - University of IowaJohn Gaspar - University of IowaReza Yousefian - Aisin
- Resource Type
- Journal article
- Publication Details
- Transportation research record, Vol.2677(8), pp.553-562
- Publisher
- Sage
- DOI
- 10.1177/03611981231157401
- ISSN
- 0361-1981
- eISSN
- 2169-4052
- Number of pages
- 10
- Grant note
- Aisin Technical Center of America
- Language
- English
- Date published
- 08/01/2023
- Academic Unit
- Iowa Technology Institute; Driving Safety Research Institute
- Record Identifier
- 9984627304302771
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