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Journal Article

Citation

Kaufmann C, Frühwirth M, Messerschmidt D, Moser M, Eichberger A, Arefnezhad S. Trans. Transp. Sci. 2020; 11(2): 51-63.

Copyright

(Copyright © 2020, Walter de Gruyter)

DOI

10.5507/tots.2020.011

PMID

unavailable

Abstract

The development of automated driving is an ongoing process; nonetheless, certain problems remain unresolved. One of them is the question when the automated vehicle control system should hand over the control to a human driver and whether this can be done in a safe way. What happens if a driver is not ready to take over? Can the system somehow estimate the status of the driver? The WACHsens simulator study was designed with the aim to gain more knowledge about when and how drivers are getting sleepy with special focus on automated driving.The overall goal of the project was to merge data from vegetative vigilance, camera observation and driving behaviour. This article describes the process of the driving behaviour observation and the evaluation of the data collected during the observation.

An enhanced observation scheme made it possible to determine, at any point in time of the 30 minutes drives, in which posture the test person is and in what degree of drowsiness the test person is. It is based on the variables and scales which have been used in other studies such as ORD (Observer Rating of Drowsiness) and ORS (Observer Rated Sleepiness). They were linked to the observation method of the Vienna driving test to allow continuous observation.

197 simulator test drives from 50 test persons were analyzed by the observers. Four different scenarios were evaluated for all test subjects: tired/manual, tired/automatic, rested/manual, and rested/automatic. The aim of the observation analysis was to investigate differences in body movements and activities according to personal characteristics (age, gender, driving experience, experience with assistance systems) and regarding the different scenarios.

The categorization of the drowsiness level of the test persons by the observers corresponds very well with the subjective assessment of the test subjects (measured by the Karolinska sleepiness scale KSS). A comparison of the different scenarios shows that most of the signs of sleepiness or situations in which the test subjects fell asleep were observed during the tired/automated trips. But even during the rested/automated drive over 40% of the test persons showed signs of tiredness, roughly the same number actually fell asleep as in the tired/manual drive. No significant differences between the personal characteristics (gender, age, and experience with assistance systems) regarding the number of body movements (change of position and activities) or sleepiness levels could be found.

A significant difference was found between the different scenarios and the comparisons between the tired/rested trips and the manual/automated trips regarding the moment in which the test persons showed first signs of tiredness. During the automated trips and/or if the test subjects showed signs of progressing weariness, the first signs of tiredness were registered significantly earlier than during the trips in which the test subjects drove manually and/or were rested.

The results show that the mode of operation - manual or automated driving - impacts the time course and level of sleepiness while driving. This sheds light on the importance to carefully evaluate driving automation systems that assume a driver as emergency fallback. Further research is recommended to investigate safe modes of control hand over in automated driving.


Language: en

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