| 1. |
- Ahlström, Christer, et al.
(författare)
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Video-based observer rated sleepiness versus self-reported subjective sleepiness in real road driving
- 2015
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Ingår i: European Transport Research Review. - : Springer Science and Business Media LLC. - 1867-0717 .- 1866-8887. ; 7:4
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Tidskriftsartikel (refereegranskat)abstract
- Observer-rated sleepiness (ORS) based on video recordings of the driver’s face is often used when analysing naturalistic driving data. The aim of this study is to investigate if ORS ratings agree with subjective self-reported sleepiness (SRS).Forty raters assessed 54 video-clips showing drivers with varying levels of sleepiness. The video-clips were recorded during a field experiment focusing on driver sleepiness using the same cameras that are typically used in large-scale field studies. The weak results prompted a second test. Ten human factors researchers made pairwise comparisons of videos showing the same four participants in an alert versus a very sleepy condition. The task was simply to select the video-clip where the driver was sleepy.The overall average percentage of video segments where ORS and SRS matched was 41 % in Test 1. ORS 0 (alert) and ORS 2 (very sleepy) were easier to score than ORS 1 and it was slightly harder to rate night-time drives. Inter-rater agreement was low, with average Pearson’s r correlations of 0.19 and Krippendorff’s alpha of 0.15. In Test 2, the average Pearson’s r correlations was 0.35 and Krippendorff’s alpha was 0.62. The correspondence between ORS and SRS showed an agreement of 35 %.The results indicate that ORS ratings based on real road video recordings correspond poorly with SRS and have low inter-rater agreement. Further research is necessary in order to further evaluate the usefulness of ORS as a measure of sleepiness.
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| 2. |
- Anund, Anna, et al.
(författare)
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Observer Rated Sleepiness and Real Road Driving : An Explorative Study
- 2013
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:5, s. e64782-
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Tidskriftsartikel (refereegranskat)abstract
- The aim of the present study was to explore if observer rated sleepiness (ORS) is a feasible method for quantification of driver sleepiness in field studies. Two measures of ORS were used:one for behavioural signs based on facial expression, body gestures and body movements labelled B-ORS, andone based on driving performance e.g. if swerving and other indicators of impaired driving occurs, labelled D-ORSA limited number of observers sitting in the back of an experimental vehicle on a motorway about 2 hours repeatedly 3 times per day (before lunch, after lunch, at night) observed 24 participant's sleepiness level with help of the two observer scales. At the same time the participant reported subjective sleepiness (KSS), EOG was recorded (for calculation of blink duration) and several driving measure were taken and synchronized with the reporting.Based on mixed model Anova and correlation analysis the result showed that observer ratings of sleepiness based on drivers' impaired performance and behavioural signs are sensitive to extend the general pattern of time awake, circadian phase and time of driving. The detailed analysis of the subjective sleepiness and ORS showed weak correspondence on an individual level. Only 16% of the changes in KSS were predicted by the observer. The correlation between the observer ratings based on performance (D-ORS) and behavioural signs (B-ORS) are high (r =. 588), and the B-ORS shows a moderately strong association (r =. 360) with blink duration. Both ORS measures show an association (r>0.45) with KSS, whereas the association with driving performance is weak.The results show that the ORS-method detects the expected general variations in sleepy driving in field studies, however, sudden changes in driver sleepiness on a detailed level as 5 minutes is usually not detected; this holds true both when taking into account driving behaviour or driver behavioural signs.
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| 3. |
- Fors, Carina, et al.
(författare)
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Investigation of driver sleepiness in FOT data : final report of the project SleepEYE II, part 2
- 2013
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Driver sleepiness contributes to a great number of motor vehicle accidents every year. In order to reduce the number of sleepiness related accidents, more knowledge on e.g. prevalence, countermeasures and driver behaviour is needed. Data from field operational tests (FOT) has a potential to provide such knowledge with high ecological validity. The objective of the project was to propose and evaluate methods for identification of driver sleepiness in FOT data. More specifically, the aim was to identify objective indicators of sleepiness – based on driving behaviour, eye blink behaviour and models of circadian rhythm – and to evaluate a subjective video scoring method for estimating driver sleepiness levels. Data from two separate projects were used: 1) the ViP-project SleepEYE, in which a controlled field test was conducted, and 2) euroFOT, which was a large scale FOT. In a first step the data quality of blink-based indicators obtained from a camera system was evaluated. It was concluded that the data quality had to be improved and thus, a new detection algorithm was devised and implemented. The new detection algorithm had an acceptable detection rate (approximately 50 %) when applied to data from the SleepEYE field test, but for euroFOT data the number of identified blinks was very low (< 5 blinks/min) in about half of the trips. There is thus a need for further improvements of the blink detection algorithm. An in-depth study on indicators of driver sleepiness was carried out using data collected in the SleepEYE experiment, with the purpose of employing the best indicators to study driver sleepiness in the euroFOT database. The most promising indicators were found to be mean blink duration and number of line crossings. A sleepiness classifier was suggested based on the distribution of the data (i.e. visual inspection). When applied to SleepEYE data the classifier was found to have good specificity while the sensitivity of the classifier was not so good. From euroFOT no true data on the drivers’ sleepiness levels were available and it was therefore not possible to evaluate the performance of the classifier. However, an explorative analysis showed that only very few data points were classified as sleepy. This may be reasonable since most trips were conducted during daytime, but it is a somewhat disappointing result for the project. A study was carried out on whether it is possible to use video recordings of drivers in order to estimate the drivers’ self-rated level of sleepiness. Forty participants rated 54 one-minute video clips of an equal number of sleepy and alert drivers on a scale with three levels (alert, first signs of sleepiness, very sleepy). The results of the study showed that performing such observer rated sleepiness (ORS) estimations on drivers is extremely difficult. The videos available in FOTs are usually of rather poor quality which, clearly limits the possibility of making reliable observer rated sleepiness estimations. In conclusion, studying driver sleepiness in (existing) FOT data is difficult, for several reasons: 1) eye camera based indicators suffer from detection errors and low detection rate, 2) driving-based indicators are influenced by e.g. road curvature and traffic density, 3) models of sleepiness cannot be used since no information on hours slept and time awake is available, and 4) video scoring is not reliable, at least not given the quality of the available video recordings. In future studies on driver sleepiness in FOTs sleepiness should be addressed in the FOT design. Some information about the drivers' sleep and sleepiness (ratings, sleep diaries, etc.) must be collected during the test; otherwise it will be very difficult to get any useful results.
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| 4. |
- Hallvig, David, et al.
(författare)
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Real driving at night - predicting lane departures from physiological and subjective sleepiness
- 2014
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Ingår i: Biological Psychology. - : Elsevier BV. - 0301-0511 .- 1873-6246. ; 101, s. 18-23
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Tidskriftsartikel (refereegranskat)abstract
- Only limited information is available on how driving performance relates to physiological and subjective sleepiness on real roads. This relation was the focus of the present study. 33 volunteers drove for 90min on a rural road during the afternoon and night in an instrumented car, while electroencephalography and electrooculography and lane departures were recorded continuously and subjective ratings of sleepiness were made every 5min (Karolinska Sleepiness Scale - KSS). Data was analyzed using Bayesian multilevel modeling. Unintentional LDs increased during night driving, as did KSS and long blink durations(LBD). Lateral position moved to the left . LDs were predicted by self-reported sleepiness and LBDs across time and were significantly higher in individuals with high sleepiness. Removal of intentional LDs, enhanced the KSS/LD relation. It was concluded that LDs, KSS, and LBDs are strongly increased during night driving and that KSS predicts LDs.
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| 5. |
- Åkerstedt, Torbjörn, et al.
(författare)
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Having to stop driving at night because of dangerous sleepiness : awareness, physiology and behaviour
- 2013
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Ingår i: Journal of Sleep Research. - : Wiley. - 0962-1105 .- 1365-2869. ; 22:4, s. 380-388
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Tidskriftsartikel (refereegranskat)abstract
- A large number of accidents are due to the driver falling asleep at the wheel, but details of this link have not been studied on a real road. The purpose of the present study was to describe the development of sleepiness indicators, leading to the drive being terminated prematurely by the onboard expert driving instructor because of imminent danger. Eighteen individuals participated during a day drive and a night drive on a motorway (both 90 min). Eight drivers terminated (N) prematurely (after 43 min) because of sleep-related imminent danger [according to the driving instructor or their own judgement (two cases)].The results showed very high sleepiness ratings (8.5 units on the Karolinska Sleepiness Scale) immediately before termination (<7 at a similar time interval for those 10 who completed the drive). Group N also showed significantly higher levels of sleep intrusions on the electroencephalography/electro-oculography (EEG/EOG) than those who completed the drive (group C). The sleep intrusions were increased in group N during the first 40 min of the night drive. During the day drive, sleep intrusions were increased significantly in group N. The night drive showed significant increases of all sleepiness indicators compared to the day drive, but also reduced speed and driving to the left in the lane. It was concluded that 44% of drivers during late-night driving became dangerously sleepy, and that this group showed higher perceived sleepiness and more sleep intrusions in the EEG/EOG.
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