| 1. |
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| 2. |
- Sandberg, David, 1980, et al.
(författare)
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Detecting driver sleeepiness using optimized non-linear combinations of sleepiness indicators
- 2011
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Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 12:1, s. 97-108
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Tidskriftsartikel (refereegranskat)abstract
- This paper addresses the problem of detecting sleepiness in car drivers. First, a variety of sleepiness indicators (based on driving behavior) proposed in the literature were evaluated. These indicators were then subjected to parametric optimization using stochastic optimization methods. To improve performance, the functional form of some of the indicators was generalized before optimization. Next, using a neural network, the best performing sleepiness indicators were combined with a mathematical model of sleepiness, i.e., the sleep/wake predictor (SWP). The analyses were based on data obtained from a study that involved 12 test subjects at the moving-base driving simulator at the Swedish National Road and Transportation Research Institute (VTI), Linkping, Sweden. The data were derived from 12 1-h driving sessions for each test subject, with varying degrees of sleepiness. The performance measure (range [0,1]) for indicators was taken as the average of sensitivity and specificity. Starting with indicators proposed in the literature, the best such indicator, i.e., the standard deviation of the yaw angle, reached a performance score of 0.72 on previously unseen test data. It was found that indicators based on a given signal gave essentially equal performance after parametric optimization, but in no case was it better than 0.72. The best generalized indicator (the generic variability indicator) obtained a performance score of 0.74. SWP achieved a score of 0.78. However, by nonlinearly combining SWP with the generic variability indicator, a score of 0.83 was obtained. Thus, the results imply that a nonlinear combination of a measure based on driving behavior with a model of sleepiness significantly improves driver sleepiness detection.
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| 3. |
- Radun, Igor, et al.
(författare)
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Sleepy drivers on a slippery road : A pilot study using a driving simulator
- 2022
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Ingår i: Journal of Sleep Research. - : John Wiley & Sons. - 0962-1105 .- 1365-2869. ; 31:2
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Tidskriftsartikel (refereegranskat)abstract
- Sleepy drivers have problems with keeping the vehicle within the lines, and might often need to apply a sudden or hard corrective steering wheel movement. Such movements, if they occur while driving on a slippery road, might increase the risk of ending off road due to the unforgiving nature of slippery roads. We tested this hypothesis. Twelve young men participated in a driving simulator experiment with two counterbalanced conditions; dry versus slippery road x day (alert) versus night (sleepy) driving. The participants drove 52.5 km on a monotonous two-lane highway and rated their sleepiness seven times using the Karolinska Sleepiness Scale. Blink durations were extracted from an electrooculogram. The standard deviation of lateral position and the smoothness of steering events were measures of driving performance. Each outcome variable was analysed with mixed-effect models with road condition, time-of-day and time-on-task as predictors. The Karolinska Sleepiness Scale increased with time-on-task (p < 0.001) and was higher during night drives (p < 0.001), with a three-way interaction suggesting a small increased sleepiness with driving time at night with slippery road conditions (p = 0.012). Blink durations increased with time-on-task (p < 0.01) with an interaction between time-of-day and road condition (p = 0.040) such that physiological sleepiness was lower for sleep-deprived participants in demanding road conditions. The standard deviation of lateral position increased with time-on-task (p = 0.026); however, during night driving it was lower on a slippery road (p = 0.025). The results indicate that driving in demanding road condition (i.e. slippery road) might further exhaust already sleepy drivers, although this is not clearly reflected in driving performance.
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| 4. |
- Sandberg, David, 1980, et al.
(författare)
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The Characteristics of Sleepiness During Real Driving at Night - A Study of Driving Performance, Physiology and Subjective Experience
- 2011
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Ingår i: Sleep. - 1550-9109 .- 0161-8105. ; 34:10, s. 1317-1325
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Tidskriftsartikel (refereegranskat)abstract
- Study Objectives: Most studies of sleepy driving have been carried out in driving simulators. A few studies of real driving are available, but these have used only a few sleepiness indicators. The purpose of the present study was to characterize sleepiness in several indicators during real driving at night, compared with daytime driving. Design: Participants drove 55 km (at 90km/h) on a 9-m-wide rural highway in southern Sweden. Daytime driving started at 09: 00 or 11: 00 (2 groups) and night driving at 01: 00 or 03: 00 (balanced design). Setting: Instrumented car on a real road in normal traffic. Participants: Eighteen participants drawn from the local driving license register. Interventions: Daytime and nighttime drives. Measurement and Results: The vehicle was an instrumented car with video monitoring of the edge of the road and recording of the lateral position and speed. Electroencephalography and electrooculography were recorded, together with ratings of sleepiness every 5 minutes. Pronounced effects of night driving were seen for subjective sleepiness, electroencephalographic indicators of sleepiness, blink duration, and speed. Also, time on task showed significant effects for subjective sleepiness, blink duration, lane position, and speed. Sleepiness was highest toward the end of the nighttime drive. Night driving caused a leftward shift in lateral position and a reduction of speed. The latter two findings, as well as the overall pattern of sleepiness indicators, provide new insights into the effects of night driving. Conclusion: Night driving is associated with high levels of subjective, electrophysiologic, and behavioral sleepiness.
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| 5. |
- Sandberg, David, 1980, et al.
(författare)
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The impact of sleepiness on lane positioning in truck driving
- 2013. - 1
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Ingår i: Driver Distraction and Inattention. - Farnham : Ashgate. - 9781409425854 - 9781315578156 ; , s. 405-416, s. 405-416
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Bokkapitel (refereegranskat)abstract
- This chapter concerns the detection of sleepiness in truck drivers. Data obtained from a driver sleepiness study involving real-world driving are used in order to analyse the performance of several sleepiness indicators based on driving behavior; such as, for example, variability in lateral position and heading angle. Contrary to the results obtained for passenger cars, for heavy trucks it is found that indicators based on variability provide little or no information; their performance does not rise significantly above chance levels.However, the data indicate that there is a significant difference in the average lane position for sleepy and alert drivers, respectively, such that a sleepy driver generally places the vehicle closer (by about 0.2 m) to the centre of the road than an alert driver. The analysis also shows a significant, monotonous, increase in average lateral position (measured from the right, outer, lane boundary towards the lane centre) between the four cases of (i) daytime alert driving, (ii) daytime sleepy driving, (iii) night-time alert driving and (iv) nighttime sleepy driving.
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| 6. |
- 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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| 7. |
- Ahlström, Christer, et al.
(författare)
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Fit-for-duty test for estimation of drivers sleepiness level: Eye movements improve the sleep/wake predictor
- 2013
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Ingår i: Transportation Research Part C. - : Elsevier. - 0968-090X .- 1879-2359. ; 26, s. 20-32
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Tidskriftsartikel (refereegranskat)abstract
- Driver sleepiness contributes to a considerable proportion of road accidents, and a fit-for-duty test able to measure a drivers sleepiness level might improve traffic safety. The aim of this study was to develop a fit-for-duty test based on eye movement measurements and on the sleep/wake predictor model (SWP, which predicts the sleepiness level) and evaluate the ability to predict severe sleepiness during real road driving. Twenty-four drivers participated in an experimental study which took place partly in the laboratory, where the fit-for-duty data were acquired, and partly on the road, where the drivers sleepiness was assessed. A series of four measurements were conducted over a 24-h period during different stages of sleepiness. Two separate analyses were performed; a variance analysis and a feature selection followed by classification analysis. In the first analysis it was found that the SWP and several eye movement features involving anti-saccades, pro-saccades, smooth pursuit, pupillometry and fixation stability varied significantly with different stages of sleep deprivation. In the second analysis, a feature set was determined based on floating forward selection. The correlation coefficient between a linear combination of the acquired features and subjective sleepiness (Karolinska sleepiness scale, KSS) was found to be R = 0.73 and the correct classification rate of drivers who reached high levels of sleepiness (KSS andgt;= 8) in the subsequent driving session was 82.4% (sensitivity = 80.0%, specificity = 84.2% and AUC = 0.86). Future improvements of a fit-for-duty test should focus on how to account for individual differences and situational/contextual factors in the test, and whether it is possible to maintain high sensitive/specificity with a shorter test that can be used in a real-life environment, e.g. on professional drivers.
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| 8. |
- Ahlström, Christer, 1977-, et al.
(författare)
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Real-Time Adaptation of Driving Time and Rest Periods in Automated Long-Haul Trucking : Development of a System Based on Biomathematical Modelling, Fatigue and Relaxation Monitoring
- 2022
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1524-9050 .- 1558-0016. ; 23:5, s. 4758-4766
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Tidskriftsartikel (refereegranskat)abstract
- Hours of service regulations govern the working hours of commercial motor vehicle drivers, but these regulations may become more flexible as highly automated vehicles have the potential to afford periods of in-cab rest or even sleep while the vehicle is moving. A prerequisite is robust continuous monitoring of when the driver is resting (to account for reduced time on task) or sleeping (to account for the reduced physiological drive to sleep). The overall aims of this paper are to raise a discussion of whether it is possible to obtain successful rest during automated driving, and to present initial work on a hypothetical data driven algorithm aimed to estimate if it is possible to gain driving time after resting under fully automated driving. The presented algorithm consists of four central components, a heart rate-based relaxation detection algorithm, a camera-based sleep detection algorithm, a fatigue modelling component taking time awake, time of day and time on task into account, and a component that estimates gained driving time. Real-time assessment of driver fitness is complicated, especially when it comes to the recuperative value of in-cab sleep and rest, as it depends on sleep quality, time of day, homeostatic sleep pressure and on the activities that are carried out while resting. The monotony that characterizes for long-haul truck driving is clearly interrupted for a while, but the long-term consequences of extended driving times, including user acceptance of the key stakeholders, requires further research.
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| 9. |
- Anund, Anna, et al.
(författare)
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Factors associated with self-reported driver sleepiness and incidents in city bus drivers
- 2016
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Ingår i: Industrial Health. - : National Institute of Occupational Safety and Health. - 0019-8366 .- 1880-8026. ; 54:4, s. 337-346
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Tidskriftsartikel (refereegranskat)abstract
- Driver fatigue has received increased attention during recent years and is now considered to be a major contributor to approximately 15-30% of all crashes. However, little is known about fatigue in city bus drivers. It is hypothesized that city bus drivers suffer from sleepiness, which is due to a combination of working conditions, lack of health and reduced sleep quantity and quality.The overall aim with the current study is to investigate if severe driver sleepiness, as indicated by subjective reports of having to fight sleep while driving, is a problem for city based bus drivers in Sweden and if so, to identify the determinants related to working conditions, health and sleep which contribute towards this. The results indicate that driver sleepiness is a problem for city bus drivers, with 19% having to fight to stay awake while driving the bus 2-3 times each week or more and nearly half experiencing this at least 2-4 times per month. In conclusion, severe sleepiness, as indicated by having to fight sleep during driving, was common among the city bus drivers. Severe sleepiness correlated with fatigue related safety risks, such as near crashes.
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| 10. |
- Anund, Anna, et al.
(författare)
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Rumble strips in centre of the lane and the effect on sleepy drivers
- 2011
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Ingår i: Industrial Health. - : National Institute of Industrial Health. - 0019-8366 .- 1880-8026. ; 49:5, s. 549-558
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to describe the effects of sleep loss on behavioural and subjective indicators of sleepiness on a road containing a milled rumble strip in the centre of the lane. Particular attention was paid to behavioural and subjective indicators of sleepiness when using the centre lane rumble strip, and to possible erratic driving behaviour when hitting a rumble strip. In total 9 regular shift workers drove during the morning hours after a full night shift and after a full night sleep. The order was balanced. The experiment was conducted in a moving base driving simulator on rural roads with a road width of 6.5 and 9 meters. Out of the 1,636 rumble strip hits that occurred during the study, no indications of erratic driving behaviour associated with the jolt caused by making contact with the centre lane rumble strip could be found. Comparing the alert condition with the sleep deprived condition, both the standard deviation of lateral position (SDLP) and the Karolinska Sleepiness Scale (KSS) increased for sleepy drivers. For the two road widths, the drivers drove closer to the centre line on the 6.5-meter road. The KSS and the SDLP increased with time on task. This simulator study indicates that rumble strips in the centre of the lane may be an alternative to centreline and edgeline rumble strips on narrow roads.
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