| 1. |
- Ahlström, Christer, et al.
(författare)
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A gaze-based driver distraction warning system and its effect on visual behaviour
- 2013
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 14:2, s. 965-973
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Tidskriftsartikel (refereegranskat)abstract
- Driver distraction is a contributing factor to many crashes; therefore, a real-time distraction warning system should have the potential to mitigate or circumvent many of these crashes. The objective of this paper is to investigate the usefulness of a real-time distraction detection algorithm called AttenD. The evaluation is based on data from an extended field study comprising seven drivers who drove on an average of 4351 ± 2181 km in a naturalistic setting.Visual behavior was investigated both on a global scale and on a local scale in the surroundings of each warning. An increase in the percentage of glances at the rear-view mirror and a decrease in the amount of glances at the center console were found. The results also show that visual time sharing decreased in duration from 9.94 to 9.20 s due to the warnings, that the time from fully attentive to warning decreased from 3.20 to 3.03 s, and that the time from warning to full attentiveness decreased from 6.02 to 5.46 s. The limited number of participants does not allow any generalizable conclusions, but a trend toward improved visual behavior could be observed. This is a promising start for further improvements of the algorithm and the warning strategy.
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| 2. |
- Ahlström, Christer, 1977-, et al.
(författare)
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A Generalized Method to Extract Visual Time-Sharing Sequences From Naturalistic Driving Data
- 2017
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 18:11, s. 2929-2938
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Tidskriftsartikel (refereegranskat)abstract
- Indicators based on visual time-sharing have been used to investigate drivers' visual behaviour during additional task execution. However, visual time-sharing analyses have been restricted to additional tasks with well-defined temporal start and end points and a dedicated visual target area. We introduce a method to automatically extract visual time-sharing sequences directly from eye tracking data. This facilitates investigations of systems, providing continuous information without well-defined start and end points. Furthermore, it becomes possible to investigate time-sharing behavior with other types of glance targets such as the mirrors. Time-sharing sequences are here extracted based on between-glance durations. If glances to a particular target are separated by less than a time-based threshold value, we assume that they belong to the same information intake event. Our results indicate that a 4-s threshold is appropriate. Examples derived from 12 drivers (about 100 hours of eye tracking data), collected in an on-road investigation of an in-vehicle information system, are provided to illustrate sequence-based analyses. This includes the possibility to investigate human-machine interface designs based on the number of glances in the extracted sequences, and to increase the legibility of transition matrices by deriving them from time-sharing sequences instead of single glances. More object-oriented glance behavior analyses, based on additional sensor and information fusion, are identified as the next future step. This would enable automated extraction of time-sharing sequences not only for targets fixed in the vehicle's coordinate system, but also for environmental and traffic targets that move independently of the driver's vehicle.
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| 3. |
- Ahlström, Christer, 1977-, et al.
(författare)
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Alcohol impairs driver attention and prevents compensatory strategies
- 2023
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Ingår i: Accident Analysis and Prevention. - : Elsevier. - 0001-4575 .- 1879-2057. ; 184
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Tidskriftsartikel (refereegranskat)abstract
- While the negative effects of alcohol on driving performance are undisputed, it is unclear how driver attention, eye movements and visual information sampling are affected by alcohol consumption. A simulator study with 35 participants was conducted to investigate whether and how a driver's level of attention is related to self-paced non-driving related task (NDRT)-engagement and tactical aspects of undesirable driver behaviour under increasing levels of breath alcohol concentration (BrAC) up to 1.0 ‰. Increasing BrAC levels lead to more frequent speeding, short time headways and weaving, and higher NDRT engagement. Instantaneous distraction events become more frequent, with more and longer glances to the NDRT, and a general decline in visual attention to the forward roadway. With alcohol, the compensatory behaviour that is typically seen when drivers engage in NDRTs did not appear. These findings support the theory that alcohol reduces the ability to shift attention between multiple tasks. To conclude, the independent reduction in safety margins in combination with impaired attention and an increased willingness to engage in NDRTs is likely the reason behind increased crash risk when driving under the influence of alcohol. © 2023
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| 4. |
- Ahlström, Christer, et al.
(författare)
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Changes in glance behaviour when using a visual eco-driving system : A field study
- 2017
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Ingår i: Applied Ergonomics. - : Elsevier BV. - 0003-6870 .- 1872-9126. ; 58, s. 414-423
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Tidskriftsartikel (refereegranskat)abstract
- While in-vehicle eco-driving support systems have the potential to reduce greenhouse gas emissions and save fuel, they may also distract drivers, especially if the system makes use of a visual interface. The objective of this study is to investigate the visual behaviour of drivers interacting with such a system, implemented on a five-inch screen mounted above the middle console. Ten drivers participated in a real-world, on-road driving study where they drove a route nine times (2 pre-baseline drives, 5 treatment drives, 2 post-baseline drives). The route was 96 km long and consisted of rural roads, urban roads and a dual-lane motorway.The results show that drivers look at the system for 5–8% of the time, depending on road type, with a glance duration of about 0.6 s, and with 0.05% long glances (>2s) per kilometre. These figures are comparable to what was found for glances to the speedometer in this study. Glance behaviour away from the windscreen is slightly increased in treatment as compared to pre- and post-baseline, mirror glances decreased in treatment and post-baseline compared to pre-baseline, and speedometer glances increased compared to pre-baseline. The eco-driving support system provided continuous information interspersed with additional advice pop-ups (announced by a beep) and feedback pop-ups (no auditory cue). About 20% of sound initiated advice pop-ups were disregarded, and the remaining cases were usually looked at within the first two seconds. About 40% of the feedback pop-ups were disregarded. The amount of glances to the system immediately before the onset of a pop-up was clearly higher for feedback than for advice.
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| 5. |
- Ahlström, Christer, et al.
(författare)
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Effects of partially automated driving on the development of driver sleepiness
- 2021
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575 .- 1879-2057. ; 153
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this study was to compare the development of sleepiness during manual driving versus level 2 partially automated driving, when driving on a motorway in Sweden. The hypothesis was that partially auto-mated driving will lead to higher levels of fatigue due to underload. Eighty-nine drivers were included in the study using a 2 ? 2 design with the conditions manual versus partially automated driving and daytime (full sleep) versus night-time (sleep deprived). The results showed that night-time driving led to markedly increased levels of sleepiness in terms of subjective sleepiness ratings, blink durations, PERCLOS, pupil diameter and heart rate. Partially automated driving led to slightly higher subjective sleepiness ratings, longer blink durations, decreased pupil diameter, slower heart rate, and higher EEG alpha and theta activity. However, elevated levels of sleepiness mainly arose from the night-time drives when the sleep pressure was high. During daytime, when the drivers were alert, partially automated driving had little or no detrimental effects on driver fatigue. Whether the negative effects of increased sleepiness during partially automated driving can be compensated by the positive effects of lateral and longitudinal driving support needs to be investigated in further studies.
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| 6. |
- Ahlström, Christer, 1977-, et al.
(författare)
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Effects of the road environment on the development of driver sleepiness in young male drivers
- 2018
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Ingår i: Accident Analysis and Prevention. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0001-4575 .- 1879-2057. ; 112, s. 127-134
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Tidskriftsartikel (refereegranskat)abstract
- Latent driver sleepiness may in some cases be masked by for example social interaction, stress and physical activity. This short-term modulation of sleepiness may also result from environmental factors, such as when driving in stimulating environments. The aim of this study is to compare two road environments and investigate how they affect driver sleepiness. Thirty young male drivers participated in a driving simulator experiment where they drove two scenarios: a rural environment with winding roads and low traffic density, and a suburban road with higher traffic density and a more built-up roadside environment. The driving task was essentially the same in both scenarios, i.e. to stay on the road, without much interaction with other road users. A 2 x 2 design, with the conditions rural versus suburban, and daytime (full sleep) versus night-time (sleep deprived), was used. The results show that there were only minor effects of the road environment on subjective and physiological indicators of sleepiness. In contrast, there was an increase in subjective sleepiness, longer blink durations and increased EEG alpha content, both due to time on task and to night-time driving. The two road environments differed both in terms of the demand on driver action and of visual load, and the results indicate that action demand is the more important of the two factors. The notion that driver fatigue should be countered in a more stimulating visual environment such as in the city is thus more likely due to increased task demand rather than to a richer visual scenery. This should be investigated in further studies.
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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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Local changes in the wake electroencephalogram precedes lane departures
- 2017
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Ingår i: Journal of Sleep Research. - : Blackwell Publishing. - 0962-1105 .- 1365-2869.
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this exploratory study is to investigate if lane departures are associated with local sleep, measured via source-localized electroencephalography (EEG) theta power in the 5-9 Hz frequency range. Thirty participants drove in an advanced driving simulator, resulting in 135 lane departures at high levels of self-reported sleepiness. These lane departures were compared to matching non-departures at the same sleepiness level within the same individual. There was no correspondence between lane departures and global theta activity. However, at the local level an increased risk for lane departures was associated with increased theta content in brain regions related to motor function.
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| 9. |
- 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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| 10. |
- Ahlström, Christer, 1977-, et al.
(författare)
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Technologies for Risk Mitigation and Support of Impaired Drivers
- 2022
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:5, s. 4736-4738
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This editorial serves as an extended introduction to the Special Issue on Technologies for Risk Mitigation and Support of Impaired Drivers. It gives the context to recent advances in assisted and automated driving and the new challenges that arise when modern technology meets human users. The Special Issue focuses on the development of robust sensors and detection algorithms for driver state monitoring of fatigue, stress, and inattention, and on the development of personalized multimodal, user-oriented, and adaptive information, warning, actuation, and handover strategies. A summary of more recent developments serves as a motivation for each article that follows.
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