Effects of a seat-integrated mobilization system during passive driver fatigue

Schneider, Lisa; Frings, Katrin; Rothe, Siegfried; Schrauf, Michael; Jaitner, Thomas

doi:10.1016/j.aap.2020.105883

Cited by 12 publications

(3 citation statements)

References 36 publications

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“…These articles mainly did not focus on countermeasures in CAD, but on manual driving. Schneider et al [34], for example, investigated the effects of a seat-integrated mobilization system on passive fatigue, Bier et al [24] focused on the effects of driving games, and Wang et al [35] explored a haptic guidance steering system. Although these studies showed effective opportunities to prevent driver fatigue, they are not wholly applicable in CAD.…”

Section: Search Strategy and Selection Criteriamentioning

confidence: 99%

How to Counteract Driver Fatigue during Conditional Automated Driving—A Systematic Review

Loew,

Kurpiers,

Götze

et al. 2024

Future Transportation

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This paper summarizes the research on countermeasures against driver fatigue based on a comprehensive systematic literature review. Driver fatigue, induced by task monotony during conditional automated driving (CAD, SAE Level 3), can increase the risk of road accidents. There are several measures that counteract driver fatigue and aim to reduce the risk caused by a fatigued driver in the context of CAD. Twelve selected articles focusing on driver fatigue countermeasures in CAD were analyzed. The findings and conclusions are presented, focusing on the countermeasures themselves and their implementation. The countermeasures were critically discussed, especially regarding effectiveness and applicability. They seem to be effective in counteracting driver fatigue. However, the measures are not easily compared because they were studied in various experimental settings and various driver fatigue measurements were used. Different countermeasures have proven to be effective in reducing fatigue during CAD. For this reason, further investigation is needed to gain further insights into their applications, advantages, and disadvantages. Further studies will be conducted to verify the best solution regarding their effectiveness and applicability.

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Section: Search Strategy and Selection Criteriamentioning

confidence: 99%

How to Counteract Driver Fatigue during Conditional Automated Driving—A Systematic Review

Loew,

Kurpiers,

Götze

et al. 2024

Future Transportation

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show abstract

“…Much of the literature since the mid-1990s has emphasised fatigue detection technology, which has been widely studied in manual driving [14]. Scholars have used various methods to collect fatigue indicators from different perspectives, including but not limited to vehicle operating characteristics [40], driver physiological signals [41], behavioural characteristics [42], and subjective scores [34] related to human or vehicle features. However, although there are now several effective fatigue detection and assessment methods for manual driving, this does not appear to be the case for automated driving.…”

Section: Evaluating Fatigue In Conditionally Automated Drivingmentioning

confidence: 99%

Effects of Level 3 Automated Vehicle Drivers’ Fatigue on Their Take-Over Behaviour: A Literature Review

Guo

Zhang

Cai

et al. 2021

Journal of Advanced Transportation

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With advancements in automated driving technology, Level 3 vehicle automation has been proliferating. In Level 3, drivers can turn their attention to things unrelated to driving and only takeover in cases of emergency. However, the transition to the main driving task can be affected by different physical and psychological changes in drivers such as fatigue and distraction. Although existing research in the field of manual driving has demonstrated the effects of fatigue on driver performance, there have been relatively few studies on fatigue in the field of automated driving. Fatigue decreases drivers’ alertness, which can prevent drivers from conducting necessary emergency takeover manoeuvres in a safe and timely manner. This systematic literature review was conducted to establish relationships between driving fatigue and takeover behaviour in the existing literature on Level 3 automated driving systems. Different from existing reviews of driving fatigue, this paper focuses on the commonly used and most effective evaluation indicators of driving fatigue and further discusses the methods to improve the takeover efficiency of fatigued drivers. This is the first detailed systematic review of general relationships between fatigue in automated driving and drivers’ takeover behaviours when the vehicle sends a takeover request. Researchers are invited to expand on the findings here to further clarify the findings on the associations between driver fatigue indicators in automated vehicle driving and drivers’ takeover response times.

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“…Driving fatigue detection can be divided into subjective methods and objective methods [5,6]. The subjective method is generally conducted in the form of questionnaires, which are often used as an auxiliary method in the detection of driving fatigue [7]. Objective detection methods mainly detect the driver's mental state by detecting the driver's physiological signals [8], facial expressions [9], vehicle tracks [10] and so on.…”

Section: Introductionmentioning

confidence: 99%

Research on Driving Fatigue Alleviation Using Interesting Auditory Stimulation Based on VMD-MMSE

Wang

Lü

Kang

et al. 2021

Entropy

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The accurate detection and alleviation of driving fatigue are of great significance to traffic safety. In this study, we tried to apply the modified multi-scale entropy (MMSE) approach, based on variational mode decomposition (VMD), to driving fatigue detection. Firstly, the VMD was used to decompose EEG into multiple intrinsic mode functions (IMFs), then the best IMFs and scale factors were selected using the least square method (LSM). Finally, the MMSE features were extracted. Compared with the traditional sample entropy (SampEn), the VMD-MMSE method can identify the characteristics of driving fatigue more effectively. The VMD-MMSE characteristics combined with a subjective questionnaire (SQ) were used to analyze the change trends of driving fatigue under two driving modes: normal driving mode and interesting auditory stimulation mode. The results show that the interesting auditory stimulation method adopted in this paper can effectively relieve driving fatigue. In addition, the interesting auditory stimulation method, which simply involves playing interesting auditory information on the vehicle-mounted player, can effectively relieve driving fatigue. Compared with traditional driving fatigue-relieving methods, such as sleeping and drinking coffee, this interesting auditory stimulation method can relieve fatigue in real-time when the driver is driving normally.

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Effects of a seat-integrated mobilization system during passive driver fatigue

Cited by 12 publications

References 36 publications

How to Counteract Driver Fatigue during Conditional Automated Driving—A Systematic Review

How to Counteract Driver Fatigue during Conditional Automated Driving—A Systematic Review

Effects of Level 3 Automated Vehicle Drivers’ Fatigue on Their Take-Over Behaviour: A Literature Review

Research on Driving Fatigue Alleviation Using Interesting Auditory Stimulation Based on VMD-MMSE

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