Review of Techniques for Driver Fatigue Detection

Zhang, Jian Yong; Qiu, Weiqiang; Fu, Hui; Zhang, Meng Ting; Guo, Qing

doi:10.4028/www.scientific.net/amm.433-435.928

Cited by 10 publications

(3 citation statements)

References 5 publications

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“…The features mainly include eyelid distance, eye blink rate, PERCLOS, gaze direction, blink speed, eye saccadic movement, yawning, head orientation, and head nodding. Zhang et al discussed the contrast between techniques based on physiological, behavioral, and vehicular features ( 32 ). This study also pointed out that every single strategy has its own set of limitations, therefore using various methods for the development of fatigue detection technology may be the best solution.…”

Section: Review Of Existing Literaturementioning

confidence: 99%

Evolution of Driver Fatigue Detection Techniques—A Review From 2007 to 2021

Kamti

Iqbal

2022

Transportation Research Record: Journal of the Transportation R

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Driver fatigue is the most important factor in the increase in the frequency of traffic accidents and fatalities every year. Fatigue impairs driving performance through a lack of concentration and slower reaction time. Therefore, a fatigue detection system is very important for safe driving. This paper presents a systematic literature review of the research conducted over the last 15 years to provide information about the evolution of various driver fatigue detection (DFD) systems with the advancement of technologies. In the domain of DFD, researchers have used different approaches such as physiological, behavioral, vehicular, and mixed. Findings from the study indicate that physiological and behavior-based techniques are widely used by the authors, whereas vehicular features are very scarcely used. Analysis of papers shows that researchers are more likely to utilize a combination of physiological and behavior-based approaches to identify driving fatigue or drowsiness. The outcome of this literature review could help practitioners to improve existing fatigue detection technologies by application of the different approaches for fatigue identification and measurement.

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Section: Review Of Existing Literaturementioning

confidence: 99%

Evolution of Driver Fatigue Detection Techniques—A Review From 2007 to 2021

Kamti

Iqbal

2022

Transportation Research Record: Journal of the Transportation R

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“…There are many factors acting as stress on the operator during the work. These stresses may be due not only to physical workload and uncomfortable postures, but also to task complexity, overload of information to be handled, time pressure [8]. This fatigue can be measured in terms of strain on the tractor driver [9].…”

Section: Research Backgroundmentioning

confidence: 99%

Application of Innovative Tools to Design Ergonomic Control Dashboards

Grandi¹,

Peruzzini²,

Campanella³

et al. 2020

Advances in Transdisciplinary Engineering

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Designing highly usable and ergonomic control dashboards is fundamental to support the user in managing and properly setting complex machines, like trains, airplanes, trucks and tractors. Contrarily, control dashboards are usually big, intrusive, full of controls and not really usable for different users. This paper focuses on the re-design of an ergonomic and compact dashboard for tractor control, proposing an innovative methodology in line with human-centered design and ergonomics principles. The study started by shifting the focus from how a machine works to how a task has to be performed and how the user interacts with the machine. It uses virtual simulations and human performance analysis tools to support the concept generation and the detailed design, and to test the new idea with users in the virtual lab. Indeed, within the virtual environment, different configurations of controls can be tested, checking which controls are mostly used and measuring human performance indexes (i.e., postural comfort and mental workload) for each configuration. Virtual mannequins can be used to as “digital twins” to interact with virtual items and to calculate robust comfort indicators during task execution. The study adopted the proposed methodology to an industrial use case to develop a usable and compact armrest for a new tractor platform. The new armrest is smaller than the previous one (-30% in dimensions), more usable (keeping on board only frequent controls, better positioned), and more comfortable (it satisfies 95% of the population size). This new approach could be used also for the design of new products.

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“…The advantages of EEG are relatively inexpensive for acquisition and high temporal resolution. Many algorithms based on EEG signals have been proposed and performed to analyse and detect driver's fatigue [14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%