Tracing the physiological response and behavioral performance of drivers at different levels of mental workload using driving simulators

Zokaei, Mojtaba; Jafari, Mohammad Javad; Khosrowabadi, Reza; Nahvi, Ali; Khodakarim, Sohila; Pouyakian, Mostafa

doi:10.1016/j.jsr.2019.12.022

Cited by 30 publications

(15 citation statements)

References 70 publications

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“…Results obtained in driving scenarios are limited and lack consistent results, however [51]. For example, several studies have reported that the theta EEG power spectrum increased with an increased driving complexity [32,34,52], whereas a more recent study found the opposite result [53]. Overall, these results obtained from research involving non-military personnel might not be strictly applicable to the military [14,54,55].…”

Section: Eeg Theta Activity As An Index Of Mental Workloadmentioning

confidence: 99%

EEG Theta Power Activity Reflects Workload among Army Combat Drivers: An Experimental Study

2020

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We aimed to evaluate the effects of mental workload variations, as a function of the road environment, on the brain activity of army drivers performing combat and non-combat scenarios in a light multirole vehicle dynamic simulator. Forty-one non-commissioned officers completed three standardized driving exercises with different terrain complexities (low, medium, and high) while we recorded their electroencephalographic (EEG) activity. We focused on variations in the theta EEG power spectrum, a well-known index of mental workload. We also assessed performance and subjective ratings of task load. The theta EEG power spectrum in the frontal, temporal, and occipital areas were higher during the most complex scenarios. Performance (number of engine stops) and subjective data supported these findings. Our findings strengthen previous results found in civilians on the relationship between driver mental workload and the theta EEG power spectrum. This suggests that EEG activity can give relevant insight into mental workload variations in an objective, unbiased fashion, even during real training and/or operations. The continuous monitoring of the warfighter not only allows instantaneous detection of over/underload but also might provide online feedback to the system (either automated equipment or the crew) to take countermeasures and prevent fatal errors.

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Section: Eeg Theta Activity As An Index Of Mental Workloadmentioning

confidence: 99%

EEG Theta Power Activity Reflects Workload among Army Combat Drivers: An Experimental Study

2020

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“…While some tasks involved real conversations and everyday topics, such as family, origin, accommodation, traveling [ 103 ], job or school commitments [ 58 ], daily driving habits, driving history, and personal information [ 82 ], in some studies, conversations involving a certain level of emotional involvement [ 129 , 130 ] or the use of the visuospatial ability [ 92 , 131 ] have been used. Tasks involving mathematical operations have been found in a large number of studies (n = 16), either with a simple level of difficulty, such as arithmetic problems [ 112 , 118 , 132 ], or with both simple and complex levels [ 105 , 133 ].…”

Section: Resultsmentioning

confidence: 99%

Talking on the Phone While Driving: A Literature Review on Driving Simulator Studies

Boboc

Voinea

Buzdugan

et al. 2022

IJERPH

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Distracted driving is a growing concern around the world and has been the focus of many naturalistic and simulator-based studies. Driving simulators provide excellent practical and theoretical help in studying the driving process, and considerable efforts have been made to prove their validity. This research aimed to review relevant simulator-based studies focused on investigating the effects of the talking-on-the-phone-while-driving distraction on drivers’ behavior. This work is a scoping review which followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines. The search was performed on five databases, covering twenty years of research results. It was focused on finding answers to three research questions that could offer an overview of the main sources of distraction, the research infrastructure, and the measures that were used to analyze and predict the effects of distractions. A number of 4332 studies were identified in the database search, from which 83 were included in the review. The main findings revealed that TPWD distraction negatively affects driving performance, exposing drivers to dangerous traffic situations. Moreover, there is a general understanding that the driver’s cognitive, manual, visual, and auditory resources are all involved, to a certain degree, when executing a secondary task while driving.

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“…If several tasks need to use the same channel resources, the workload will increase. Consistent with the Yerkes-Dodson law, Zokaei et al [15] tracked drivers' physiological response and behavior under different workload levels and found that to maintain the best driving performance the workload should not be too high or too low.…”

Section: Introductionmentioning

confidence: 91%

Analysis of Freeway Safety Influencing Factors on Driving Workload and Performance Based on the Gray Correlation Method

Xie

Deng³

et al. 2021

Journal of Advanced Transportation

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Human-related factors are a crucial inducement of traffic accidents. Understanding the influence of freeway environments on the driving behavior and workload experienced by drivers has been demonstrated to be of primary importance for improving traffic safety. To study the effect of alignment, traffic flow, and sign information on drivers’ mental workload and behavior, 16 scenarios were constructed using the orthogonal design method, and simulated driving experiments were carried out with 45 participants. During driving, indicators such as the mean and standard deviation of vehicle speed and lane departure were collected, and the NASA-TLX questionnaire was adopted to measure workload. Analysis of variance results indicated that the radius of the horizontal curve, gradient, flow, and sign information level have a significant influence on drivers’ workload and speed keeping ability. In addition, the horizontal curve radius has a significant effect on lane keeping ability. The importance of safety influencing factors on driving workload and performance was quantitatively ranked by integrating the trend of Deng’s correlation degree, comprehensive correlation degree, and similar correlation degree, whose weight was calculated using the entropy method. Traffic sign information was found to have the greatest impact on workload. In terms of driving performance, traffic volume has the greatest influence on the mean and standard deviation of vehicle speed, followed by the amount of sign information. Lane departure is most affected by the radius of the horizontal curve. These findings provide guidance for freeway traffic safety regulation, including workload control and road facility optimization.

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Tracing the physiological response and behavioral performance of drivers at different levels of mental workload using driving simulators

Cited by 30 publications

References 70 publications

EEG Theta Power Activity Reflects Workload among Army Combat Drivers: An Experimental Study

EEG Theta Power Activity Reflects Workload among Army Combat Drivers: An Experimental Study

Talking on the Phone While Driving: A Literature Review on Driving Simulator Studies

Analysis of Freeway Safety Influencing Factors on Driving Workload and Performance Based on the Gray Correlation Method

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