Investigating the interplay between cognitive workload and situation awareness during full driving automation DOI

Praneet Sahoo,

Anthony R. Bain, Francesco Biondi

et al.

Theoretical Issues in Ergonomics Science, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 21

Published: Dec. 27, 2024

This study investigates concurrent changes in cognitive workload and situation awareness during the use of full driving automation. Research shows that automation has a negative effect on awareness. Driving studies posit decline when is engaged. Yet little known about how affects awareness, or vice versa, used. Participants were instructed to operate virtual reality fixed-base simulator mode. No input was required by participants making demand minimal. Situation measured means global assessment scale. Cognitive behavioral, ocular, neurophysiological metrics. Lower observed over time. increased time as evidenced an increase pupil size oxygenated hemoglobin right dorsolateral prefrontal cortex. Results indicate inverse relationship between with increments former leading reductions latter. Although this pattern runs counter our hypothesis, consistent prior work observing under increasingly higher workload.

Language: Английский

Recognizing situation awareness of forklift operators based on eye-movement & EEG features DOI
Yutao Kang, Feng Liu, Weijiong Chen

et al.

International Journal of Industrial Ergonomics, Journal Year: 2024, Volume and Issue: 100, P. 103552 - 103552

Published: Jan. 18, 2024

Language: Английский

Citations

12
EEG-based neural activity for decoding situation awareness at different levels DOI

Qiongfei Wu,

Na Chen, Pei-Luen Patrick Rau

et al.

Ergonomics, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 13

Published: Jan. 13, 2025

Situation awareness (SA) is the ability to perceive, comprehend and project environmental information. Neural activity closely associated with SA. However, it remains unclear how neural represents SA at different levels. Here, three tasks were used assess levels, behavioural electroencephalogram data collected. Relationships between explored through comparisons of EEG power high low For each level, significantly differed Brain region-based analyses further revealed activities originating from distinct brain regions recruited represent These pattern features could be decode KNN (k-nearest neighbour) classifier. The present study marked a significant step in augmenting our understanding mechanism that characterise

Language: Английский

Citations

1
Recognizing the situation awareness of forklift operators based on EEG techniques in a field experiment DOI Creative Commons
Xin Li, Yutao Kang, Weijiong Chen

et al.

Frontiers in Neuroscience, Journal Year: 2024, Volume and Issue: 18

Published: Feb. 20, 2024

Lack of situation awareness (SA) is the primary cause human errors when operating forklifts, so determining SA level forklift operator crucial to safety operations. An EEG recognition approach in actual settings was presented order address issues with invasiveness, subjectivity, and intermittency existing measuring methods. In this paper, we conducted a field experiment that mimicked typical operation scenario verify differences states operators different levels investigate correlation multi-band combination features each brain region SA. Based on sensitive indexes, Support Vector Mechanism used construct model. The results revealed there were between high low θ , α β frequency bands zones F, C, P, O; combined indicators / ( + )/( ), /( ) C significantly correlated SA; accuracy model reached 88.64% case & F P as input. It could provide reference for measurement, contributing improvement

Language: Английский

Citations

2
Identifying suicide attempter in major depressive disorder through machine learning: the importance of pain avoidance, event-related potential features of affective processing DOI Creative Commons
Huanhuan Li,

Shijie Wei,

Fang Sun

et al.

Cerebral Cortex, Journal Year: 2024, Volume and Issue: 34(4)

Published: April 1, 2024

Abstract How to achieve a high-precision suicide attempt classifier based on the three-dimensional psychological pain model is valuable issue in research. The aim of present study explore importance avoidance and its related neural features classification models among patients with major depressive disorder. By recursive feature elimination cross-validation support-vector-machine algorithms, scores from measurements task-based EEG signals were chosen model. In multimodal an accuracy 83.91% area under curve 0.90, ranked as top one optimal set. Theta (reward positive feedback minus neutral feedback) was shared representation ranking event-related potential classifiers. conclusion, affective processing has excellent Pain stable strong indicator for identifying risks both traditional analyses machine-learning approaches. A novel methodology needed clarify relationship between cognitive evoked by punishment stimuli avoidance.

Language: Английский

Citations

1
Effectiveness of Adaptive Attention-based Network for Situation Awareness Recognition DOI
Rongrong Fu, Qien Hou, Shiwei Wang

et al.

IEEE Sensors Journal, Journal Year: 2024, Volume and Issue: 24(12), P. 20092 - 20102

Published: May 8, 2024

Situation awareness (SA) is directly related to the operating level of dynamic system operators, and electroencephalography (EEG) frequently employed as gold standard for SA recognition. Several deep learning models performed well in recognition based on EEG features. However, it remains limitations such a limited size datasets, restricted model interpretability, low capability extracting beneficial In this work, an adaptive spatial-channel attention mechanism (ASCAM) was introduced architectures convolutional neural network (CNN). Specifically, ASCAM allows layers CNN fuse various sizes received information selectively focus effective interpretable Regarding problem by combing frequency noise with multivariate variational mode decomposition (MVMD) enhance generalization models. Experiment results gave that EEGNet embedded framework exhibited relative improvement 6.02% over baseline method. And contributes feature extraction significantly enhances considerable performance. Ablation studies were further implemented confirm efficacy proposed MVMD-based data augmentation. Interpretation indicated have discovered neurobiological mechanisms loss. Meanwhile, lightweight plug-and-play, which can be into any architecture utilized decoding tasks.

Language: Английский

Citations

1
Examining Driver Situation Awareness in the Takeover Process of Conditionally Automated Driving With the Effect of Age DOI Creative Commons

Wen Ding,

Yovela Murzello, Siby Samuel

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 96169 - 96178

Published: Jan. 1, 2024

Background: Previous research has shown that drivers from different age groups demonstrated Situation Awareness (SA) levels in the takeover process of conditional automated driving, where need to collect surrounding information, perceive hazardous events, and make correct actions. Objective: To further explore reason for this age-related difference, we investigated SA two measures, Hazard Perception Time scores delayed SAGAT questions. The time reflects both cognitive processes ocular movements. test was completed after each scenario, revealing how perceived comprehended information. Method: This study recruited three groups, young, middle-aged, older drivers. Especially, old-old (75+ years old), who have more severe impairments compared young-old (65 - 75 old). Each driver went through 12 driving scenarios with road types (highway straight, highway curved, city curved) (manual only, autopilot non-driving-related Tasks). Results: result showed had significantly higher statistically equivalent other groups. Also, curved roads led Conclusion: Older drivers' decreased mainly came movement, which moving their gaze toward events current experiment. Researchers should be mindful regarding slowed movement when designing systems.

Language: Английский

Citations

1
Attention Allocation to Projection Level Alleviates Overconfidence in Situation Awareness DOI
Yang Cai, Pei‐Luen Patrick Rau

Journal of Cognitive Engineering and Decision Making, Journal Year: 2024, Volume and Issue: 18(3), P. 187 - 208

Published: May 25, 2024

Overconfidence in situation awareness (SA) can lead to various detrimental consequences, including risky behaviors. This study investigates the influence of stress and attention allocation on SA manufacturing. Specifically, this aims (1) examine effects objective SA, (2) explore relationship between levels overconfidence, (3) investigate potential alleviation overconfidence through more challenging levels. These findings demonstrate that impairs comprehension aspect SA. Moreover, increases with level. In exploring strategies mitigate allocating specifically most level—SA projection—proved effective alleviating overconfidence. contribute future research by clarifying uncovering link methods alleviate improve decision accuracy manufacturing systems.

Language: Английский

Citations

0
Evaluation of driver’s situation awareness in freeway exit using backpropagation neural network DOI
Yanqun Yang, Yue Chen, Said M. Easa

et al.

Transportation Research Part F Traffic Psychology and Behaviour, Journal Year: 2024, Volume and Issue: 105, P. 42 - 57

Published: July 5, 2024

Language: Английский

Citations

0
Working memory capacity prevents pilots' loss of situation awareness in distraction scenarios——An eye-movement study DOI
Xudong Xie, Jiazhong Yang, Yuan Li

et al.

International Journal of Industrial Ergonomics, Journal Year: 2024, Volume and Issue: 104, P. 103667 - 103667

Published: Nov. 1, 2024

Language: Английский

Citations

0
Research on the Effect of Working Memory Training on the Prevention of Situation Awareness Failure in Shearer Monitoring Operations DOI Creative Commons

Xiaofang Yuan,

Rui Song,

Linhui Sun

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11876 - 11876

Published: Dec. 19, 2024

The digitization of the instrument control system in monitoring operations makes problem operator’s situational awareness failure more prominent. In order to better prevent this occurrence, paper explores from perspective cognitive function. subjects were randomly divided into two groups: a working memory training group and group. Working measurements coal mining machine simulation operation tasks performed before after training, task performance, scale, EEG index data recorded. results showed that, there was significant improvement performance scores different degrees activation θ, α2, β1 frequency bands. It demonstrated that could help improve rapid reaction decision-making abilities operators complex or emergency situations, thus preventing awareness. This study provides new direction for research on prevention failure.

Language: Английский

Citations

0