On the importance of working memory in the driving safety field: a systematic review

H Zhang, Y Guo, W Yuan, K Li - Accident Analysis & Prevention, 2023 - Elsevier
In recent years, many studies have used poor cognitive functions to explain risk safety
differences among drivers. Working memory is a cognitive function with information storage …

A progressive review: Emerging technologies for ADAS driven solutions

J Nidamanuri, C Nibhanupudi, R Assfalg… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Over the last decade, the Advanced Driver Assistance System (ADAS) concept has evolved
significantly. ADAS involves several technologies such as automotive electronics, vehicle-to …

A multilayer stacking method base on RFE-SHAP feature selection strategy for recognition of driver's mental load and emotional state

J Huang, Y Peng, L Hu - Expert Systems with Applications, 2024 - Elsevier
The driver state monitoring is becoming one of the research hotspots in the field of traffic and
vehicle safety, which can ensure driving safety by monitoring the driver's state. Therefore …

Driver's mental workload classification using physiological, traffic flow and environmental factors

W Wei, X Fu, S Zhong, H Ge - … research part F: traffic psychology and …, 2023 - Elsevier
During the dynamic driving process, classification of mental workload for drivers is a
complex task due to multiple factors, including human, vehicle, road, and the environment …

Biosignals in human factors research for heavy equipment operators: A review of available methods and their feasibility in laboratory and ambulatory studies

A Hekmatmanesh, V Zhidchenko, K Kauranen… - IEEE …, 2021 - ieeexplore.ieee.org
Heavy equipment operation is a responsible and difficult task causing mental workload on a
human operator and exposing the operator to a range of harmful factors. Human factors and …

[HTML][HTML] Deep learning-based drivers emotion classification system in time series data for remote applications

RA Naqvi, M Arsalan, A Rehman, AU Rehman… - Remote Sensing, 2020 - mdpi.com
Aggressive driving emotions is indeed one of the major causes for traffic accidents
throughout the world. Real-time classification in time series data of abnormal and normal …

XGBoost algorithm-based monitoring model for urban driving stress: Combining driving behaviour, driving environment, and route familiarity

Y Lu, X Fu, E Guo, F Tang - IEEE Access, 2021 - ieeexplore.ieee.org
Stress is considered by many studies to affect traffic safety, and many researchers have
attempted to monitor the dynamics of driving stress. Previous research has relied …

The association between physiological and eye-tracking metrics and cognitive load in drivers: A meta-analysis

A Wang, C Huang, J Wang, D He - … Research Part F: Traffic Psychology and …, 2024 - Elsevier
Driving performance can be impaired by a high cognitive load of drivers. Thus, it is important
to estimate drivers' cognitive load. Although physiological and eye-tracking metrics have …

[HTML][HTML] A novel mutual information based feature set for drivers' mental workload evaluation using machine learning

MR Islam, S Barua, MU Ahmed, S Begum, P Aricò… - Brain Sciences, 2020 - mdpi.com
Analysis of physiological signals, electroencephalography more specifically, is considered a
very promising technique to obtain objective measures for mental workload evaluation …

Cognitive Workload Estimation in Conditionally Automated Vehicles Using Transformer Networks Based on Physiological Signals

A Wang, J Wang, W Shi, D He - Transportation Research …, 2024 - journals.sagepub.com
Though driving automation promises to improve driving safety, drivers are still required to be
ready to retake control in conditionally automated vehicles, which are defined by the Society …