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 …

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 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 …

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 …

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 …

[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 …

[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 …

[HTML][HTML] Machine learning models and videos of facial regions for estimating heart rate: a review on patents, datasets, and literature

TP Pagano, VR Santos, YS Bonfim, JVD Paranhos… - Electronics, 2022 - mdpi.com
Estimating heart rate is important for monitoring users in various situations. Estimates based
on facial videos are increasingly being researched because they allow the monitoring of …

[PDF][PDF] 自适应自动驾驶等级的驾驶人状态监测模型研究

黄晶, 陈紫琳, 杨梦婷, 彭晓燕 - 机械工程学报, 2023 - qikan.cmes.org
自动驾驶等级的逐级提升意味着驾驶执行权从驾驶人向车辆自动控制系统逐渐转移,
驾驶人所承担的责任也随之发生变化. 大量研究表明, 自动驾驶车辆驾驶人的注意力跨度与行驶 …