Results 1 to 10 of about 249,287 (216)

Survey and Synthesis of State of the Art in Driver Monitoring

Sensors, 2021
Road vehicle accidents are mostly due to human errors, and many such accidents could be avoided by continuously monitoring the driver. Driver monitoring (DM) is a topic of growing interest in the automotive industry, and it will remain relevant for all ...
Anaïs Halin, Jacques G. Verly, Marc Van Droogenbroeck   +2 more
doaj   +3 more sources

DriverSVT: Smartphone-Measured Vehicle Telemetry Data for Driver State Identification

Data, 2022
One of the key functions of driver monitoring systems is the evaluation of the driver’s state, which is a key factor in improving driving safety. Currently, such systems heavily rely on the technology of deep learning, that in turn requires corresponding
Walaa Othman, Alexey Kashevnik, Batol Hamoud, Nikolay Shilov   +3 more
doaj   +3 more sources

Non-Intrusive Contact Respiratory Sensor for Vehicles

Sensors, 2022
In this work, we propose a low-cost solution capable of collecting the driver’s respiratory signal in a robust and non-intrusive way by contact with the chest and abdomen.
Quentin Meteier, Michiel Kindt, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini   +4 more
doaj   +1 more source

Drowsiness Mitigation Through Driver State Monitoring Systems: A Scoping Review. [PDF]

Hum Factors
Ayas S, Donmez B, Tang X.
europepmc   +2 more sources

Carrying a passenger and relaxation before driving: Classification of young drivers’ physiological activation

Physiological Reports, 2022
Drivers are often held responsible for road crashes. Previous research has shown that stressors such as carrying passengers in the vehicle can be a source of accidents for young drivers.
Quentin Meteier, Marine Capallera, Emmanuel De Salis, Marino Widmer, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini, Andreas Sonderegger   +7 more
doaj   +1 more source

An Integrated Framework for Multi-State Driver Monitoring Using Heterogeneous Loss and Attention-Based Feature Decoupling

Sensors, 2022
Multi-state driver monitoring is a key technique in building human-centric intelligent driving systems. This paper presents an integrated visual-based multi-state driver monitoring framework that incorporates head rotation, gaze, blinking, and yawning ...
Zhongxu Hu, Yiran Zhang, Yang Xing, Qinghua Li, Chen Lv   +4 more
doaj   +1 more source

DriverMVT: In-Cabin Dataset for Driver Monitoring including Video and Vehicle Telemetry Information

Data, 2022
Developing a driver monitoring system that can assess the driver’s state is a prerequisite and a key to improving the road safety. With the success of deep learning, such systems can achieve a high accuracy if corresponding high-quality datasets are ...
Walaa Othman, Alexey Kashevnik, Ammar Ali, Nikolay Shilov   +3 more
doaj   +1 more source

Assessment of the Potential of Wrist-Worn Wearable Sensors for Driver Drowsiness Detection

Sensors, 2020
Drowsy driving imposes a high safety risk. Current systems often use driving behavior parameters for driver drowsiness detection. The continuous driving automation reduces the availability of these parameters, therefore reducing the scope of such methods.
Thomas Kundinger, Nikoletta Sofra, Andreas Riener   +2 more
doaj   +1 more source

EEG and ECG-Based Multi-Sensor Fusion Computing for Real-Time Fatigue Driving Recognition Based on Feedback Mechanism

Sensors, 2023
A variety of technologies that could enhance driving safety are being actively explored, with the aim of reducing traffic accidents by accurately recognizing the driver’s state.
Ling Wang, Fangjie Song, Tie Hua Zhou, Jiayu Hao, Keun Ho Ryu   +4 more
doaj   +1 more source

Measuring Drivers’ Physiological Response to Different Vehicle Controllers in Highly Automated Driving (HAD): Opportunities for Establishing Real-Time Values of Driver Discomfort

Information, 2020
This study investigated how driver discomfort was influenced by different types of automated vehicle (AV) controllers, compared to manual driving, and whether this response changed in different road environments, using heart-rate variability (HRV) and ...
Vishnu Radhakrishnan, Natasha Merat, Tyron Louw, Michael G. Lenné, Richard Romano, Evangelos Paschalidis, Foroogh Hajiseyedjavadi, Chongfeng Wei, Erwin R. Boer   +8 more
doaj   +1 more source