Results 21 to 30 of about 109,274 (257)
Temporal Dashboard Gaze Variance (TDGV) Changes for Measuring Cognitive Distraction While Driving
Sensors, 2022 A difficult challenge for today’s driver monitoring systems is the detection of cognitive distraction. The present research presents the development of a theory-driven approach for cognitive distraction detection during manual driving based on temporal ...
Cyril Marx +2 more
doaj +1 more source
Driver Health Monitoring System
International Journal for Research in Applied Science and Engineering Technology, 2022 Abstract: All over the world, most of the road accidents are occurred by driving and some rash driving due to health issues. The main concept of this paper is to prevent the road accident so to prevent the road accident we are using smart glasses and some IOT based small user-friendly devices.
Vidhya Balakrishnan +2 more
openaire +1 more source
European NCAP Program Developments to Address Driver Distraction, Drowsiness and Sudden Sickness
Frontiers in Neuroergonomics, 2021 Driver distraction and drowsiness remain significant contributors to death and serious injury on our roads and are long standing issues in road safety strategies around the world.
Rikard Fredriksson +7 more
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Driving Behavior during Takeover Request of Autonomous Vehicle: Effect of Driver Postures
Behavioral Sciences, 2022 We investigated the effect of driver posture on driving control following a takeover request (TOR) from autonomous to manual driving in level 3 autonomous vehicles.
Koki Muto +3 more
doaj +1 more source
Sensors, 2022 Estimating the driver’s gaze in a natural real-world setting can be problematic for different challenging scenario conditions. For example, faces will undergo facial occlusions, illumination, or various face positions while driving.
Catherine Lollett +2 more
doaj +1 more source
Driver Distraction Detection Methods: A Literature Review and Framework
IEEE Access, 2021 Driver inattention and distraction are the main causes of road accidents, many of which result in fatalities. To reduce road accidents, the development of information systems to detect driver inattention and distraction is essential.
Alexey Kashevnik +3 more
doaj +1 more source
Drowsy Driver Monitoring System
, 2022 One of the leading causes of traffic accidents and fatalities is drowsiness while driving. Driver drowsiness detection and indication is therefore an active research area. Most of the conventional methods are either vehicle based, behavioral based or physiological-based.
Dr.Subba Reddy Borra +3 more
openaire +1 more source
Information, 2022 Vehicles equipped with so-called partially automated driving functions are becoming more and more common nowadays. The special feature of this automation level is that the driver is relieved of the execution of the lateral and longitudinal driving task ...
Nadja Schömig +3 more
doaj +1 more source
Monitoring Distracted Driving Behaviours with Smartphones: An Extended Systematic Literature Review
Sensors, 2023 Driver behaviour monitoring is a broad area of research, with a variety of methods and approaches. Distraction from the use of electronic devices, such as smartphones for texting or talking on the phone, is one of the leading causes of vehicle accidents.
Efi Papatheocharous +3 more
doaj +1 more source
Drowsiness Detection System Through Eye and Mouth Analysis
JOIV: International Journal on Informatics Visualization, 2023 Traffic jams are one of the serious issues in many developed countries. After the pandemic, many employees were allowed to travel interstate to work. This contributes to more severe jams, especially in the capital and nearby states. Long-distance driving
Bey-Ee Belle Lim, Kok Why Ng, Sew Lai Ng
doaj +1 more source