In the high-attention-demanding environment of underground coal mines, distraction is a major cause of unsafe behavior and decreased safety performance. Research on the cognitive neural mechanisms and monitoring of distraction in miners is limited. T...
Previous studies have focused on the impact of individual factors on lane departure warning (LDW) utility during driving. However, comprehensive analysis has not been considered based on multiple variables, such as driver characteristics. This paper...
Recently, studies on driver inattention state recognition as an advanced mobility application technology are being actively conducted to prevent traffic accidents caused by driver drowsiness and distraction. The driver inattention state recognition s...
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 a...
Driver distraction and fatigue are among the leading contributing factors in various fatal accidents. Driver activity monitoring can effectively reduce the number of roadway accidents. Besides the traditional methods that rely on camera or wearable d...
Distracted human driver detection is an important feature that should be included in most levels of autonomous cars, because most of these are still under development. Hereby, this paper proposes an architecture to perform this task in a fast and acc...
In the realm of intelligent vehicles, gestures can be characterized for promoting automotive interfaces to control in-vehicle functions without diverting the driver’s visual attention from the road. Driver gesture recognition has gained more at...
Driver distraction remains a critical factor in road accidents, necessitating intelligent systems for real-time detection. This study introduces a novel fNIRS-based method to to classify varying levels of driver distraction across diverse simulated s...
Electroencephalogram (EEG) was used to analyze the mechanisms and differences in brain neural activity of drivers in visual, auditory, and cognitive distracted vs. normal driving emergency braking conditions. A pedestrian intrusion emergency braking...
The use of mobile phones has become one of the major threats to road safety, especially in young novice drivers. To avoid crashes induced by distraction, adaptive distraction mitigation systems have been developed that can determine how to detect a d...
The present study utilizes the significant differences in θ, α, and β band power spectra observed in electroencephalograms (EEGs) during distracted versus focused driving. Three subtasks, visual distraction, auditory distraction, and...
In the last decade, distraction detection of a driver gained a lot of significance due to increases in the number of accidents. Many solutions, such as feature based, statistical, holistic, etc., have been proposed to solve this problem. With the adv...
One of the main reasons for fatal accidents on the road is distracted driving. The continuous attention of an individual driver is a necessity for the task of driving. While driving, certain levels of distraction can cause drivers to lose their atten...
The increasing number of car accidents is a significant issue in current transportation systems. According to the World Health Organization (WHO), road accidents are the eighth highest top cause of death around the world. More than 80% of road accide...
Based on the impact of industry extreme return on the attention of institutional investors, taking Chinese A-share listed companies from 2011 to 2020 as a sample, this paper empirically tests the relationship between institutional investors’ di...
Driver distraction is a well-known cause for traffic collisions worldwide. Studies have indicated that shared steering control, which actively provides haptic guidance torque on the steering wheel, effectively improves the performance of distracted d...
The accurate and prompt recognition of a driver’s cognitive distraction state is of great significance to intelligent driving systems (IDSs) and human-autonomous collaboration systems (HACSs). Once the driver’s distraction status has been...
Background/Objectives: Audio and audiovisual distraction can be effective additive tools to reduce anxiety and pain in patients receiving outpatient procedures (OP). Audiovisual distraction tools already showed positive effects on pain perception in...
With regard to autonomous driving, on-road projections cannot only be used for communication with the driver but also with other road users. Our study aims to investigate the distraction potential for other road users when on-road projections (e.g.,...
Driver distraction has become a leading cause of traffic crashes. Visual distraction has the most direct impact on driving safety among various driver distractions. If the driver’s line of sight deviates from the road in front, there will be a...
In recent years, the number of deaths and injuries resulting from traffic accidents has been increasing dramatically all over the world due to distracted drivers. Thus, a key element in developing intelligent vehicles and safe roads is monitoring dri...
In this paper, we propose a portable device named SOMN_IA, to detect drowsiness and distraction in drivers. The SOMN_IA can be installed inside of any type of vehicle, and it operates in real time, alerting the dangerous state caused by drowsiness an...
In response to negative impacts such as personal and property safety hazards caused by drivers being distracted while driving on the road, this article proposes a driver’s attention state-detection method based on the improved You Only Look Onc...
Distracted driving remains a major concern on highways, with it contributing to severe and fatal crashes, particularly on high-speed routes, prompting numerous states to implement targeted initiatives aimed at combating traffic violations that signif...
Studies assessing the association between hunger and psychological states have been conducted in laboratory settings, or limited to persons with eating disorders. In this study, 748 community-dwelling adults (56.4% women, 60.0 ± 9.3 years) com...
Many factors affect road safety, but research constantly shows that drivers are the major cause of critical situations that could potentially lead to a traffic accident in road traffic. Visual information is a crucial part of input information into t...
Background: Type 1 basilar invagination (BI) is caused by a structural instability at the craniovertebral junction (CVJ) and has been historically treated with distraction and stabilization through fusion of the C1–C2 vertebrae. Recent advances...
This paper introduces a comprehensive framework for the detection of behaviors indicative of reduced concentration levels among motor vehicle operators, leveraging multimodal image data. By integrating dedicated deep learning models, our approach sys...
Over the last decade, a driver’s distraction has gained popularity due to its increased significance and high impact on road accidents. Various factors, such as mood disorder, anxiety, nervousness, illness, loud music, and driver’s head r...
Driver distraction is considered a main cause of road accidents, every year, thousands of people obtain serious injuries, and most of them lose their lives. In addition, a continuous increase can be found in road accidents due to driver’s distr...
Detecting the factors affecting drivers’ safe driving and taking early warning measures can effectively reduce the probability of automobile safety accidents and improve vehicle driving safety. Considering the two factors of driver fatigue and...
Distracted driving is currently a global issue causing fatal traffic crashes and injuries. Although deep learning has achieved significant success in various fields, it still faces the trade-off between computation cost and overall accuracy in the fi...
Driver distraction detection not only helps to improve road safety and prevent traffic accidents, but also promotes the development of intelligent transportation systems, which is of great significance for creating a safer and more efficient transpor...
Driver distraction detection not only effectively prevents traffic accidents but also promotes the development of intelligent transportation systems. In recent years, thanks to the powerful feature learning capabilities of deep learning algorithms, d...
Road traffic accidents regarding commercial vehicles have been demonstrated as an important culprit restricting the steady development of the social economy, which are closely related to the distracted behavior of drivers. However, the existing drive...
6 September 2022
This study compared Romanian college students’ off-task use of digital devices in online courses with their digital distractions in face-to-face courses. Students taking both online and face-to-face courses completed surveys assessing off-task...
This study examines how Internet Addiction (IA) and negative affect relate to everyday memory lapses in Portuguese students and teachers. A cross-sectional sample of 254 participants (167 youth aged < 25 years and 87 adults aged ≥ 25 years) com...
Music is believed to aid the implementation of emotion regulation strategies like distraction or reappraisal, but empirical studies have shown null results. However, the moderating role of one’s relation with music (musical sophistication) and/...
Cognitive failures represent everyday task failures that individuals are normally capable of completing. While cognitive failures measured with the Cognitive Failures Questionnaire can be considered a trait, the psychophysiological states associated...
This tutorial describes the necessary steps for designing and conducting a perception experiment in order to obtain design parameters for human–machine interactions. It is intended for engineers and product designers, which require design parameters...
This paper addresses the
Bus driver distraction and cognitive load lead to higher accident risk. Driver distraction sources and complex physical and psychological effects must be recognized and analyzed in real-world driving conditions to reduce risk and enhance overall road...
Oil is currently over-represented in the energy humanities, a state of affairs I describe as petromyopia. While oil constitutes a vital source of energy in the modern world, focusing too heavily on petroleum can distract scholars from giving proper a...
25 April 2019
Distracted driving behaviors are closely related to crash risk, with the use of mobile phones during driving being one of the leading causes of accidents. This paper attempts to investigate the impact of cell phone use while driving on drivers’...
Driver distraction has become a critical factor in traffic accidents, necessitating accurate behavior recognition for road safety. However, existing methods still suffer from limitations such as low accuracy in recognizing drivers’ localized ac...
Drowning is a major health issue worldwide. The World Health Organization’s global report on drowning states that the highest rates of drowning deaths occur among children aged 1–4 years, followed by children aged 5–9 years. Young c...
29 October 2021
Ankle joint distraction (AJD) has been described to be a valuable joint-sparing alternative to arthrodesis or arthroplasty; however, clinical endpoints associated to this surgical intervention are lacking. The current case report describes clinical a...
With the rapid increase in the number of drivers, traffic accidents due to driver distraction is a major threat around the world. In this paper, we present a novel long-term recurrent convolutional network (LRCN) model for real-time driver activity r...
Physical fatigue is frequent for heavy manual laborers like construction workers, but it causes distraction and may lead to safety incidents. The purpose of this study is to develop predictive models for monitoring construction workers’ inatten...
Emotion perception frequently involves the integration of visual and auditory information. During multisensory emotion perception, the attention devoted to each modality can be measured by calculating the difference between trials in which the facial...
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