Using naturalistic driving study data to investigate the impact of driver distraction on driver's brake reaction time in freeway rear-end events in car-following situation.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of safety research"
DOI: 10.1016/j.jsr.2017.10.012
Abstract: INTRODUCTION The rear-end crash is one of the most common freeway crash types, and driver distraction is often cited as a leading cause of rear-end crashes. Previous research indicates that driver distraction could have negative… read more here.
Keywords: reaction time; driver distraction; reaction; distraction ... See more keywords
Driver distraction and inattention in the realm of automated driving
Sign Up to like & getrecommendations! Published in 2017 at "Iet Intelligent Transport Systems"
DOI: 10.1049/iet-its.2017.0232
Abstract: Despite the increasing number of automated systems that have been introduced in vehicles over the past decade, highly automated vehicles are not yet capable of driving reliably and safely in all traffic scenarios and conditions.… read more here.
Keywords: driver distraction; distraction inattention; inattention; distraction ... See more keywords
Driver distraction and fatigue detection in images using ME‐YOLOv8 algorithm
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DOI: 10.1049/itr2.12560
Abstract: Driving while inattentive or fatigued significantly contributes to traffic accidents and puts road users at a significantly higher risk of collision. The rise in road accidents due to driver inattention resulting from distractive objects, for… read more here.
Keywords: detection; distraction fatigue; fatigue detection; driver distraction ... See more keywords
CRNet: A Driver Distraction Detection Model Based on Cascaded ResNet Networks and Attention Mechanisms
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DOI: 10.1049/itr2.70106
Abstract: In order to solve the problem of excessive model parameters and low real‐time performance in driver distraction driving detection tasks, this work proposes a detection model based on cascaded convolutional network and attention mechanism. The… read more here.
Keywords: detection; attention; model; driver distraction ... See more keywords
Usability Testing of Three Visual HMIs for Assisted Driving: How Design Impacts Driver Distraction and Mental Models.
Sign Up to like & getrecommendations! Published in 2022 at "Ergonomics"
DOI: 10.1080/00140139.2022.2136766
Abstract: There is a variety of visual human-machine interfaces (HMI) designed across vehicle manufacturers that support drivers while supervising driving automation features, such as adaptive cruise control (ACC). These various designs communicate the same limited amount… read more here.
Keywords: system; mental models; driver distraction; design ... See more keywords
Dynamic is optimal: Effect of three alternative auto-complete on the usability of in-vehicle dialing displays and driver distraction
Sign Up to like & getrecommendations! Published in 2021 at "Traffic Injury Prevention"
DOI: 10.1080/15389588.2021.2010052
Abstract: Abstract Objective Auto-complete (AC) has become ubiquitous on domain-specific systems and is mainly divided into two types (static-AC and dynamic-AC). Specifically, static-AC only presents the possible completions not changing with user input in the suggestion… read more here.
Keywords: vehicle; vehicle dialing; dialing displays; effect ... See more keywords
Address inputting while driving: a comparison of four alternative text input methods on in-vehicle navigation displays usability and driver distraction
Sign Up to like & getrecommendations! Published in 2022 at "Traffic Injury Prevention"
DOI: 10.1080/15389588.2022.2047958
Abstract: Abstract Objective Efficient and safe address entry is crucial to in-vehicle navigation systems. Although various text input methods (TIMs) are commercially available, to date, the details of the driver’s interactions with these TIMs in the… read more here.
Keywords: driver distraction; four alternative; vehicle navigation; vehicle ... See more keywords
The effects of age on crash risk associated with driver distraction.
Sign Up to like & getrecommendations! Published in 2017 at "International journal of epidemiology"
DOI: 10.1093/ije/dyw234
Abstract: Background Driver distraction is a major contributing factor to crashes, which are the leading cause of death for the US population under 35 years of age. The prevalence of secondary-task engagement and its impacts on… read more here.
Keywords: secondary task; driver distraction; age; secondary tasks ... See more keywords
Multimodel System for Driver Distraction Detection and Elimination
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DOI: 10.1109/access.2022.3188715
Abstract: On average 3,700 people lose their lives on roads every day due to car accidents as a result of drivers’ distraction. In this research, a proposed hybrid approach is presented. The approach is based on… read more here.
Keywords: driver distraction; distraction; car; detection ... See more keywords
AB-DLM: An Improved Deep Learning Model Based on Attention Mechanism and BiFPN for Driver Distraction Behavior Detection
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DOI: 10.1109/access.2022.3197146
Abstract: Driver distraction behavior causes a large number of traffic accidents every year, resulting in economic losses and injuries. Currently, the driver still plays an important role in the driving and control of the vehicle due… read more here.
Keywords: attention; detection; model; driver distraction ... See more keywords
CEAM-YOLOv7: Improved YOLOv7 Based on Channel Expansion and Attention Mechanism for Driver Distraction Behavior Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3228331
Abstract: Driver distraction behavior is prone to induce traffic accidents. Therefore, it is necessary to detect it to caution drivers in time for traffic safety. In driver behavior recognition, the diversity of behaviors and driving environment… read more here.
Keywords: ceam yolov7; detection; yolov7; driver distraction ... See more keywords