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A Comprehensive Survey of Driving Monitoring and Assistance Systems
Improving a vehicle driver’s performance decreases the damage caused by, and chances of, road accidents. In recent decades, engineers and researchers have proposed several strategies to model and improve driving monitoring and assistance systems ...
Muhammad Qasim Khan, Sukhan Lee
doaj +1 more source
The box task - a method for assessing in-vehicle system demand
The use of advanced in-vehicle information systems (IVIS) and other complex devices such as smartphones while driving can lead to driver distraction, which, in turn, increases safety-critical event risk.
Daniel Trommler +5 more
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Driver Distraction Using Visual-Based Sensors and Algorithms
Driver distraction, defined as the diversion of attention away from activities critical for safe driving toward a competing activity, is increasingly recognized as a significant source of injuries and fatalities on the roadway.
Alberto Fernández +3 more
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Multimodel System for Driver Distraction Detection and Elimination
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.
Abdulrahman AbouOuf +5 more
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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 to the low level of vehicle ...
Taiguo Li +3 more
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Detection of Driving Distractions and Their Impacts
For decades, road crashes have caused many deaths and injuries and generally have had a severe social and economic impact on societies. According to studies, driver distraction has led to an increase in driving-related risks.
Arian Shajari +7 more
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Monitoring Distracted Driving Behaviours with Smartphones: An Extended Systematic Literature Review
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
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Driver distraction remains one of the leading causes of traffic accidents. Although deep learning approaches such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers have been extensively applied for distracted ...
Zhuo He, Chengming Chen, Xiaoyi Zhou
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Dual-Flow Driver Distraction Driving Detection Model Based on Sobel Edge Detection
Cognitive or visual distraction caused by drivers using mobile phones, operating the central console, or conversing with passengers while driving is a significant contributing factor to road traffic accidents.
Binbin Qin, Bolin Zhang
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ABSTRACT Background Acute lymphoblastic leukaemia (ALL) is one of the most treatable forms of paediatric cancer; however, there is a substantial burden of treatment‐related toxicities (TRTs). In addition, the long‐term changes in children's health‐related quality of life (HRQoL) due to toxic treatments are not well understood.
Clare Ghows +19 more
wiley +1 more source

