A survey on vision-based driver distraction analysis

W Li, J Huang, G Xie, F Karray, R Li - Journal of Systems Architecture, 2021 - Elsevier
Motor vehicle crashes are great threats to our life, which may result in numerous fatalities, as
well as tremendous economic and societal costs. Driver inattention, either distraction or …

Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …

HV Koay, JH Chuah, CO Chow, YL Chang - Engineering Applications of …, 2022 - Elsevier
Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …

Computer vision‐based recognition of driver distraction: A review

N Moslemi, M Soryani, R Azmi - Concurrency and Computation …, 2021 - Wiley Online Library
Vehicle crash rates caused by distracted driving have been rising in recent years. Hence,
safety while driving on roads is today a crucial concern across the world. Some of the …

[HTML][HTML] EFFNet-CA: an efficient driver distraction detection based on multiscale features extractions and channel attention mechanism

T Khan, G Choi, S Lee - Sensors, 2023 - mdpi.com
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 …

[HTML][HTML] Survey of cooperative advanced driver assistance systems: from a holistic and systemic vision

JF González-Saavedra, M Figueroa, S Céspedes… - Sensors, 2022 - mdpi.com
The design of cooperative advanced driver assistance systems (C-ADAS) involves a holistic
and systemic vision that considers the bidirectional interaction among three main elements …

A smart analysis of driver fatigue and drowsiness detection using convolutional neural networks

AA Minhas, S Jabbar, M Farhan… - Multimedia Tools and …, 2022 - Springer
Automotive industry experiences multiple injuries in our everyday life. The increasing road
accident rate is due to driver drowsiness, such as fatigue and insomnia. This research is …

[HTML][HTML] Towards Efficient Risky Driving Detection: A Benchmark and a Semi-Supervised Model

Q Cheng, H Li, Y Yang, J Ling, X Huang - Sensors, 2024 - mdpi.com
Risky driving is a major factor in traffic incidents, necessitating constant monitoring and
prevention through Intelligent Transportation Systems (ITS). Despite recent progress, a lack …

[HTML][HTML] Monitoring distracted driving behaviours with smartphones: an extended systematic literature review

E Papatheocharous, C Kaiser, J Moser, A Stocker - Sensors, 2023 - mdpi.com
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 …

Distributed edge-based video analytics on the move

J King, YC Lee - arXiv preprint arXiv:2206.14414, 2022 - arxiv.org
In recent years, we have witnessed an explosive growth of data. Much of this data is video
data generated by security cameras, smartphones, and dash cams. The timely analysis of …

Distracted driver monitoring with smartphones: A preliminary literature review

C Kaiser, A Stocker… - 2021 29th Conference of …, 2021 - ieeexplore.ieee.org
Distracted driving is known to be one of the leading causes of vehicle accidents. With the
increase in the number of sensors available within vehicles, there exists an abundance of …