A survey on driver behavior analysis from in-vehicle cameras

J Wang, W Chai, A Venkatachalapathy… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Distracted or drowsy driving is unsafe driving behavior responsible for thousands of crashes
every year. Studying driver behavior has challenges associated with observing drivers in …

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 …

A survey on vision-based driver distraction analysis

W Li, J Huang, G **e, 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 …

E2DR: A deep learning ensemble-based driver distraction detection with recommendations model

M Aljasim, R Kashef - Sensors, 2022 - mdpi.com
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 …

CAT-CapsNet: A convolutional and attention based capsule network to detect the driver's distraction

H Mittal, B Verma - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Worldwide inflation in the count of road accidents has raised an alarming scenario wherein
driver distraction is identified as one of the main causes. According to the National Highway …

[HTML][HTML] Real-time driver distraction recognition: A hybrid genetic deep network based approach

AA Aljohani - Alexandria Engineering Journal, 2023 - Elsevier
Distracting while driving is a serious issue that causes serious direct and indirect harm to the
society. To avoid these problems, detecting dangerous drivers' behaviour is very important …

CBAM VGG16: an efficient driver distraction classification using CBAM embedded VGG16 architecture

CH Praharsha, A Poulose - Computers in biology and medicine, 2024 - Elsevier
Driver monitoring systems (DMS) are crucial in autonomous driving systems (ADS) when
users are concerned about driver/vehicle safety. In DMS, the significant influencing factor of …

Evaluating the impact of Heavy Goods Vehicle driver monitoring and coaching to reduce risky behaviour

JM Mase, S Majid, M Mesgarpour, MT Torres… - Accident Analysis & …, 2020 - Elsevier
Determining the impact of driver-monitoring technologies to improve risky driving behaviours
allows stakeholders to understand which aspects of onboard sensors and feedback need …

A new unsupervised deep learning algorithm for fine-grained detection of driver distraction

B Li, J Chen, Z Huang, H Wang, J Lv… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Traffic accidents caused by distracted drivers account for a large proportion of traffic
accidents each year, and monitoring the driving state of drivers to avoid traffic accidents …

In-vehicle sensing for smart cars

X Zeng, F Wang, B Wang, C Wu… - IEEE Open Journal of …, 2022 - ieeexplore.ieee.org
Driving safety has been attracting more and more interest due to the unprecedented
proliferation of vehicles and the subsequent increase of traffic accidents. As such the …