Driver behavior classification: A systematic literature review

S Bouhsissin, N Sael, F Benabbou - IEEE Access, 2023 - ieeexplore.ieee.org
Driver behavior is receiving increasing attention because of the staggering number of road
accidents. Many road safety reports regard human behavior as the most important factor 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 …

How did COVID-19 impact driving behaviors and crash Severity? A multigroup structural equation modeling

X Dong, K **e, H Yang - Accident Analysis & Prevention, 2022 - Elsevier
Risky driving behaviors such as speeding and failing to signal have been witnessed more
frequently during the COVID-19 pandemic, resulting in higher rates of severe crashes. This …

A review of driving style recognition methods from short-term and long-term perspectives

H Chu, H Zhuang, W Wang, X Na, L Guo… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Driving style recognition provides an effective way to understand human driving behaviors
and thereby plays an important role in the automotive sector. However, most works fail to …

Early identification and detection of driver drowsiness by hybrid machine learning

A Altameem, A Kumar, RC Poonia, S Kumar… - IEEE …, 2021 - ieeexplore.ieee.org
Drunkenness or exhaustion is a leading cause of car accidents, with severe implications for
road safety. More fatal accidents could be avoided if fatigued drivers were warned ahead of …

MTP-GO: Graph-based probabilistic multi-agent trajectory prediction with neural ODEs

T Westny, J Oskarsson, B Olofsson… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Enabling resilient autonomous motion planning requires robust predictions of surrounding
road users' future behavior. In response to this need and the associated challenges, we …

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 …

[HTML][HTML] Driver fatigue detection systems using multi-sensors, smartphone, and cloud-based computing platforms: a comparative analysis

Q Abbas, A Alsheddy - Sensors, 2021 - mdpi.com
Internet of things (IoT) cloud-based applications deliver advanced solutions for smart cities
to decrease traffic accidents caused by driver fatigue while driving on the road …

Driver drowsiness prediction based on multiple aspects using image processing techniques

VU Maheswari, R Aluvalu, MVVP Kantipudi… - IEEE …, 2022 - ieeexplore.ieee.org
The majority of the accidents were happening perpetually due to driver drowsiness over the
decades. Automation has been playing key role in many fields to provide conformity and …

[PDF][PDF] Deriving Driver Behavioral Pattern Analysis and Performance Using Neural Network Approaches.

M Malik, R Nandal, S Dalal, V Jalglan… - Intelligent Automation & …, 2022 - academia.edu
It has been observed that driver behavior has a direct and considerable impact upon factors
like fuel consumption, environmentally harmful emissions, and public safety, making it a key …