[HTML][HTML] Thirty years of research on driving behavior active intervention: A bibliometric overview
M Yang, Q Bao, Y Shen, Q Qu - Journal of traffic and transportation …, 2023 - Elsevier
To better understand the research focus and development direction in the field of driving
behavior active intervention, thereby laying a scientific foundation for further research, we …
behavior active intervention, thereby laying a scientific foundation for further research, we …
DADA: Driver attention prediction in driving accident scenarios
Driver attention prediction is becoming an essential research problem in human-like driving
systems. This work makes an attempt to predict the d river a ttention in d riving a ccident …
systems. This work makes an attempt to predict the d river a ttention in d riving a ccident …
NeuroIV: Neuromorphic vision meets intelligent vehicle towards safe driving with a new database and baseline evaluations
Neuromorphic vision sensors such as the Dynamic and Active-pixel Vision Sensor (DAVIS)
using silicon retina are inspired by biological vision, they generate streams of asynchronous …
using silicon retina are inspired by biological vision, they generate streams of asynchronous …
A multimodal deep neural network for prediction of the driver's focus of attention based on anthropomorphic attention mechanism and prior knowledge
R Fu, T Huang, M Li, Q Sun, Y Chen - Expert Systems with Applications, 2023 - Elsevier
The prediction of the driver's focus of attention (DFoA) is becoming essential research for the
driver distraction detection and intelligent vehicle. Therefore, this work makes an attempt to …
driver distraction detection and intelligent vehicle. Therefore, this work makes an attempt to …
How to select distracted driving countermeasures evaluation metrics: A systematic review
While there are numerous performance metrics that have been developed for the evaluation
of distracted driving prevention programs, there is little information on how to select them …
of distracted driving prevention programs, there is little information on how to select them …
Driver distraction detection based on the true driver's focus of attention
T Huang, R Fu - IEEE transactions on intelligent transportation …, 2022 - ieeexplore.ieee.org
Effective driver distraction detection (DDD) can significantly improve driving safety. Inspired
by the definition of driver distraction, this work aims to detect driver distraction based on the …
by the definition of driver distraction, this work aims to detect driver distraction based on the …
[HTML][HTML] Understanding the contributing factors to young driver crashes: A comparison of crash profiles of three age groups
Despite the adoption of the Graduated Driver Licensing (GDL) in 1998, the
disproportionately high rate of young driver (15–24 years) crashes is still prevalent on …
disproportionately high rate of young driver (15–24 years) crashes is still prevalent on …
Risky behaviors and road safety: An exploration of age and gender influences on road accident rates
Human behavior is a dominant factor in road accidents, contributing to more than 70% of
such incidents. However, gathering detailed data on individual drivers' behavior is a …
such incidents. However, gathering detailed data on individual drivers' behavior is a …
[HTML][HTML] Driver behavior and the use of automation in real-world driving
Background The emergence of partial-automation in consumer vehicles is reshaping the
driving task, the driver role, and subsequent driver behavior. When using partial-automation …
driving task, the driver role, and subsequent driver behavior. When using partial-automation …
[HTML][HTML] Application of machine learning models and SHAP to examine crashes involving young drivers in New Jersey
Motor vehicle crashes are the leading cause of the death of teenagers in the United States.
Young drivers have shown a higher propensity to get involved in crashes due to using a …
Young drivers have shown a higher propensity to get involved in crashes due to using a …