[HTML][HTML] Gaze and eye tracking: Techniques and applications in ADAS
MQ Khan, S Lee - Sensors, 2019 - mdpi.com
Tracking drivers' eyes and gazes is a topic of great interest in the research of advanced
driving assistance systems (ADAS). It is especially a matter of serious discussion among the …
driving assistance systems (ADAS). It is especially a matter of serious discussion among the …
Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …
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 …
detect driver inattention is essential in building a safe yet intelligent transportation system …
Bayesian network modeling of accident investigation reports for aviation safety assessment
X Zhang, S Mahadevan - Reliability Engineering & System Safety, 2021 - Elsevier
Safety assurance is of paramount importance in the air transportation system. In this paper,
we analyze the historical passenger airline accidents that happened from 1982 to 2006 as …
we analyze the historical passenger airline accidents that happened from 1982 to 2006 as …
A temporal–spatial deep learning approach for driver distraction detection based on EEG signals
Distracted driving has been recognized as a major challenge to traffic safety improvement.
This article presents a novel driving distraction detection method that is based on a new …
This article presents a novel driving distraction detection method that is based on a new …
Driver distraction detection based on vehicle dynamics using naturalistic driving data
Distracted driving such as phone use during driving is risky, as it increases the probability of
severe crashes. Detecting distraction using Naturalistic Driving Studies was attempted in …
severe crashes. Detecting distraction using Naturalistic Driving Studies was attempted in …
Driver distraction detection using semi-supervised machine learning
Real-time driver distraction detection is the core to many distraction countermeasures and
fundamental for constructing a driver-centered driver assistance system. While data-driven …
fundamental for constructing a driver-centered driver assistance system. While data-driven …
A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes
Rear-end crash is one of the most common types of traffic crashes in the US A good
understanding of its characteristics and contributing factors is of practical importance …
understanding of its characteristics and contributing factors is of practical importance …
Identification and analysis of driver postures for in-vehicle driving activities and secondary tasks recognition
Driver decisions and behaviors regarding the surrounding traffic are critical to traffic safety. It
is important for an intelligent vehicle to understand driver behavior and assist in driving tasks …
is important for an intelligent vehicle to understand driver behavior and assist in driving tasks …
A dynamic Bayesian network model for real-time crash prediction using traffic speed conditions data
Traffic crashes occurring on freeways/expressways are considered to relate closely to
previous traffic conditions, which are time-varying. Meanwhile, most studies use …
previous traffic conditions, which are time-varying. Meanwhile, most studies use …
[HTML][HTML] 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 …
driving toward a competing activity, is increasingly recognized as a significant source of …