Attention for vision-based assistive and automated driving: A review of algorithms and datasets
I Kotseruba, JK Tsotsos - IEEE transactions on intelligent …, 2022 - ieeexplore.ieee.org
Driving safety has been a concern since the first cars appeared on the streets. Driver
inattention has been singled out as a major cause of accidents early on. This is hardly …
inattention has been singled out as a major cause of accidents early on. This is hardly …
Drivers' visual scanning behavior at signalized and unsignalized intersections: A naturalistic driving study in China
Introduction: Intersections are the most dangerous locations in urban traffic. The present
study aims to investigate drivers' visual scanning behavior at signalized and unsignalized …
study aims to investigate drivers' visual scanning behavior at signalized and unsignalized …
Autonomous vehicle interactions in the urban street environment: A research agenda
The Venturer project is trialling an autonomous vehicle (AV) in the context of use on urban
roads. This paper summarises a literature review undertaken to assist in developing a …
roads. This paper summarises a literature review undertaken to assist in developing a …
Deep reinforcement learning enabled decision-making for autonomous driving at intersections
Road intersection is one of the most complex and accident-prone traffic scenarios, so it's
challenging for autonomous vehicles (AVs) to make safe and efficient decisions at the …
challenging for autonomous vehicles (AVs) to make safe and efficient decisions at the …
Continuous decision‐making for autonomous driving at intersections using deep deterministic policy gradient
Intersections have been identified as the most complex and accident‐prone traffic scenarios
on road. Making appropriate decisions at intersections for driving safety, efficiency, and …
on road. Making appropriate decisions at intersections for driving safety, efficiency, and …
Approaching intersections: Gaze behavior of drivers depending on traffic, intersection type, driving maneuver, and secondary task involvement
Urban intersections are hotspots for crashes because they provide a location for several
traffic streams and types of road users to cross. A main cause of crashes is the …
traffic streams and types of road users to cross. A main cause of crashes is the …
Systematic observation of an expert driver's gaze strategy—an on-road case study
In this paper we present and qualitatively analyze an expert driver's gaze behavior in natural
driving on a real road, with no specific experimental task or instruction. Previous eye tracking …
driving on a real road, with no specific experimental task or instruction. Previous eye tracking …
Learning automated driving in complex intersection scenarios based on camera sensors: A deep reinforcement learning approach
Making proper decisions at intersections that are one of the most dangerous and
sophisticated driving scenarios is full of challenges, especially for autonomous vehicles …
sophisticated driving scenarios is full of challenges, especially for autonomous vehicles …
A survey of eye tracking in automobile and aviation studies: Implications for eye-tracking studies in marine operations
In the last decade researchers have increasingly considered eye tracking of the operators of
cars and airplanes as a means to address human error and evaluate operational …
cars and airplanes as a means to address human error and evaluate operational …
Drivers' visual attention: A field study at intersections
Crossing a road intersection, a driver must collect visual information from various locations.
The allocation of visual attention, which allows this collection, mainly relies on top-down …
The allocation of visual attention, which allows this collection, mainly relies on top-down …