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Human Factors
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July 18, 2020
Effects of Distraction in On-Road Level 2 Automated Driving: Impacts on Glance Behavior and Takeover Performance
Shiyan Yang, Jonny Kuo, Michael G Lenné
Journal of Safety Research
|
September 26, 2015
Evaluation of a video-based measure of driver heart rate
Jonny Kuo, Sjaan Koppel, Judith L Charlton, et al.
Accident; Analysis and Prevention
|
July 27, 2014
Computer vision and driver distraction: developing a behaviour-flagging protocol for naturalistic driving data
Jonny Kuo, Sjaan Koppel, Judith L Charlton, et al.
Human Factors
|
December 6, 2021
Get Ready for Take-Overs: Using Head-Up Display for Drivers to Engage in Non-Driving-Related Tasks in Automated Vehicles
Xiaomeng Li, Ronald Schroeter, Andry Rakotonirainy, et al.
Accident; Analysis and Prevention
|
April 16, 2022
Beyond gaze fixation: Modeling peripheral vision in relation to speed, Tesla Autopilot, cognitive load, and age in highway driving
Shiyan Yang, Kyle Wilson, Trey Roady, et al.
Human Factors
|
October 15, 2020
Evaluating Driver Features for Cognitive Distraction Detection and Validation in Manual and Level 2 Automated Driving
Shiyan Yang, Kyle M Wilson, Trey Roady, et al.
Human Factors
|
May 28, 2016
Modeling Driving Performance Using In-Vehicle Speech Data From a Naturalistic Driving Study
Jonny Kuo, Judith L Charlton, Sjaan Koppel, et al.
Journal of Safety Research
|
December 6, 2017
Automated recognition of rear seat occupants' head position using Kinect™ 3D point cloud
Helen Loeb, Jinyong Kim, Kristy Arbogast, et al.
Plos One
|
November 19, 2025
Assessing data imbalance correction methods and gaze entropy for collision prediction
Courtney M Goodridge, Rafael C Gonçalves, Amélie Reher, et al.
Traffic Injury Prevention
|
September 3, 2016
Naturalistic driving study of rear seat child occupants: Quantification of head position using a Kinect™ sensor
Kristy B Arbogast, Jinyong Kim, Helen Loeb, et al.
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of 2
Search research articles
Search
Showing results (1-10 of 17) with videos related to
Sort By:
Page
of 2
Human Factors
|
July 18, 2020
Effects of Distraction in On-Road Level 2 Automated Driving: Impacts on Glance Behavior and Takeover Performance
Shiyan Yang, Jonny Kuo, Michael G Lenné
Journal of Safety Research
|
September 26, 2015
Evaluation of a video-based measure of driver heart rate
Jonny Kuo, Sjaan Koppel, Judith L Charlton, et al.
Accident; Analysis and Prevention
|
July 27, 2014
Computer vision and driver distraction: developing a behaviour-flagging protocol for naturalistic driving data
Jonny Kuo, Sjaan Koppel, Judith L Charlton, et al.
Human Factors
|
December 6, 2021
Get Ready for Take-Overs: Using Head-Up Display for Drivers to Engage in Non-Driving-Related Tasks in Automated Vehicles
Xiaomeng Li, Ronald Schroeter, Andry Rakotonirainy, et al.
Accident; Analysis and Prevention
|
April 16, 2022
Beyond gaze fixation: Modeling peripheral vision in relation to speed, Tesla Autopilot, cognitive load, and age in highway driving
Shiyan Yang, Kyle Wilson, Trey Roady, et al.
Human Factors
|
October 15, 2020
Evaluating Driver Features for Cognitive Distraction Detection and Validation in Manual and Level 2 Automated Driving
Shiyan Yang, Kyle M Wilson, Trey Roady, et al.
Human Factors
|
May 28, 2016
Modeling Driving Performance Using In-Vehicle Speech Data From a Naturalistic Driving Study
Jonny Kuo, Judith L Charlton, Sjaan Koppel, et al.
Journal of Safety Research
|
December 6, 2017
Automated recognition of rear seat occupants' head position using Kinect™ 3D point cloud
Helen Loeb, Jinyong Kim, Kristy Arbogast, et al.
Plos One
|
November 19, 2025
Assessing data imbalance correction methods and gaze entropy for collision prediction
Courtney M Goodridge, Rafael C Gonçalves, Amélie Reher, et al.
Traffic Injury Prevention
|
September 3, 2016
Naturalistic driving study of rear seat child occupants: Quantification of head position using a Kinect™ sensor
Kristy B Arbogast, Jinyong Kim, Helen Loeb, et al.
Page
of 2