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https://doi.org/10.2139/ssrn.4640135
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cpe.6475openalex-extracted
Computer vision‐based recognition of driver distraction: A review
inferredcites →https://doi.org/10.1007/978-1-4613-2173-6_19openalex-extracted
A Critical View of Driver Behavior Models: What Do We Know, What Should We Do?
inferredcites →https://doi.org/10.1007/978-3-319-40250-5_44openalex-extracted
Density of Gaze Points Within a Fixation and Information Processing Behavior
inferredcites →https://doi.org/10.1007/978-3-319-60441-1_58openalex-extracted
Understanding and Applying the Concept of “Driver Availability” in Automated Driving
inferredcites →https://doi.org/10.1007/978-3-319-96074-6_43openalex-extracted
A Review of Driver State Monitoring Systems in the Context of Automated Driving
inferredcites →https://doi.org/10.1007/s00422-017-0743-9openalex-extracted
Sustained sensorimotor control as intermittent decisions about prediction errors: computational framework and application to ground vehicle steering
inferredcites →https://doi.org/10.1007/s10111-018-0525-8openalex-extracted
The “Out-of-the-Loop” concept in automated driving: proposed definition, measures and implications
inferredcites →https://doi.org/10.1016/j.aap.2015.02.023openalex-extracted
What determines the take-over time? An integrated model approach of driver take-over after automated driving
inferredcites →https://doi.org/10.1016/j.aap.2016.04.002openalex-extracted
Is take-over time all that matters? The impact of visual-cognitive load on driver take-over quality after conditionally automated driving
inferredcites →https://doi.org/10.1016/j.aap.2016.08.027openalex-extracted
Age differences in the takeover of vehicle control and engagement in non-driving-related activities in simulated driving with conditional automation
inferredcites →https://doi.org/10.1016/j.aap.2017.08.011openalex-extracted
Coming back into the loop: Drivers’ perceptual-motor performance in critical events after automated driving
inferredcites →https://doi.org/10.1016/j.aap.2020.105432openalex-extracted
Detection of driver manual distraction via image-based hand and ear recognition
inferredcites →https://doi.org/10.1016/j.aap.2020.105748openalex-extracted
Predicting driver takeover performance in conditionally automated driving
inferredcites →https://doi.org/10.1016/j.aap.2020.105776openalex-extracted
Estimating the out-of-the-loop phenomenon from visual strategies during highly automated driving
inferredcites →https://doi.org/10.1016/j.aap.2021.106238openalex-extracted
Drivers trust, acceptance, and takeover behaviors in fully automated vehicles: Effects of automated driving styles and driver’s driving styles
inferredcites →https://doi.org/10.1016/j.aap.2022.106726openalex-extracted
The effect of information from dash-based human-machine interfaces on drivers' gaze patterns and lane-change manoeuvres after conditionally automated driving
inferredcites →https://doi.org/10.1016/j.apergo.2020.103074openalex-extracted
Effects of cognitive and visual loads on driving performance after take-over request (TOR) in automated driving
inferredcites →https://doi.org/10.1016/j.icte.2021.04.008openalex-extracted
A novel study on subjective driver readiness in terms of non-driving related tasks and take-over performance
inferredcites →https://doi.org/10.1016/j.neubiorev.2018.12.007openalex-extracted
A review of gaze entropy as a measure of visual scanning efficiency
inferredcites →https://doi.org/10.1016/j.promfg.2015.07.499openalex-extracted
Vigilance Decrement and Passive Fatigue Caused by Monotony in Automated Driving
inferredcites →https://doi.org/10.1016/j.tics.2016.01.007openalex-extracted
Diffusion Decision Model: Current Issues and History
inferredcites →https://doi.org/10.1016/j.trc.2017.01.001openalex-extracted
Are you in the loop? Using gaze dispersion to understand driver visual attention during vehicle automation
inferredcites →https://doi.org/10.1016/j.trf.2014.04.009openalex-extracted
Intention to use a fully automated car: Attitudes and a priori acceptability
inferredcites →https://doi.org/10.1016/j.trf.2014.06.016openalex-extracted
Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence
inferredcites →https://doi.org/10.1016/j.trf.2018.08.009openalex-extracted
Mind-wandering while driving: The impact of fatigue, task length, and sustained attention abilities
inferredcites →https://doi.org/10.1016/j.trf.2018.11.015openalex-extracted
Non-driving-related tasks, workload, and takeover performance in highly automated driving contexts
inferredcites →https://doi.org/10.1016/j.trf.2019.07.018openalex-extracted
Modelling visual-vestibular integration and behavioural adaptation in the driving simulator
inferredcites →https://doi.org/10.1016/j.trf.2022.04.002openalex-extracted
Physiological indicators of driver workload during car-following scenarios and takeovers in highly automated driving
inferredcites →https://doi.org/10.1016/s0896-6273(02)00971-6openalex-extracted
Banburismus and the Brain
inferredcites →https://doi.org/10.1016/s0927-0507(06)13020-0openalex-extracted
Chapter 20 An Overview of Simulation Optimization via Random Search
inferredcites →https://doi.org/10.1037/0033-295x.111.2.333openalex-extracted
A Comparison of Sequential Sampling Models for Two-Choice Reaction Time.
inferredcites →https://doi.org/10.1037/0033-295x.85.2.59openalex-extracted
A theory of memory retrieval.
inferredcites →https://doi.org/10.1037/xhp0001101openalex-extracted
Error accumulation when steering toward curves.
inferredcites →https://doi.org/10.1109/iccvw.2013.85openalex-extracted
Various Approaches for Driver and Driving Behavior Monitoring: A Review
inferredcites →https://doi.org/10.1109/ictc.2018.8539408openalex-extracted
Design of Driver Readiness Evaluation System in Automated Driving Environment
inferredcites →https://doi.org/10.1109/icufn.2018.8436988openalex-extracted
Real-Time Drowsiness Detection Algorithm for Driver State Monitoring Systems
inferredcites →https://doi.org/10.1109/itsc.2018.8569545openalex-extracted
Wake Up and Take Over! The Effect of Fatigue on the Take-over Performance in Conditionally Automated Driving
inferredcites →https://doi.org/10.1109/tits.2021.3069776openalex-extracted
Using Eye-Tracking Data to Predict Situation Awareness in Real Time During Takeover Transitions in Conditionally Automated Driving
inferredcites →https://doi.org/10.1109/tits.2022.3146793openalex-extracted
Physiological Measures of Risk Perception in Highly Automated Driving
inferredcites →https://doi.org/10.1109/tits.2022.3154329openalex-extracted
Predicting Driver Takeover Time in Conditionally Automated Driving
inferredcites →https://doi.org/10.1109/tiv.2019.2955364openalex-extracted
Looking at the Driver/Rider in Autonomous Vehicles to Predict Take-Over Readiness
inferredcites →https://doi.org/10.1109/vtc2020-spring48590.2020.9129132openalex-extracted
A Physiology-based Driver Readiness Estimation Model for Tuning ISO 26262 Controllability
inferredcites →https://doi.org/10.1136/injuryprev-2016-042155openalex-extracted
Were they in the loop during automated driving? Links between visual attention and crash potential
inferredcites →https://doi.org/10.1136/qshc.2003.009548openalex-extracted
Beyond the organisational accident: the need for "error wisdom" on the frontline
inferredcites →https://doi.org/10.1155/2021/8632685openalex-extracted
Effects of Level 3 Automated Vehicle Drivers’ Fatigue on Their Take-Over Behaviour: A Literature Review
inferredcites →https://doi.org/10.1177/0018720812460246openalex-extracted
Control Task Substitution in Semiautomated Driving
inferredcites →https://doi.org/10.1177/0018720813506223openalex-extracted
Situation Awareness Recovery
inferredcites →https://doi.org/10.1177/0018720817728774openalex-extracted
Driving Performance After Self-Regulated Control Transitions in Highly Automated Vehicles
inferredcites →https://doi.org/10.1177/0018720819829594openalex-extracted
Getting Back Into the Loop: The Perceptual-Motor Determinants of Successful Transitions out of Automated Driving
inferredcites →https://doi.org/10.1177/1541931213571433openalex-extracted
“Take over!” How long does it take to get the driver back into the loop?
inferredcites →https://doi.org/10.1518/001872095779049543openalex-extracted
Toward a Theory of Situation Awareness in Dynamic Systems
inferredcites →https://doi.org/10.31234/osf.io/bwp6fopenalex-extracted
Physiological Indicators of Driver Workload During Car-Following Scenarios and Takeovers in Highly Automated Driving
inferredcites →https://doi.org/10.31234/osf.io/cbksdopenalex-extracted
Steering is initiated based on error accumulation
inferredcites →https://doi.org/10.32604/cmc.2020.09763openalex-extracted
Driver Fatigue Detection System Based on Colored and Infrared Eye Features Fusion
inferredcites →https://doi.org/10.48550/arxiv.2103.14792openalex-extracted
Using Eye-tracking Data to Predict Situation Awareness in Real Time during Takeover Transitions in Conditionally Automated Driving
inferredcites →https://doi.org/10.5151/ergodesign2019-2.09openalex-extracted
Applicability of risky decision-making theory to understand drivers' behaviour during transitions of control in vehicle automation
inferredcites →https://doi.org/10.5281/zenodo.7995032openalex-extracted
Quantifying Drivers' Physiological Responses to Take-Over Requests in Conditionally Automated Vehicles
inferredcites →https://doi.org/10.7910/dvn/ldo7ppopenalex-extracted
Driver’s Mental Models of Advanced Vehicle Technologies: A Proposed Framework for Identifying and Predicting Operator Errors
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