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A novel study on subjective driver readiness in terms of non-driving related tasks and take-over performance
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-60441-1_58openalex-snapshot
Understanding and Applying the Concept of “Driver Availability” in Automated Driving
inferredcites →https://doi.org/10.1016/j.aap.2015.02.023openalex-snapshot
What determines the take-over time? An integrated model approach of driver take-over after automated driving
inferredcites →https://doi.org/10.1016/j.trf.2018.11.015openalex-snapshot
Non-driving-related tasks, workload, and takeover performance in highly automated driving contexts
inferredcites →https://doi.org/10.1016/j.trf.2019.04.020openalex-snapshot
Determinants of take-over time from automated driving: A meta-analysis of 129 studies
inferredcites →https://doi.org/10.1111/j.1464-0597.2004.00161.xopenalex-snapshot
Evaluation of Subjective Mental Workload: A Comparison of SWAT, NASA‐TLX, and Workload Profile Methods
inferredcites →https://doi.org/10.1145/3025171.3025199openalex-snapshot
Driver Readiness Model for Regulating the Transfer from Automation to Human Control
inferredcites →https://doi.org/10.1186/s12544-020-00427-5openalex-snapshot
Multimodal warning design for take-over request in conditionally automated driving
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4469559openalex-extracted
Disturbance Analysis and Safety Monitoring of Driver's Emotion Swings in Human-Machine Co-Driving Environment: A Digital Twin Approach
inferred← citeshttps://doi.org/10.2139/ssrn.4658356openalex-extracted
Non-Driving-Related Tasks Influencing Drivers’ Takeover Time: A Meta-Analysis
inferred← citeshttps://doi.org/10.1007/978-3-031-93736-1_15openalex-snapshot
Identifying Key Features for Classifying Takeover Performance in Level 3 Autonomous Vehicles with Consideration of Takeover Readiness
inferred← citeshttps://doi.org/10.1007/s10111-024-00777-3openalex-snapshot
Using driver monitoring to estimate readiness in automation: a conceptual model based on simulator experimental data
inferred← citeshttps://doi.org/10.1016/j.aap.2023.107040openalex-snapshot
Constructing the behavioral sequence of the takeover process—TOR, behavior characteristics and phases division: A real vehicle experiment
inferred← citeshttps://doi.org/10.1016/j.aap.2024.107793openalex-snapshot
Effects of non-driving related postures on takeover performance during conditionally automated driving
inferred← citeshttps://doi.org/10.1016/j.aap.2025.108327openalex-snapshot
The impact of N-back-induced mental workload and time budget on takeover performance
inferred← citeshttps://doi.org/10.1016/j.aap.2025.108348openalex-snapshot
Beyond distraction: unraveling touchscreen effects on driver takeover performance and visual attention dynamics in Level 3 automated driving
inferred← citeshttps://doi.org/10.1016/j.aei.2026.105094openalex-snapshot
Comprehensive assessment of driver takeover readiness via a multimodal fusion multi-task learning model
inferred← citeshttps://doi.org/10.1016/j.displa.2025.103117openalex-snapshot
How task demands influence driver behaviour in conditionally automated driving: An investigation of situation awareness and takeover performance
inferred← citeshttps://doi.org/10.1016/j.dss.2025.114559openalex-snapshot
Driver readiness prediction: Bridging cognitive distraction monitoring and in-vehicle decision support systems
inferred← citeshttps://doi.org/10.1016/j.isci.2025.112783openalex-snapshot
Task-specific versus free-choice non-driving-related tasks: Enhancing automated driving takeover research through varied task engagement
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2026.125249openalex-snapshot
An inference model for optimal crew takeover timing in MASS under human-machine co-driving conditions
inferred← citeshttps://doi.org/10.1016/j.trf.2024.05.012openalex-snapshot
Non-driving-related tasks and drivers’ takeover time: A meta-analysis
inferred← citeshttps://doi.org/10.1049/itr2.70006openalex-snapshot
Evaluating Driver Readiness in Conditionally Automated Vehicles From Eye‐Tracking Data and Head Pose
inferred← citeshttps://doi.org/10.1080/10447318.2022.2121455openalex-snapshot
Impacts of Attention Level on Manual Take-Over Performance in Automatic Driving on High-Speed Railways
inferred← citeshttps://doi.org/10.1080/10447318.2026.2721890openalex-snapshot
A Taxonomy and Systematic Review of Driving Automation Failure Scenarios
inferred← citeshttps://doi.org/10.1080/15389588.2024.2447574openalex-snapshot
Takeover performance prediction model considering cognitive load: analysis of subjective and objective factors
inferred← citeshttps://doi.org/10.1080/15389588.2026.2619003openalex-snapshot
The interactive effects of NDRT cognitive complexity and traffic density on takeover performance in level 3 automated driving: a multimodal EEG and behavioral study
inferred← citeshttps://doi.org/10.1080/15472450.2024.2307029openalex-snapshot
Predicting the duration of reduced driver performance during the automated driving takeover process
inferred← citeshttps://doi.org/10.1109/itsc60802.2025.11423647openalex-snapshot
Machine Learning Classification of Crash Risk During Takeover Based on Driver Readiness and Scenario Features
inferred← citeshttps://doi.org/10.1109/iv64158.2025.11097677openalex-snapshot
Driver-Net: Multi-Camera Fusion for Assessing Driver Take-Over Readiness in Automated Vehicles
inferred← citeshttps://doi.org/10.1109/thms.2025.3595269openalex-snapshot
Effects of Readiness Deprivation on Takeover With Varying Time Budget in Conditional Automated Driving Scenarios
inferred← citeshttps://doi.org/10.1109/tits.2022.3233623openalex-snapshot
A Human-Centered Comprehensive Measure of Take-Over Performance Based on Multiple Objective Metrics
inferred← citeshttps://doi.org/10.1109/tits.2025.3589326openalex-snapshot
Predicting Takeover Performance and Identifying Behavioral Patterns in Autonomous Vehicles Based on Readiness State and Scenario Complexity
inferred← citeshttps://doi.org/10.1145/3641308.3685041openalex-snapshot
Markov Chain Analysis of Gaze Transitions: Assessing Attention Management in SAE Level 3 Automated Driving
inferred← citeshttps://doi.org/10.1145/3678544openalex-snapshot
TimelyTale: A Multimodal Dataset Approach to Assessing Passengers' Explanation Demands in Highly Automated Vehicles
inferred← citeshttps://doi.org/10.1145/3726986.3727030openalex-snapshot
Using gaze to understand shifts in visual attention during conditional automation with non-driving related tasks
inferred← citeshttps://doi.org/10.1145/3744335.3749136openalex-snapshot
What makes a ready driver? A deep dive into the measurement and validation of readiness estimation for driver monitoring systems of partially automated (SAE level 2) vehicles
inferred← citeshttps://doi.org/10.1177/03611981221076442openalex-snapshot
Impact of Secondary Task Immersion Duration on Take-Over Process of Conditional (L3) Automated Vehicles in an Off-Ramp Area
inferred← citeshttps://doi.org/10.1371/journal.pone.0336777openalex-snapshot
Assessing data imbalance correction methods and gaze entropy for collision prediction
inferred← citeshttps://doi.org/10.1371/journal.pone.0355165openalex-snapshot
Pupillary dynamics during hands-off L2 driving and transitions of control under high cognitive load
inferred← citeshttps://doi.org/10.2139/ssrn.5056613openalex-snapshot
The Impacts of Non-Driving Related Tasks on In-Vehicle Users While Operating Conditionally Automated Vehicles: A Systematic Literature Review
inferred← citeshttps://doi.org/10.3390/electronics15071390openalex-snapshot
Towards Safer Automated Driving: Predicting Drivers with Long Takeover Time Using Random Forest and Human Factors
inferred← citeshttps://doi.org/10.4218/etrij.2021-0241openalex-snapshot
Study on the Take‐over Performance of Level 3 Autonomous Vehicles Based on Subjective Driving Tendency Questionnaires and Machine Learning Methods
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