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Non‐instinct detection of cellphone usage from lane‐keeping performance based on eXtreme gradient boosting and optimal sliding windows

https://doi.org/10.1049/itr2.12236
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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-14066-7_37openalex-snapshot
Driver Workload Detection in On-Road Driving Environment Using Machine Learning
inferredcites →https://doi.org/10.1016/j.aap.2012.06.013openalex-snapshot
Driver's lane keeping ability with eyes off road: Insights from a naturalistic study
inferredcites →https://doi.org/10.1016/j.aap.2014.10.009openalex-snapshot
The effects of texting on driving performance in a driving simulator: The influence of driver age
inferredcites →https://doi.org/10.1016/j.aap.2015.02.021openalex-snapshot
Identification of common features of vehicle motion under drowsy/distracted driving: A case study in Wuhan, China
inferredcites →https://doi.org/10.1016/j.aap.2018.01.005openalex-snapshot
A contextual and temporal algorithm for driver drowsiness detection
inferredcites →https://doi.org/10.1016/j.aap.2018.12.005openalex-snapshot
A hierarchical machine learning classification approach for secondary task identification from observed driving behavior data
inferredcites →https://doi.org/10.1016/j.aap.2019.01.030openalex-snapshot
What is the difference in driver’s lateral control ability during naturalistic distracted driving and normal driving? A case study on a real highway
inferredcites →https://doi.org/10.1016/j.aap.2019.05.005openalex-snapshot
A feature learning approach based on XGBoost for driving assessment and risk prediction
inferredcites →https://doi.org/10.1016/j.csda.2005.05.007openalex-snapshot
Confidence interval for a coefficient of quartile variation
inferredcites →https://doi.org/10.1016/j.ssci.2013.08.012openalex-snapshot
Effects of driving experience and sensation-seeking on drivers’ adaptation to road environment complexity
inferredcites →https://doi.org/10.1016/j.trc.2018.05.017openalex-snapshot
How is driving volatility related to intersection safety? A Bayesian heterogeneity-based analysis of instrumented vehicles data
inferredcites →https://doi.org/10.1016/j.trc.2022.103561openalex-snapshot
Driver distraction detection based on vehicle dynamics using naturalistic driving data
inferredcites →https://doi.org/10.1016/j.trf.2011.06.003openalex-snapshot
The effect of visual and cognitive distraction on driver’s anticipation in a simulated car following scenario
inferredcites →https://doi.org/10.1016/j.trf.2012.05.004openalex-snapshot
Driver performance effects of simultaneous visual and cognitive distraction and adaptation behavior
inferredcites →https://doi.org/10.1016/j.trf.2013.12.017openalex-snapshot
A study of young adults examining phone dialing while driving using a touchscreen vs. a button style flip-phone
inferredcites →https://doi.org/10.1016/j.trf.2017.11.021openalex-snapshot
A framework for evaluating aggressive driving behaviors based on in-vehicle driving records
inferredcites →https://doi.org/10.1016/j.trf.2018.06.013openalex-snapshot
Adaptive warning signals adjusted to driver passenger conversation: Impact of system awareness on behavioral adaptations
inferredcites →https://doi.org/10.1016/j.trf.2018.06.027openalex-snapshot
Real-time detection of drivers’ texting and eating behavior based on vehicle dynamics
inferredcites →https://doi.org/10.1016/j.trf.2019.03.017openalex-snapshot
A graphical modeling method for individual driving behavior and its application in driving safety analysis using GPS data
inferredcites →https://doi.org/10.1037/1076-898x.9.2.119openalex-snapshot
Mental workload while driving: Effects on visual search, discrimination, and decision making.
inferredcites →https://doi.org/10.1049/iet-its.2018.5172openalex-snapshot
Real‐time detection of distracted driving based on deep learning
inferredcites →https://doi.org/10.1049/itr2.12133openalex-snapshot
Stacking‐based ensemble learning method for cognitive distraction state recognition for drivers in traditional and connected environments
inferredcites →https://doi.org/10.1080/15389588.2011.607197openalex-snapshot
Effects of Age and the Use of Hands-Free Cellular Phones on Driving Behavior and Task Performance
inferredcites →https://doi.org/10.1080/15389588.2012.699695openalex-snapshot
Driver Performance While Texting: Even a Little is Too Much
inferredcites →https://doi.org/10.1080/15389588.2014.920953openalex-snapshot
The Influence of Drinking, Texting, and Eating on Simulated Driving Performance
inferredcites →https://doi.org/10.1080/15389588.2014.969803openalex-snapshot
Post and During Event Effect of Cell Phone Talking and Texting on Driving Performance—A Driving Simulator Study
inferredcites →https://doi.org/10.1088/1742-6596/1770/1/012007openalex-snapshot
Driver Distraction Detection and Early Prediction and avoidance of accidents using Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/access.2021.3073599openalex-snapshot
Driver Distraction Detection Methods: A Literature Review and Framework
inferredcites →https://doi.org/10.1109/access.2021.3109815openalex-snapshot
TML: A Triple-Wise Multi-Task Learning Framework for Distracted Driver Recognition
inferredcites →https://doi.org/10.1109/tits.2007.895298openalex-snapshot
Real-Time Detection of Driver Cognitive Distraction Using Support Vector Machines
inferredcites →https://doi.org/10.1109/tits.2011.2119483openalex-snapshot
Online Driver Distraction Detection Using Long Short-Term Memory
inferredcites →https://doi.org/10.1109/tits.2020.3002419openalex-snapshot
An Automated Machine Learning (AutoML) Method of Risk Prediction for Decision-Making of Autonomous Vehicles
inferredcites →https://doi.org/10.1109/tits.2021.3122865openalex-snapshot
Explanations in Autonomous Driving: A Survey
inferredcites →https://doi.org/10.1109/tits.2022.3159602openalex-snapshot
Driver Distraction Detection Using Bidirectional Long Short-Term Network Based on Multiscale Entropy of EEG
inferredcites →https://doi.org/10.1177/0018720817748145openalex-snapshot
Does Talking on a Cell Phone, With a Passenger, or Dialing Affect Driving Performance? An Updated Systematic Review and Meta-Analysis of Experimental Studies
inferredcites →https://doi.org/10.1371/journal.pone.0160288openalex-snapshot
Why Do Drivers Use Mobile Phones While Driving? The Contribution of Compensatory Beliefs
inferredcites →https://doi.org/10.3389/fnhum.2022.754379openalex-snapshot
Neural Correlates Predicting Lane-Keeping and Hazard Detection: An fMRI Study Featuring a Pedestrian-Rich Simulator Environment

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.4772738openalex-extracted
A Systematic Review of Abnormal Behavior Detection and Analysis in Driving Simulators
inferred← citeshttps://doi.org/10.1016/j.aap.2022.106936openalex-snapshot
Analysis of mobile phone use engagement during naturalistic driving through explainable imbalanced machine learning
inferred← citeshttps://doi.org/10.1016/j.aap.2025.108240openalex-snapshot
Deriving workload from driving behavior and psycho-physiology in work zones
inferred← citeshttps://doi.org/10.1016/j.trf.2025.01.002openalex-snapshot
A systematic review of abnormal behaviour detection and analysis in driving simulators
inferred← citeshttps://doi.org/10.7753/10.7753/ijsea1112.1001openalex-snapshot
A Method of Car Driver's Phone Call Recognition Based on Human Joint Points
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