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A Systematic Review of Abnormal Behavior Detection and Analysis in Driving Simulators

https://doi.org/10.2139/ssrn.4772738
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Computer vision‐based recognition of driver distraction: A review
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Distraction produces over-additive increases in the degree to which alcohol impairs driving performance
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How eco-driving training course influences driver behavior and comprehensibility: a driving simulator study
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How do angry drivers respond to emotional music? A comprehensive perspective on assessing emotion
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A Multi-Modal Driver Fatigue and Distraction Assessment System
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Real-Time Distraction Detection from Driving Data Based Personal Driving Model Using Deep Learning
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Towards Behavioral Modeling of Drivers in Mixed Traffic Conditions
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Efficient driver drowsiness detection at moderate levels of drowsiness
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A simulator study of the effects of singing on driving performance
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Lane heading difference: An innovative model for drowsy driving detection using retrospective analysis around curves
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Driver drowsiness detection based on non-intrusive metrics considering individual specifics
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In the eye of the beholder: A simulator study of the impact of Google Glass on driving performance
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Prediction of drowsiness events in night shift workers during morning driving
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The impact of texting on driver behaviour at rail level crossings
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Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness
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The long road home from distraction: Investigating the time-course of distraction recovery in driving
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Temporal patterns of driving fatigue and driving performance among male taxi drivers in Hong Kong: A driving simulator approach
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Analysis of commercial truck drivers’ potentially dangerous driving behaviors based on 11-month digital tachograph data and multilevel modeling approach
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Influence of traffic congestion on driver behavior in post-congestion driving
inferredcites →https://doi.org/10.1016/j.aap.2020.105516openalex-extracted
Links between observed and self-reported driving anger, observed and self-reported aggressive driving, and personality traits
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Smartwatches are more distracting than mobile phones while driving: Results from an experimental study
inferredcites →https://doi.org/10.1016/j.aap.2020.105908openalex-extracted
Analyzing driver behavior under naturalistic driving conditions: A review
inferredcites →https://doi.org/10.1016/j.aap.2022.106565openalex-extracted
Driver distraction and its effects on partially automated driving performance: A driving simulator study among young-experienced drivers
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Alcohol impairs driver attention and prevents compensatory strategies
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Driver drowsiness detection using mixed-effect ordered logit model considering time cumulative effect
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Simulation-based driver and vehicle crew training: Applications, efficacy and future directions
inferredcites →https://doi.org/10.1016/j.apergo.2012.10.009openalex-extracted
Driver distraction and performance effects of highway logo sign design
inferredcites →https://doi.org/10.1016/j.apergo.2018.09.001openalex-extracted
The relative impact of smartwatch and smartphone use while driving on workload, attention, and driving performance
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The application of machine learning techniques for driving behavior analysis: A conceptual framework and a systematic literature review
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Drivers’ attitudes, preference, and acceptance of in-vehicle anger intervention systems and their relationships to demographic and personality characteristics
inferredcites →https://doi.org/10.1016/j.ergon.2020.102999openalex-extracted
Impacts of anger on driving performance: A comparison to texting and conversation while driving
inferredcites →https://doi.org/10.1016/j.ergon.2020.103009openalex-extracted
Driver's distracted behavior: The contribution of compensatory beliefs increases with higher perceived risk
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A method for fatigue detection based on Driver's steering wheel grip
inferredcites →https://doi.org/10.1016/j.ergon.2021.103124openalex-extracted
Physical workload and psychosocial working conditions in Swedish pig transport drivers
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Which factors lead to driving errors? A structural equation model analysis through a driving simulator experiment
inferredcites →https://doi.org/10.1016/j.jsr.2015.06.007openalex-extracted
Drunk driving detection based on classification of multivariate time series
inferredcites →https://doi.org/10.1016/j.jtte.2017.05.013openalex-extracted
An analysis on older driver's driving behavior by GPS tracking data: Road selection, left/right turn, and driving speed
inferredcites →https://doi.org/10.1016/j.trc.2012.10.006openalex-extracted
Analysis of hands activity for automatic driving risk detection
inferredcites →https://doi.org/10.1016/j.trc.2013.10.004openalex-extracted
A hybrid Bayesian Network approach to detect driver cognitive distraction
inferredcites →https://doi.org/10.1016/j.trc.2017.02.007openalex-extracted
Modelling driver distraction effects due to mobile phone use on reaction time
inferredcites →https://doi.org/10.1016/j.trf.2014.04.003openalex-extracted
Effects of specific emotions on subjective judgment, driving performance, and perceived workload
inferredcites →https://doi.org/10.1016/j.trf.2017.10.002openalex-extracted
Does cognitive distraction improve or degrade lane keeping performance? Analysis of time-to-line crossing safety margins
inferredcites →https://doi.org/10.1016/j.trf.2018.02.013openalex-extracted
Effects of roadside distractors on performance of drivers with and without attention deficit tendencies
inferredcites →https://doi.org/10.1016/j.trf.2018.02.032openalex-extracted
Driver’s emotional state and detection of vulnerable road users: Towards a better understanding of how emotions affect drivers’ perception using cardiac and ocular metrics
inferredcites →https://doi.org/10.1016/j.trf.2018.06.027openalex-extracted
Real-time detection of drivers’ texting and eating behavior based on vehicle dynamics
inferredcites →https://doi.org/10.1016/j.trf.2018.12.006openalex-extracted
Efficacy of training with driving simulators in improving safety in young novice or learner drivers: A systematic review
inferredcites →https://doi.org/10.1016/j.trf.2019.11.007openalex-extracted
The ability of young, middle-aged and older drivers to inhibit visual and auditory distraction in a driving simulator task
inferredcites →https://doi.org/10.1016/j.trf.2022.08.007openalex-extracted
Towards a new approach to detect sleepiness: Validation of the objective sleepiness scale under simulated driving conditions
inferredcites →https://doi.org/10.1016/j.trip.2019.100087openalex-extracted
Evaluating driver cognitive distraction by eye tracking: From simulator to driving
inferredcites →https://doi.org/10.1016/j.trip.2023.100864openalex-extracted
A systematic review on detection and prediction of driver drowsiness
inferredcites →https://doi.org/10.1016/j.trpro.2017.05.148openalex-extracted
Review of driving performance parameters critical for distracted driving research
inferredcites →https://doi.org/10.1038/s41598-020-70645-3openalex-extracted
Contrast sensitivity and retinal straylight after alcohol consumption: effects on driving performance
inferredcites →https://doi.org/10.1038/s41598-021-88435-wopenalex-extracted
Deterioration of binocular vision after alcohol intake influences driving performance
inferredcites →https://doi.org/10.1049/iet-its.2019.0638openalex-extracted
Comparative analysis of the effects of mobile phone use on driving performance using ANOVA and ANCOVA
inferredcites →https://doi.org/10.1049/itr2.12236openalex-extracted
Non‐instinct detection of cellphone usage from lane‐keeping performance based on eXtreme gradient boosting and optimal sliding windows
inferredcites →https://doi.org/10.1080/15389588.2017.1303140openalex-extracted
Evaluating driver drowsiness countermeasures
inferredcites →https://doi.org/10.1080/15389588.2018.1517237openalex-extracted
Effects of texting on accident risk during a sudden hazardous event: Analysis of predetection and postdetection phases
inferredcites →https://doi.org/10.1080/15389588.2019.1706088openalex-extracted
Driving simulator experiments to study drowsiness: A systematic review
inferredcites →https://doi.org/10.1097/opx.0000000000001501openalex-extracted
The Effects of Age, Distraction, and Simulated Central Vision Impairment on Hazard Detection in a Driving Simulator
inferredcites →https://doi.org/10.1109/access.2020.2999829openalex-extracted
Detecting Human Driver Inattentive and Aggressive Driving Behavior Using Deep Learning: Recent Advances, Requirements and Open Challenges
inferredcites →https://doi.org/10.1109/access.2023.3243865openalex-extracted
Driver Behavior Classification: A Systematic Literature Review
inferredcites →https://doi.org/10.1109/access.2023.3245122openalex-extracted
Detection of Driver Cognitive Distraction Using Machine Learning Methods
inferredcites →https://doi.org/10.1109/access.2023.3257238openalex-extracted
A Distracted Driving Detection Model Based On Driving Performance
inferredcites →https://doi.org/10.1109/iciinfs.2018.8721391openalex-extracted
Study to Determine the Effectiveness of Deep Learning Classifiers for ECG Based Driver Fatigue Classification
inferredcites →https://doi.org/10.1109/itsc45102.2020.9294422openalex-extracted
LGSVL Simulator: A High Fidelity Simulator for Autonomous Driving
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A Temporal–Spatial Deep Learning Approach for Driver Distraction Detection Based on EEG Signals
inferredcites →https://doi.org/10.1109/tbcas.2014.2316224openalex-extracted
Wireless and Wearable EEG System for Evaluating Driver Vigilance
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The Effect of a Haptic Guidance Steering System on Fatigue-Related Driver Behavior
inferredcites →https://doi.org/10.1109/thms.2021.3090787openalex-extracted
Classification of Officers’ Driving Situations Based on Eye-Tracking and Driver Performance Measures
inferredcites →https://doi.org/10.1109/tits.2012.2208223openalex-extracted
Changes in the Correlation Between Eye and Steering Movements Indicate Driver Distraction
inferredcites →https://doi.org/10.1109/tits.2014.2307891openalex-extracted
Detection of Intoxicated Drivers Using Online System Identification of Steering Behavior
inferredcites →https://doi.org/10.1109/tits.2015.2506602openalex-extracted
Detection of Driver Cognitive Distraction: A Comparison Study of Stop-Controlled Intersection and Speed-Limited Highway
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Driver Mental Fatigue Detection Based on Head Posture Using New Modified reLU-BiLSTM Deep Neural Network
inferredcites →https://doi.org/10.1111/jsr.12163openalex-extracted
Sleep‐related eye symptoms and their potential for identifying driver sleepiness
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The Induction and Detection Method of Angry Driving: Evidences from EEG and Physiological Signals
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A Strategically Timed Verbal Task Improves Performance and Neurophysiological Alertness During Fatiguing Drives
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Effects of Different Alcohol Dosages on Steering Behavior in Curve Driving
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Voice Control Tasks on Cognitive Workload and Driving Performance: Implications of Modality, Difficulty, and Duration
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Enhancing the Performance of a Model to Predict Driving Distraction with the Random Forest Classifier
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Classification of Driver Cognitive Load: Exploring the Benefits of Fusing Eye-Tracking and Physiological Measures
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Random forest–based feature selection and detection method for drunk driving recognition
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Effects of driver behavior style differences and individual differences on driver sleepiness detection
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Effects of Visual and Acoustic Distraction on Driving Behavior and EEG in Young and Older Car Drivers: A Driving Simulation Study
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An Investigation of Early Detection of Driver Drowsiness Using Ensemble Machine Learning Based on Hybrid Sensing
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Feature Extraction and Evaluation for Driver Drowsiness Detection Based on Thermoregulation
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Support Vector Machine Classification of Drunk Driving Behaviour
inferredcites →https://doi.org/10.3390/ijerph16111935openalex-extracted
Classification of Fatigued and Drunk Driving Based on Decision Tree Methods: A Simulator Study
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Talking on the Phone While Driving: A Literature Review on Driving Simulator Studies
inferredcites →https://doi.org/10.3390/ijerph20054354openalex-extracted
Texting While Driving: A Literature Review on Driving Simulator Studies
inferredcites →https://doi.org/10.3390/s140101106openalex-extracted
Fusion of Optimized Indicators from Advanced Driver Assistance Systems (ADAS) for Driver Drowsiness Detection
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Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition
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A Deep Learning Framework for Driving Behavior Identification on In-Vehicle CAN-BUS Sensor Data
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Assessment of the Potential of Wrist-Worn Wearable Sensors for Driver Drowsiness Detection
inferredcites →https://doi.org/10.3390/s23031345openalex-extracted
Young Novice Drivers’ Cognitive Distraction Detection: Comparing Support Vector Machines and Random Forest Model of Vehicle Control Behavior
inferredcites →https://doi.org/10.4236/jtts.2017.73023openalex-extracted
Development of a Driving Simulator with Analyzing Driver’s Characteristics Based on a Virtual Reality Head Mounted Display
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CARLA: An Open Urban Driving Simulator
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