Eraqi, H.M.[Hesham M.],
Abouelnaga, Y.[Yehya],
Saad, M.H.[Mohamed H.],
Moustafa, M.N.[Mohamed N.],
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Dataset, Driver Monitoring. Includes Distracted Driver V1 and Distracted Driver V2.
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Reyes, M.L.,
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Real-Time Detection of Driver Cognitive Distraction Using Support
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ITS(8), No. 2, April 2007, pp. 340-350.
IEEE DOI
0706
BibRef
Ersal, T.,
Fuller, H.J.A.,
Tsimhoni, O.,
Stein, J.L.,
Fathy, H.K.,
Model-Based Analysis and Classification of Driver Distraction Under
Secondary Tasks,
ITS(11), No. 3, September 2010, pp. 692-701.
IEEE DOI
1003
BibRef
Gelau, C.,
Schindhelm, R.,
Enhancing the occlusion technique as an assessment tool for driver
visual distraction,
IET-ITS(4), No. 4, 2010, pp. 346-355.
DOI Link
1204
BibRef
Metz, B.,
Krueger, H.P.,
Measuring visual distraction in driving:
The potential of head movement analysis,
IET-ITS(4), No. 4, 2010, pp. 289-297.
DOI Link
1204
BibRef
Hoel, J.,
Jaffard, M.,
Boujon, C.,
van Elslande, P.,
Different forms of attentional disturbances involved in driving
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IET-ITS(5), No. 2, June 2011, pp. 120-126.
DOI Link
1712
BibRef
Wollmer, M.,
Blaschke, C.,
Schindl, T.,
Schuller, B.,
Farber, B.,
Mayer, S.,
Trefflich, B.,
Online Driver Distraction Detection Using Long Short-Term Memory,
ITS(12), No. 2, June 2011, pp. 574-582.
IEEE DOI
1101
BibRef
Jimenez, P.,
Bergasa, L.M.,
Nuevo, J.,
Hernandez, N.,
Daza, I.G.,
Gaze Fixation System for the Evaluation of Driver Distractions Induced
by IVIS,
ITS(13), No. 3, September 2012, pp. 1167-1178.
IEEE DOI
1209
BibRef
Yekhshatyan, L.,
Lee, J.D.,
Changes in the Correlation Between Eye and Steering Movements Indicate
Driver Distraction,
ITS(14), No. 1, March 2013, pp. 136-145.
IEEE DOI
1303
BibRef
Ahlstrom, C.,
Kircher, K.,
Kircher, A.,
A Gaze-Based Driver Distraction Warning System and
Its Effect on Visual Behavior,
ITS(14), No. 2, 2013, pp. 965-973.
IEEE DOI
1307
Roads; Safety; Distraction warning; eye movements;
eye tracking
BibRef
Tango, F.,
Botta, M.,
Real-Time Detection System of Driver Distraction Using Machine Learning,
ITS(14), No. 2, 2013, pp. 894-905.
IEEE DOI
1307
Artificial neural networks; driver distraction and inattention
BibRef
Tian, R.,
Li, L.,
Chen, M.,
Chen, Y.,
Witt, G.J.,
Studying the Effects of Driver Distraction and Traffic Density on the
Probability of Crash and Near-Crash Events in Naturalistic Driving
Environment,
ITS(14), No. 3, 2013, pp. 1547-1555.
IEEE DOI
1309
Cumulative driver off-road glance duration
BibRef
Kim, H.S.[Hyun Suk],
Hwang, Y.[Yoonsook],
Yoon, D.[Daesub],
Choi, W.[Wongeun],
Park, C.H.[Cheong Hee],
Driver Workload Characteristics Analysis Using EEG Data From an Urban
Road,
ITS(15), No. 4, August 2014, pp. 1844-1849.
IEEE DOI
1410
cognition
BibRef
Siordia, O.S.[Oscar S.],
Martín de Diego, I.[Isaac],
Conde, C.[Cristina],
Cabello, E.[Enrique],
Subjective Traffic Safety Experts' Knowledge for Driving-Risk
Definition,
ITS(15), No. 4, August 2014, pp. 1823-1834.
IEEE DOI
1410
BibRef
Earlier: A2, A1, A3, A4:
Section-Wise Similarities for Classification of Subjective-Data on Time
Series,
CIARP11(363-371).
Springer DOI
1111
automobiles
BibRef
Li, N.,
Busso, C.,
Predicting Perceived Visual and Cognitive Distractions of Drivers
With Multimodal Features,
ITS(16), No. 1, February 2015, pp. 51-65.
IEEE DOI
1502
Cameras
BibRef
Wang, S.,
Zhang, Y.,
Wu, C.,
Darvas, F.,
Chaovalitwongse, W.A.,
Online Prediction of Driver Distraction Based on Brain Activity
Patterns,
ITS(16), No. 1, February 2015, pp. 136-150.
IEEE DOI
1502
Cities and towns
BibRef
Liu, T.,
Yang, Y.,
Huang, G.B.,
Yeo, Y.K.,
Lin, Z.,
Driver Distraction Detection Using Semi-Supervised Machine Learning,
ITS(17), No. 4, April 2016, pp. 1108-1120.
IEEE DOI
1604
Labeling
BibRef
Hajinoroozi, M.[Mehdi],
Mao, Z.J.[Zi-Jing],
Jung, T.P.[Tzyy-Ping],
Lin, C.T.[Chin-Teng],
Huang, Y.F.[Yu-Fei],
EEG-based prediction of driver's cognitive performance by deep
convolutional neural network,
SP:IC(47), No. 1, 2016, pp. 549-555.
Elsevier DOI
1610
Deep neural network
BibRef
Liao, Y.,
Li, S.E.,
Wang, W.,
Wang, Y.,
Li, G.,
Cheng, B.,
Detection of Driver Cognitive Distraction: A Comparison Study of
Stop-Controlled Intersection and Speed-Limited Highway,
ITS(17), No. 6, June 2016, pp. 1628-1637.
IEEE DOI
1606
Accidents
BibRef
Villán, A.F.[Alberto Fernández],
Facial attributes recognition using computer vision to detect
drowsiness and distraction in drivers,
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1804
BibRef
Wan, P.[Ping],
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On-road experimental study on driving anger identification model based
on physiological features by ROC curve analysis,
IET-ITS(11), No. 5, June 2017, pp. 290-298.
DOI Link
1705
BibRef
Yüce, A.,
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Thiran, J.P.,
Action Units and Their Cross-Correlations for Prediction of Cognitive
Load during Driving,
AffCom(8), No. 2, April 2017, pp. 161-175.
IEEE DOI
1706
Accidents, Databases, Feature extraction, Gold, Monitoring, Vehicles,
Visualization, Affect sensing and analysis,
affective computing applications, driver cognitive distraction,
emotional corpora, facial expression, vehicle, operation
BibRef
Muñoz-Organero, M.,
Corcoba-Magaña, V.,
Predicting Upcoming Values of Stress While Driving,
ITS(18), No. 7, July 2017, pp. 1802-1811.
IEEE DOI
1706
Heart rate variability, Physiology, Sensors, Skin, Stress, Vehicles,
Stress level prediction, machine learning,
stress level classification, stress-friendly, driving, behavior
BibRef
Lee, B.G.,
Chung, W.Y.,
Wearable Glove-Type Driver Stress Detection Using a Motion Sensor,
ITS(18), No. 7, July 2017, pp. 1835-1844.
IEEE DOI
1706
Accelerometers, Biomedical monitoring, Mobile handsets, Stress,
Stress measurement, Vehicles, Wheels, Driver assistance,
healthcare sensor, inertial motion unit, stress monitoring,
wearable, system
BibRef
Tran, D.[Duy],
Do, H.M.[Ha Manh],
Sheng, W.H.[Wei-Hua],
Bai, H.[He],
Chowdhary, G.[Girish],
Real-time detection of distracted driving based on deep learning,
IET-ITS(12), No. 10, December 2018, pp. 1210-1219.
DOI Link
1812
BibRef
Ben Ahmed, K.,
Goel, B.,
Bharti, P.,
Chellappan, S.,
Bouhorma, M.,
Leveraging Smartphone Sensors to Detect Distracted Driving Activities,
ITS(20), No. 9, September 2019, pp. 3303-3312.
IEEE DOI
1909
Sensors, Accelerometers, Gyroscopes, Acceleration, Automobiles, Wheels,
Smart sensing, intelligent transportation systems,
smartphones
BibRef
Rastgoo, M.N.[Mohammad Naim],
Nakisa, B.[Bahareh],
Rakotonirainy, A.[Andry],
Chandran, V.[Vinod],
Tjondronegoro, D.[Dian],
A Critical Review of Proactive Detection of Driver Stress Levels Based
on Multimodal Measurements,
Surveys(51), No. 5, January 2019, pp. Article No 88.
DOI Link
1902
Survey, Driver Stress.
BibRef
Aksjonov, A.,
Nedoma, P.,
Vodovozov, V.,
Petlenkov, E.,
Herrmann, M.,
Detection and Evaluation of Driver Distraction Using Machine Learning
and Fuzzy Logic,
ITS(20), No. 6, June 2019, pp. 2048-2059.
IEEE DOI
1906
Vehicles, Task analysis, Support vector machines, Machine learning,
Artificial neural networks, Machine learning algorithms,
vehicle safety
BibRef
Alotaibi, M.[Munif],
Alotaibi, B.[Bandar],
Distracted driver classification using deep learning,
SIViP(14), No. 3, April 2020, pp. 617-624.
Springer DOI
2004
BibRef
Jegham, I.[Imen],
Ben Khalifa, A.[Anouar],
Alouani, I.[Ihsen],
Mahjoub, M.A.[Mohamed Ali],
A novel public dataset for multimodal multiview and multispectral
driver distraction analysis: 3MDAD,
SP:IC(88), 2020, pp. 115960.
Elsevier DOI
2009
Safe driving, Intelligent transportation system,
Driver distraction, Multiview, Multimodal, Multispectral, Public dataset
BibRef
Masood, S.[Sarfaraz],
Rai, A.[Abhinav],
Aggarwal, A.[Aakash],
Doja, M.N.,
Ahmad, M.[Musheer],
Detecting distraction of drivers using Convolutional Neural Network,
PRL(139), 2020, pp. 79-85.
Elsevier DOI
2011
Distracted driver, Deep learning, Convolutional Neural Network,
VGG16, VGG19
BibRef
Pavlidis, I.[Ioannis],
Khatri, A.[Ashik],
Buddharaju, P.[Pradeep],
Manser, M.[Michael],
Wunderlich, R.[Robert],
Akleman, E.[Ergun],
Tsiamyrtzis, P.[Panagiotis],
Biofeedback Arrests Sympathetic and Behavioral Effects in Distracted
Driving,
AffCom(12), No. 2, April 2021, pp. 453-465.
IEEE DOI
2106
Biological control systems, Vehicles, Drives, Image color analysis,
Imaging, Visualization, Biomedical monitoring, Biofeedback,
cusum
BibRef
Chen, J.[Jie],
Jiang, Y.N.[Ya-Nan],
Huang, Z.X.[Zhi-Xiang],
Guo, X.H.[Xiao-Hui],
Wu, B.C.[Bo-Cai],
Sun, L.[Long],
Wu, T.[Tao],
Fine-Grained Detection of Driver Distraction Based on Neural
Architecture Search,
ITS(22), No. 9, September 2021, pp. 5783-5801.
IEEE DOI
2109
Vehicles, Accidents, Manuals, Roads, Feature extraction, Safety,
Neural architecture search,
intelligent transportation systems
BibRef
Jin, L.S.[Li-Sheng],
Hua, Q.[Qiang],
Zhang, S.R.[Shun-Ran],
Guo, B.C.[Bai-Cang],
Stacking-based ensemble learning method for cognitive distraction
state recognition for drivers in traditional and connected
environments,
IET-ITS(16), No. 1, 2022, pp. 114-132.
DOI Link
2112
cognitive distraction, connected environment,
intelligent vehicle, stacking-based ensemble learning method
BibRef
Zhang, Y.L.[Yu-Le],
Zhu, S.L.[Shou-Lin],
The influence of landscape intervention used as an alertness
maintaining 'tool' on driving behaviour,
IET-ITS(16), No. 3, 2022, pp. 394-407.
DOI Link
2202
BibRef
Leicht, L.[Lennart],
Walter, M.[Marian],
Mathissen, M.[Marcel],
Antink, C.H.[Christoph Hoog],
Teichmann, D.[Daniel],
Leonhardt, S.[Steffen],
Unobtrusive Measurement of Physiological Features Under Simulated and
Real Driving Conditions,
ITS(23), No. 5, May 2022, pp. 4767-4777.
IEEE DOI
2205
Vehicles, Sensors, Temperature measurement, Heart rate, Imaging,
Physiology, Webcams, Hybrid imaging, unobtrusive, vital signs,
capacitive ECG
BibRef
Ahlström, C.[Christer],
Georgoulas, G.[George],
Kircher, K.[Katja],
Towards a Context-Dependent Multi-Buffer Driver Distraction Detection
Algorithm,
ITS(23), No. 5, May 2022, pp. 4778-4790.
IEEE DOI
2205
Vehicles, Roads, Mirrors, Monitoring, Gaze tracking, Visualization,
AttenD, classification, detection,
inattention
BibRef
Lu, K.[Ke],
Karlsson, J.[Johan],
Dahlman, A.S.[Anna Sjörs],
Sjöqvist, B.A.[Bengt Arne],
Candefjord, S.[Stefan],
Detecting Driver Sleepiness Using Consumer Wearable Devices in Manual
and Partial Automated Real-Road Driving,
ITS(23), No. 5, May 2022, pp. 4801-4810.
IEEE DOI
2205
Sleep, Vehicles, Heart rate variability, Monitoring,
Biomedical monitoring, Automation, Particle measurements,
machine learning
BibRef
Perello-March, J.R.[Jaume R.],
Burns, C.G.[Christopher G.],
Birrell, S.A.[Stewart A.],
Woodman, R.[Roger],
Elliott, M.T.[Mark T.],
Physiological Measures of Risk Perception in Highly Automated Driving,
ITS(23), No. 5, May 2022, pp. 4811-4822.
IEEE DOI
2205
Vehicles, Monitoring, Task analysis, Biomedical monitoring, Skin,
Stress, Human factors, Driver state monitoring,
risk perception
BibRef
Mathissen, M.[Marcel],
Hennes, N.[Nikica],
Faller, F.[Fabian],
Leonhardt, S.[Steffen],
Teichmann, D.[Daniel],
Investigation of Three Potential Stress Inducement Tasks During
On-Road Driving,
ITS(23), No. 5, May 2022, pp. 4823-4832.
IEEE DOI
2205
Stress, Task analysis, Vehicles, Physiology, Heart rate variability,
Protocols, Automation, Stress, workload, driver, sensor, ecg, hrv
BibRef
Hwang, S.[Steven],
Banerjee, A.G.[Ashis G.],
Boyle, L.N.[Linda Ng],
Predicting Driver's Transition Time to a Secondary Task Given an
in-Vehicle Alert,
ITS(23), No. 5, May 2022, pp. 4739-4745.
IEEE DOI
2205
Vehicles, Hidden Markov models, Task analysis, Data models,
Predictive models, Time factors, Information processing,
prediction
BibRef
Pipkorn, L.[Linda],
Victor, T.[Trent],
Dozza, M.[Marco],
Tivesten, E.[Emma],
Automation Aftereffects:
The Influence of Automation Duration, Test Track and Timings,
ITS(23), No. 5, May 2022, pp. 4746-4757.
IEEE DOI
2205
Automation, Vehicles, Manuals, Human factors, Task analysis, TV, Wheels,
Automated driving, driver response, driving performance,
automation
BibRef
Bohrmann, D.[Dominique],
Bruder, A.[Anna],
Bengler, K.[Klaus],
Effects of Dynamic Visual Stimuli on the Development of Carsickness
in Real Driving,
ITS(23), No. 5, May 2022, pp. 4833-4842.
IEEE DOI
2205
Light emitting diodes, Visualization, Vehicle dynamics, Dynamics,
Color, Automobiles, Task analysis, Autonomous vehicles, carsickness,
visual feedback system
BibRef
Fang, J.W.[Jian-Wu],
Yan, D.X.[Ding-Xin],
Qiao, J.H.[Jia-Huan],
Xue, J.R.[Jian-Ru],
Yu, H.K.[Hong-Kai],
DADA: Driver Attention Prediction in Driving Accident Scenarios,
ITS(23), No. 6, June 2022, pp. 4959-4971.
IEEE DOI
2206
Vehicles, Semantics, Accidents, Visualization, Roads, Convolution,
Predictive models, Driver attention prediction,
driving accident scenarios
BibRef
Xu, J.W.[Jia-Wei],
Park, S.H.[Seop Hyeong],
Zhang, X.Q.[Xiao-Qin],
Hu, J.[Jie],
The Improvement of Road Driving Safety Guided by Visual Inattentional
Blindness,
ITS(23), No. 6, June 2022, pp. 4972-4981.
IEEE DOI
2206
Visualization, Task analysis, Safety, Blindness, Vehicles,
Human factors, Computational modeling, Road driving safety,
eye fixation
BibRef
Amadori, P.V.[Pierluigi Vito],
Fischer, T.[Tobias],
Demiris, Y.F.[Yi-Fannis],
HammerDrive: A Task-Aware Driving Visual Attention Model,
ITS(23), No. 6, June 2022, pp. 5573-5585.
IEEE DOI
2206
Visualization, Vehicles, Task analysis, Predictive models,
Computational modeling, Real-time systems,
HAMMER
BibRef
Qin, B.B.[Bin-Bin],
Qian, J.B.[Jiang-Bo],
Xin, Y.[Yu],
Liu, B.S.[Bai-Song],
Dong, Y.H.[Yi-Hong],
Distracted Driver Detection Based on a CNN With Decreasing Filter
Size,
ITS(23), No. 7, July 2022, pp. 6922-6933.
IEEE DOI
2207
Convolution, Feature extraction, Real-time systems, Vehicles,
Graphics processing units, Deep learning, Task analysis, CNN
BibRef
Li, P.H.[Peng-Hua],
Yang, Y.F.[Yi-Feng],
Grosu, R.[Radu],
Wang, G.D.[Guo-Dong],
Li, R.[Rui],
Wu, Y.H.[Yue-Hong],
Huang, Z.[Zeng],
Driver Distraction Detection Using Octave-Like Convolutional Neural
Network,
ITS(23), No. 7, July 2022, pp. 8823-8833.
IEEE DOI
2207
Vehicles, Videos, Convolution, Cameras, Roads, Databases,
Data collection, Naturalistic driving, octave-like convolution,
lightweight neural network
BibRef
Tarabay, R.[Rana],
Abou-Zeid, M.[Maya],
A Dynamic Hybrid Choice Model to Quantify Stress in a Simulated
Driving Environment,
ITS(23), No. 7, July 2022, pp. 6390-6405.
IEEE DOI
2207
Stress, Vehicles, Mathematical model, Task analysis,
Stress measurement, Context modeling, Roads, Driver stress,
state detection
BibRef
Lin, C.T.[Chin-Teng],
Tian, Y.Q.[Yan-Qiu],
Wang, Y.K.[Yu-Kai],
Do, T.T.N.[Tien-Thong Nguyen],
Chang, Y.L.[Yao-Lung],
King, J.T.[Jung-Tai],
Huang, K.C.[Kuan-Chih],
Liao, L.D.[Lun-De],
Effects of Multisensory Distractor Interference on Attentional
Driving,
ITS(23), No. 8, August 2022, pp. 10395-10403.
IEEE DOI
2208
Task analysis, Electroencephalography, Visualization, Interference,
Wheels, Automobiles, Australia, Attentional driving,
brain oscillation
BibRef
Echanobe, J.[Javier],
Basterretxea, K.[Koldo],
del Campo, I.[Inés],
Martínez, V.[Victoria],
Vidal, N.[Naiara],
Multi-Objective Genetic Algorithm for Optimizing an ELM-Based Driver
Distraction Detection System,
ITS(23), No. 8, August 2022, pp. 11946-11959.
IEEE DOI
2208
Vehicles, Task analysis, Visualization, Proposals,
Feature extraction, Automobiles, Genetic algorithms, DAS,
feature selection
BibRef
Jha, S.[Sumit],
Marzban, M.F.[Mohamed F.],
Hu, T.C.[Tian-Cheng],
Mahmoud, M.H.[Mohamed H.],
Al-Dhahir, N.[Naofal],
Busso, C.[Carlos],
The Multimodal Driver Monitoring Database: A Naturalistic Corpus to
Study Driver Attention,
ITS(23), No. 8, August 2022, pp. 10736-10752.
IEEE DOI
2208
Vehicles, Magnetic heads, Cameras, Head, Monitoring, Annotations, Safety,
In-vehicle safety, driver visual attention, driver monitoring dataset
BibRef
Li, P.H.[Peng-Hui],
Li, Y.B.[Yi-Bing],
Yao, Y.[Yao],
Wu, C.X.[Chang-Xu],
Nie, B.B.[Bing-Bing],
Li, S.E.[Shengbo Eben],
Sensitivity of Electrodermal Activity Features for Driver Arousal
Measurement in Cognitive Load: The Application in Automated Driving
Systems,
ITS(23), No. 9, September 2022, pp. 14954-14967.
IEEE DOI
2209
Vehicles, Skin, Physiology, Sensitivity, Safety, Task analysis,
Heart rate, Automated driving systems, driver arousal,
skin conductance response (SCR)
BibRef
Xu, J.W.[Jia-Wei],
Zhang, X.Q.[Xiao-Qin],
Park, S.H.[Seop Hyeong],
Guo, K.[Kun],
The Alleviation of Perceptual Blindness During Driving in Urban Areas
Guided by Saccades Recommendation,
ITS(23), No. 9, September 2022, pp. 16386-16396.
IEEE DOI
2209
Visualization, Vehicles, Task analysis, Blindness,
Feature extraction, Delays, Roads, Saccades recommendation,
human factors in driving
BibRef
Huang, T.[Tao],
Fu, R.[Rui],
Driver Distraction Detection Based on the True Driver's Focus of
Attention,
ITS(23), No. 10, October 2022, pp. 19374-19386.
IEEE DOI
2210
Vehicles, Feature extraction, Convolution, Visualization,
Residual neural networks, Driver distraction detection, neural network
BibRef
Li, B.[Bing],
Chen, J.[Jie],
Huang, Z.X.[Zhi-Xiang],
Wang, H.T.[Hai-Tao],
Lv, J.M.[Jian-Ming],
Xi, J.M.[Jing-Min],
Zhang, J.[Jun],
Wu, Z.C.[Zhong-Cheng],
A New Unsupervised Deep Learning Algorithm for Fine-Grained Detection
of Driver Distraction,
ITS(23), No. 10, October 2022, pp. 19272-19284.
IEEE DOI
2210
Vehicles, Accidents, Feature extraction, Deep learning, Data models,
Convolutional neural networks, Computational modeling, multilayer perceptron
BibRef
Li, W.J.[Wen-Jing],
Wang, J.[Jing],
Ren, T.T.[Ting-Ting],
Li, F.[Fang],
Zhang, J.[Jun],
Wu, Z.C.[Zhong-Cheng],
Learning Accurate, Speedy, Lightweight CNNs via Instance-Specific
Multi-Teacher Knowledge Distillation for Distracted Driver Posture
Identification,
ITS(23), No. 10, October 2022, pp. 17922-17935.
IEEE DOI
2210
Vehicles, Computational modeling, Brain modeling,
Real-time systems, Accidents, Biomedical monitoring, Wheels,
lightweight
BibRef
Luo, L.X.[Long-Xi],
Wu, J.P.[Jian-Ping],
Fei, W.J.[Wei-Jie],
Bi, L.Z.[Lu-Zheng],
Fan, X.[Xinan],
Detecting Driver Cognition Alertness State From Visual Activities in
Normal and Emergency Scenarios,
ITS(23), No. 10, October 2022, pp. 19497-19510.
IEEE DOI
2210
Vehicles, Cognition, Computational modeling, Brain modeling,
Visualization, Iris, Faces, Driver cognition alertness state,
driver visual activity
BibRef
Yusof, N.M.[Nidzamuddin Md.],
Karjanto, J.[Juffrizal],
Hassan, M.Z.[Muhammad Zahir],
Terken, J.[Jacques],
Delbressine, F.[Frank],
Rauterberg, M.[Matthias],
Reading During Fully Automated Driving: A Study of the Effect of
Peripheral Visual and Haptic Information on Situation Awareness and
Mental Workload,
ITS(23), No. 10, October 2022, pp. 19136-19144.
IEEE DOI
2210
Visualization, Task analysis, Haptic interfaces,
Information systems, Vehicles, Automobiles, Situation awareness,
user experience
BibRef
Gan, S.[Shun],
Pei, X.[Xizhe],
Ge, Y.L.[Yu-Long],
Wang, Q.[Qingfan],
Shang, S.[Shi],
Li, S.E.[Shengbo Eben],
Nie, B.B.[Bing-Bing],
Multisource Adaption for Driver Attention Prediction in Arbitrary
Driving Scenes,
ITS(23), No. 11, November 2022, pp. 20912-20925.
IEEE DOI
2212
Vehicles, Adaptation models, Task analysis, Visualization,
Feature extraction, Computational modeling, Semantics, attention mechanism
BibRef
Wang, M.[Mei],
Ma, C.[Chen],
Li, Z.L.[Zhan-Li],
Zhang, S.M.[Si-Ming],
Li, Y.C.[Yuan-Cheng],
Alertness Estimation Using Connection Parameters of the Brain Network,
ITS(23), No. 12, December 2022, pp. 25448-25457.
IEEE DOI
2212
Electroencephalography, Estimation, Scalp, Visualization,
Brain modeling, Electrodes, Autonomous robots,
electroencephalograph signals
BibRef
Simpson, T.G.[Thomas G.],
Rafferty, K.[Karen],
EEG Correlates of Driving Performance,
HMS(52), No. 2, April 2022, pp. 232-247.
IEEE DOI
2203
Electroencephalography, Task analysis, Monitoring, Brain modeling,
Training, Psychology, Measurement, Electroencephalography,
regression modeling
BibRef
Hu, Z.X.[Zhong-Xu],
Zhang, Y.[Yiran],
Li, Q.H.[Qing-Hua],
Lv, C.[Chen],
A Novel Heterogeneous Network for Modeling Driver Attention With
Multi-Level Visual Content,
ITS(23), No. 12, December 2022, pp. 24343-24354.
IEEE DOI
2212
Feature extraction, Semantics, Visualization, Estimation,
Task analysis, Optical imaging, Object detection,
graph neural network
BibRef
Liu, D.[Dichao],
Yamasaki, T.[Toshihiko],
Wang, Y.[Yu],
Mase, K.[Kenji],
Kato, J.[Jien],
Toward Extremely Lightweight Distracted Driver Recognition With
Distillation-Based Neural Architecture Search and Knowledge Transfer,
ITS(24), No. 1, January 2023, pp. 764-777.
IEEE DOI
2301
Task analysis, Vehicles, Lighting, Knowledge engineering, Training,
Behavioral sciences, Distracted driving, decreasing filter size,
action recognition
BibRef
Balaji, A.[Aswin],
Tripathi, U.[Utkarsh],
Chamola, V.[Vinay],
Benslimane, A.[Abderrahim],
Guizani, M.[Mohsen],
Toward Safer Vehicular Transit: Implementing Deep Learning on Single
Channel EEG Systems for Microsleep Detection,
ITS(24), No. 1, January 2023, pp. 1052-1061.
IEEE DOI
2301
Electroencephalography, Sleep, Brain modeling, Training, Vehicles,
Internet of Things, Headphones, Brain-computer interface,
accident avoidance
BibRef
Wang, H.T.[Hai-Tao],
Chen, J.[Jie],
Huang, Z.X.[Zhi-Xiang],
Li, B.[Bing],
Lv, J.M.[Jian-Ming],
Xi, J.[Jingmin],
Wu, B.[Bocai],
Zhang, J.[Jun],
Wu, Z.C.[Zhong-Cheng],
FPT: Fine-Grained Detection of Driver Distraction Based on the
Feature Pyramid Vision Transformer,
ITS(24), No. 2, February 2023, pp. 1594-1608.
IEEE DOI
2302
Transformers, Vehicles, Feature extraction,
Convolutional neural networks, Accidents, Roads, Convolution, driving safety
BibRef
Sun, Q.[Qinyu],
Guo, Y.[Yingshi],
Liu, Y.T.[Yong-Tao],
Wang, C.[Chang],
Gu, M.[Menglu],
Su, Y.Q.[Yan-Qi],
Comparing the Effects of Visual Distraction in a High-Fidelity
Driving Simulator and on a Real Highway,
ITS(24), No. 4, April 2023, pp. 3738-3747.
IEEE DOI
2304
Task analysis, Visualization, Vehicles, Wheels, Mirrors, Standards,
Vehicle dynamics, Driving simulator, lane-keeping, validation,
visual distraction
BibRef
Sultana, R.[Rebeka],
Ohashi, G.[Gosuke],
Prediction of Driver's Visual Attention in Critical Moment Using
Optical Flow,
IEICE(E106-D), No. 5, May 2023, pp. 1018-1026.
WWW Link.
2305
BibRef
Guo, L.[Lie],
Xu, L.L.[Lin-Li],
Ge, P.S.[Ping-Shu],
Wang, X.[Xu],
How Resource Demands of Nondriving-Related Tasks and Engagement Time
Affect Drivers' Physiological Response and Takeover Performance in
Conditional Automated Driving,
HMS(53), No. 3, June 2023, pp. 600-609.
IEEE DOI
2306
Task analysis, Vehicles, Biomedical monitoring, Monitoring, Games,
Heart rate, Automation, Heart rate (HR), resource demand
BibRef
Morrison, T.N.[Tyler N.],
Jagacinski, R.J.[Richard J.],
Petrov, J.[Jordan],
Drivers' Attention to Preview and Its Momentary Persistence,
HMS(53), No. 3, June 2023, pp. 610-618.
IEEE DOI
2306
Perturbation methods, Particle measurements,
Atmospheric measurements, Feedback control, Vehicles, tracking
BibRef
Wang, J.[Jing],
Li, W.J.[Wen-Jing],
Li, F.[Fang],
Zhang, J.[Jun],
Wu, Z.C.[Zhong-Cheng],
Zhong, Z.[Zhun],
Sebe, N.[Nicu],
100-Driver: A Large-Scale, Diverse Dataset for Distracted Driver
Classification,
ITS(24), No. 7, July 2023, pp. 7061-7072.
IEEE DOI
2307
Vehicles, Behavioral sciences, Cameras, Accidents, Safety,
Task analysis, Roads, Distracted driver dataset, large-scale,
cross-vehicle
BibRef
Mittal, H.[Himanshu],
Verma, B.[Bindu],
CAT-CapsNet: A Convolutional and Attention Based Capsule Network to
Detect the Driver's Distraction,
ITS(24), No. 9, September 2023, pp. 9561-9570.
IEEE DOI
2310
BibRef
Duan, C.[Cong],
Gong, Y.P.[Yi-Peng],
Liao, J.[Jiacai],
Zhang, M.[Minghai],
Cao, L.[Libo],
FRNet: DCNN for Real-Time Distracted Driving Detection Toward
Embedded Deployment,
ITS(24), No. 9, September 2023, pp. 9835-9848.
IEEE DOI
2310
BibRef
Wang, J.[Jing],
Wu, Z.C.[Zhong-Cheng],
Driver distraction detection via multi-scale domain adaptation
network,
IET-ITS(17), No. 9, 2023, pp. 1742-1751.
DOI Link
2310
advanced driver assistance systems,
intelligent transportation systems, learning (artificial intelligence)
BibRef
Chen, H.Y.W.[Huei-Yen Winnie],
Xie, J.Y.[Jeanne Y.],
Donmez, B.[Birsen],
Gamification of Driver Distraction Feedback: A Simulator Study With
Younger Drivers,
HMS(53), No. 5, October 2023, pp. 813-822.
IEEE DOI
2310
BibRef
Bosch, E.[Esther],
Corbí, R.L.H.[Raquel Le Houcq],
Ihme, K.[Klas],
Hörmann, S.[Stefan],
Jipp, M.[Meike],
Käthner, D.[David],
Frustration Recognition Using Spatio Temporal Data: A Novel Dataset
and GCN Model to Recognize In-Vehicle Frustration,
AffCom(14), No. 4, October 2023, pp. 2864-2875.
IEEE DOI Code:
WWW Link.
2312
BibRef
Mou, L.[Luntian],
Zhao, Y.Y.[Yi-Yuan],
Zhou, C.[Chao],
Nakisa, B.[Bahareh],
Rastgoo, M.N.[Mohammad Naim],
Ma, L.[Lei],
Huang, T.J.[Tie-Jun],
Yin, B.C.[Bao-Cai],
Jain, R.[Ramesh],
Gao, W.[Wen],
Driver Emotion Recognition With a Hybrid Attentional Multimodal
Fusion Framework,
AffCom(14), No. 4, October 2023, pp. 2970-2981.
IEEE DOI
2312
BibRef
Yang, L.[Lie],
Yang, H.H.[Hao-Han],
Hu, B.B.[Bin-Bin],
Wang, Y.[Yan],
Lv, C.[Chen],
A Robust Driver Emotion Recognition Method Based on High-Purity
Feature Separation,
ITS(24), No. 12, December 2023, pp. 15092-15104.
IEEE DOI
2312
BibRef
Yang, H.H.[Hao-Han],
Liu, H.C.[Hao-Chen],
Hu, Z.X.[Zhong-Xu],
Nguyen, A.T.[Anh-Tu],
Guerra, T.M.[Thierry-Marie],
Lv, C.[Chen],
Quantitative Identification of Driver Distraction: A Weakly
Supervised Contrastive Learning Approach,
ITS(25), No. 2, February 2024, pp. 2034-2045.
IEEE DOI Code:
WWW Link.
2402
Behavioral sciences, Vehicles, Feature extraction, Transformers,
Training, Decoding, Support vector machines,
representation clustering
BibRef
Kuang, J.[Jian],
Li, W.J.[Wen-Jing],
Li, F.[Fang],
Zhang, J.[Jun],
Wu, Z.C.[Zhong-Cheng],
MIFI: MultI-Camera Feature Integration for Robust 3D Distracted
Driver Activity Recognition,
ITS(25), No. 1, January 2024, pp. 338-348.
IEEE DOI
2402
Behavioral sciences, Feature extraction, Cameras, Vehicles,
Three-dimensional displays, Task analysis, Activity recognition,
example re-weighting
BibRef
Hu, Z.X.[Zhong-Xu],
Cai, Y.X.[Yu-Xin],
Li, Q.H.[Qing-Hua],
Su, K.[Kui],
Lv, C.[Chen],
Context-Aware Driver Attention Estimation Using Multi-Hierarchy
Saliency Fusion With Gaze Tracking,
ITS(25), No. 8, August 2024, pp. 8602-8614.
IEEE DOI
2408
Vehicles, Estimation, Task analysis, Visualization,
Feature extraction, Context modeling, Predictive models,
multi-hierarchy fusion
BibRef
Nan, Z.X.[Zhi-Xiong],
Xiang, T.[Tao],
Third-Person View Attention Prediction in Natural Scenarios With Weak
Information Dependency and Human-Scene Interaction Mechanism,
CirSysVideo(34), No. 8, August 2024, pp. 6762-6773.
IEEE DOI
2408
Feature extraction, Computational modeling, Predictive models,
Transformers, Head, Cognition, Crops, Human attention, third-person view
BibRef
Chen, Y.L.[Yi-Long],
Nan, Z.X.[Zhi-Xiong],
Xiang, T.[Tao],
FBLNet: FeedBack Loop Network for Driver Attention Prediction,
ICCV23(13325-13334)
IEEE DOI
2401
BibRef
Li, G.[Guofa],
Wang, G.L.[Guang-Lei],
Guo, Z.Z.[Zi-Zheng],
Liu, Q.[Qing],
Luo, X.[Xiyuan],
Yuan, B.[Bangwei],
Li, M.[Mingrui],
Yang, L.[Lu],
Domain Adaptive Driver Distraction Detection Based on Partial Feature
Alignment and Confusion-Minimized Classification,
ITS(25), No. 9, September 2024, pp. 11227-11240.
IEEE DOI
2409
Feature extraction, Vehicles, Adaptation models,
Image classification, Training, Adaptive systems, Task analysis,
feature-level H-divergence
BibRef
Hasan, M.Z.[Md. Zahid],
Chen, J.J.[Jia-Jing],
Wang, J.[Jiyang],
Rahman, M.S.[Mohammed Shaiqur],
Joshi, A.[Ameya],
Velipasalar, S.[Senem],
Hegde, C.[Chinmay],
Sharma, A.[Anuj],
Sarkar, S.[Soumik],
Vision-Language Models Can Identify Distracted Driver Behavior From
Naturalistic Videos,
ITS(25), No. 9, September 2024, pp. 11602-11616.
IEEE DOI Code:
WWW Link.
2409
Videos, Vehicles, Adaptation models, Accidents, Training, Task analysis,
Data models, Distracted driving, computer vision, embedding
BibRef
Rafi, H.[Houda],
Benezeth, Y.[Yannick],
Reynaud, P.[Philippe],
Arnoux, E.[Emmanuel],
Song, F.Y.[Fan Yang],
Demonceaux, C.[Cedric],
Personalization of AI Models Based on Federated Learning for Driver
Stress Monitoring,
InVehicle22(575-585).
Springer DOI
2304
BibRef
Rafi, H.[Houda],
Benezeth, Y.[Yannick],
Reynaud, P.[Philippe],
Arnoux, E.[Emmanuel],
Song, F.Y.[Fan Yang],
Demonceaux, C.[Cedric],
Personalization of AI Models Based on Federated Learning for Driver
Stress Monitoring,
InVehicle22(575-585).
Springer DOI
2304
BibRef
Baee, S.[Sonia],
Pakdamanian, E.[Erfan],
Kim, I.[Inki],
Feng, L.[Lu],
Ordonez, V.[Vicente],
Barnes, L.[Laura],
MEDIRL: Predicting the Visual Attention of Drivers via Maximum
Entropy Deep Inverse Reinforcement Learning,
ICCV21(13158-13168)
IEEE DOI
2203
Visualization, Computational modeling, Reinforcement learning,
Predictive models, Benchmark testing, Entropy,
Vision for robotics and autonomous vehicles
BibRef
Gopinath, D.[Deepak],
Rosman, G.[Guy],
Stent, S.[Simon],
Terahata, K.[Katsuya],
Fletcher, L.[Luke],
Argall, B.[Brenna],
Leonard, J.[John],
MAAD: A Model and Dataset for 'Attended Awareness' in Driving,
EPIC21(3419-3429)
IEEE DOI
2112
Visualization, Computational modeling,
Noise reduction, Data models, Safety
BibRef
Wu, M.Y.[Ming-Yan],
Zhang, X.[Xi],
Shen, L.L.[Lin-Lin],
Yu, H.[Hang],
Pose-aware Multi-feature Fusion Network for Driver Distraction
Recognition,
ICPR21(1228-1235)
IEEE DOI
2105
Pose estimation, Feature extraction, Data mining, Accidents
BibRef
Xia, Y.[Ye],
Zhang, D.Q.[Dan-Qing],
Kim, J.K.[Jin-Kyu],
Nakayama, K.[Ken],
Zipser, K.[Karl],
Whitney, D.[David],
Predicting Driver Attention in Critical Situations,
ACCV18(V:658-674).
Springer DOI
1906
BibRef
Baheti, B.,
Gajre, S.,
Talbar, S.,
Detection of Distracted Driver Using Convolutional Neural Network,
AutoDrive18(1145-11456)
IEEE DOI
1812
Vehicles, Vehicle crash testing,
Convolutional neural networks, Task analysis, Wheels, Roads
BibRef
Borghi, G.,
Frigieri, E.,
Vezzani, R.,
Cucchiara, R.,
Hands on the wheel: A Dataset for Driver Hand Detection and Tracking,
FG18(564-570)
IEEE DOI
1806
Automobiles, Automotive engineering, Cameras, Task analysis,
Tracking, Wheels, Hand detection, automotive, dataset
BibRef
Theagarajan, R.,
Bhanu, B.,
Cruz, A.,
Le, B.,
Tambo, A.,
Novel representation for driver emotion recognition in motor vehicle
videos,
ICIP17(810-814)
IEEE DOI
1803
Correlation, Emotion recognition, Face, Gabor filters,
Spatiotemporal phenomena, Vehicle dynamics, Videos,
feature extraction
BibRef
Le, T.H.N.,
Quach, K.G.,
Zhu, C.,
Duong, C.N.,
Luu, K.,
Savvides, M.,
Robust Hand Detection and Classification in Vehicles and in the Wild,
CVVT17(1203-1210)
IEEE DOI
1709
Databases, Feature extraction, Object detection, Proposals,
Robustness, Support vector machines, Vehicles
BibRef
Ou, C.J.[Chao-Jie],
Ouali, C.[Chahid],
Karray, F.[Fakhri],
Transfer Learning Based Strategy for Improving Driver Distraction
Recognition,
ICIAR18(443-452).
Springer DOI
1807
BibRef
Koesdwiady, A.[Arief],
Bedawi, S.M.[Safaa M.],
Ou, C.J.[Chao-Jie],
Karray, F.[Fakhri],
End-to-End Deep Learning for Driver Distraction Recognition,
ICIAR17(11-18).
Springer DOI
1706
BibRef
Ragab, A.[Amira],
Craye, C.[Celine],
Kamel, M.S.[Mohamed S.],
Karray, F.[Fakhri],
A Visual-Based Driver Distraction Recognition and Detection Using
Random Forest,
ICIAR14(I: 256-265).
Springer DOI
1410
BibRef
Rezaei, M.[Mahdi],
Klette, R.[Reinhard],
Look at the Driver, Look at the Road: No Distraction! No Accident!,
CVPR14(129-136)
IEEE DOI
1409
2D to 3D modelling
BibRef
Rezaei, M.[Mahdi],
Klette, R.[Reinhard],
Novel Adaptive Eye Detection and Tracking for Challenging Lighting
Conditions,
DTCE12(II:427-440).
Springer DOI
1304
BibRef
Earlier:
3D Cascade of Classifiers for Open and Closed Eye Detection in Driver
Distraction Monitoring,
CAIP11(II: 171-179).
Springer DOI
1109
BibRef
Kutila, M.[Matti],
Jokela, M.[Maria],
Markkula, G.[Gustav],
Rue, M.R.[Maria Romera],
Driver Distraction Detection with a Camera Vision System,
ICIP07(VI: 201-204).
IEEE DOI
0709
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Driver Fatigue .