Eraqi, H.M.[Hesham M.],
Abouelnaga, Y.[Yehya],
Saad, M.H.[Mohamed H.],
Moustafa, M.N.[Mohamed N.],
Distracted Driver Dataset,
WWW Link.
Dataset, Driver Monitoring. Includes Distracted Driver V1 and Distracted Driver V2.
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Reyes, M.L.,
Lee, J.D.,
Real-Time Detection of Driver Cognitive Distraction Using Support
Vector Machines,
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
accidents,
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
Bi, L.,
Gan, G.,
Shang, J.,
Liu, Y.,
Queuing Network Modeling of Driver Lateral Control With or Without a
Cognitive Distraction Task,
ITS(13), No. 4, December 2012, pp. 1810-1820.
IEEE DOI
1212
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
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ITS(14), No. 3, 2013, pp. 1547-1555.
IEEE DOI
1309
Cumulative driver off-road glance duration
BibRef
Siordia, O.S.[Oscar S.],
Martín de Diego, I.[Isaac],
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Cabello, E.[Enrique],
Subjective Traffic Safety Experts' Knowledge for Driving-Risk
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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
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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.,
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Online Prediction of Driver Distraction Based on Brain Activity
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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
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
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Villán, A.F.[Alberto Fernández],
Facial attributes recognition using computer vision to detect
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BibRef
Wan, P.[Ping],
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IET-ITS(11), No. 5, June 2017, pp. 290-298.
DOI Link
1705
BibRef
Yüce, A.,
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Cuendet, G.L.,
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],
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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.,
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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.[YaNan],
Huang, Z.[ZhiXiang],
Guo, X.[XiaoHui],
Wu, B.[BoCai],
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,
Computer architecture, 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
Bakker, B.[Bram],
Zablocki, B.[Bartosz],
Baker, A.[Angela],
Riethmeister, V.[Vanessa],
Marx, B.[Bernd],
Iyer, G.[Girish],
Anund, A.[Anna],
Ahlström, C.[Christer],
A Multi-Stage, Multi-Feature Machine Learning Approach to Detect
Driver Sleepiness in Naturalistic Road Driving Conditions,
ITS(23), No. 5, May 2022, pp. 4791-4800.
IEEE DOI
2205
Sleep, Vehicles, Fatigue, Feature extraction, Roads,
Hidden Markov models, Faces, Fatigue detection, video-based,
field trial
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.[Yiannis],
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, Computer architecture,
HAMMER
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, Computer architecture, 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.[Chaojie],
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.[Chaojie],
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
License Plate Recognition, Extraction, Analysis .