16.7.2.8.3 Driver Distraction Analysis, Driver Attention, Driver Inattention

Chapter Contents (Back)
Driver Assistance. Driver Distraction. Driver Attention.
See also Driver Fatigue.

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. BibRef

Liang, Y., 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

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,
ELCVIA(16), No. 2, 2017, pp. 25-28.
DOI Link 1804
BibRef

Wan, P.[Ping], Wu, C.Z.[Chao-Zhong], Lin, Y.Z.[Ying-Zi], Ma, X.F.[Xiao-Feng],
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., Gao, H., 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], 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


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

Akdag, E.[Erkut], Zhu, Z.[Zeqi], Bondarev, E.[Egor], de With, P.H.N.[Peter H. N.],
Transformer-based Fusion of 2D-pose and Spatio-temporal Embeddings for Distracted Driver Action Recognition,
AICity23(5453-5462)
IEEE DOI 2309
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 .


Last update:May 23, 2024 at 14:31:23