15.3.1.2.2 Driver Modeling, Behavior Models, Analysis

Chapter Contents (Back)
Driver Assistance. Driver Behavior.

Hu, J.S., Cheng, C.C., Liu, W.H.,
Robust Speaker's Location Detection in a Vehicle Environment Using GMM Models,
SMC-B(36), No. 2, April 2006, pp. 403-412.
IEEE DOI 0604
BibRef

Yamada, K., Kuchar, J.K.,
Preliminary study of behavioral and safety effects of driver dependence on a warning system in a driving simulator,
SMC-A(36), No. 3, May 2006, pp. 602-610.
IEEE DOI 0606
BibRef

Cheng, H., Zheng, N., Zhang, X., Qin, J., van de Wetering, H.,
Interactive Road Situation Analysis for Driver Assistance and Safety Warning Systems: Framework and Algorithms,
ITS(8), No. 1, March 2007, pp. 157-167.
IEEE DOI 0703
BibRef

Li, Z.H.[Zhi-Heng], Li, L.[Li], Zhang, Y.[Yi],
IVS 09: Future Research in Vehicle Vision Systems,
IEEE_Int_Sys(24), No. 6, November-December 2009, pp. 62-65.
IEEE DOI 1001
BibRef

Amditis, A., Bertolazzi, E., Bimpas, M., Biral, F., Bosetti, P., Da Lio, M., Danielsson, L., Gallione, A., Lind, H., Saroldi, A., Sjogren, A.,
A Holistic Approach to the Integration of Safety Applications: The INSAFES Subproject Within the European Framework Programme 6 Integrating Project PReVENT,
ITS(11), No. 3, September 2010, pp. 554-566.
IEEE DOI 1003
BibRef

Amditis, A., Da Lio, M., Goudy, R.,
Guest Editorial Special Section on ITS and Road Safety,
ITS(11), No. 3, September 2010, pp. 524-524.
IEEE DOI 1003
Special section introduction. BibRef

Zhang, Y.[Yilu], Lin, W.C., Chin, Y.K.S.,
A Pattern-Recognition Approach for Driving Skill Characterization,
ITS(11), No. 4, December 2010, pp. 905-916.
IEEE DOI 1101
BibRef

Younsi, K., Loslever, P., Popieul, J.C., Simon, P.,
Fuzzy Segmentation for the Exploratory Analysis of Multidimensional Signals: Example From a Study on Driver Overtaking Behavior,
SMC-A(41), No. 5, September 2011, pp. 892-904.
IEEE DOI 1109
BibRef

Boyle, R.[Rebecca],
How Intelligent Cars Will Make Driving Easier and Greener,
PopSci(News), July 18, 2011.
WWW Link. A new generation of smarter-car technology is helping drivers and cars manage trips more efficiently, preventing gridlock, avoiding wrecks and ameliorating 5 p.m. road rage BibRef 1107

Riener, A.,
Subliminal Persuasion and Its Potential for Driver Behavior Adaptation,
ITS(13), No. 1, March 2012, pp. 71-80.
IEEE DOI 1203
BibRef

Fuller, H.J.A., Reed, M.P., Liu, Y.[Yili],
Integration of Physical and Cognitive Human Models to Simulate Driving With a Secondary In-Vehicle Task,
ITS(13), No. 2, June 2012, pp. 967-972.
IEEE DOI 1206
BibRef

Trommer, S., Höltl, A.,
Perceived usefulness of eco-driving assistance systems in Europe,
IET-ITS(6), No. 2, 2012, pp. 145-152.
DOI Link 1206
BibRef

Takeda, K., Miyajima, C., Suzuki, T., Angkititrakul, P., Kurumida, K., Kuroyanagi, Y., Ishikawa, H., Terashima, R., Wakita, T., Oikawa, M., Komada, Y.,
Self-Coaching System Based on Recorded Driving Data: Learning From One's Experiences,
ITS(13), No. 4, December 2012, pp. 1821-1831.
IEEE DOI 1212
BibRef

Windridge, D., Shaukat, A., Hollnagel, E.,
Characterizing Driver Intention via Hierarchical Perception-Action Modeling,
HMS(43), No. 1, January 2013, pp. 17-31.
IEEE DOI 1301
BibRef

Okuda, H., Ikami, N., Suzuki, T., Tazaki, Y., Takeda, K.,
Modeling and Analysis of Driving Behavior Based on a Probability-Weighted ARX Model,
ITS(14), No. 1, March 2013, pp. 98-112.
IEEE DOI 1303
BibRef

Berthoz, A., Bles, W., Bulthoff, H.H., Correia Gracio, B.J., Feenstra, P., Filliard, N., Huhne, R., Kemeny, A., Mayrhofer, M., Mulder, M., Nusseck, H.G., Pretto, P., Reymond, G., Schlusselberger, R., Schwandtner, J., Teufel, H., Vailleau, B., van Paassen, M.M., Vidal, M., Wentink, M.,
Motion Scaling for High-Performance Driving Simulators,
HMS(43), No. 3, May 2013, pp. 265-276.
IEEE DOI 1305
BibRef

Malikopoulos, A.A., Aguilar, J.P.,
An Optimization Framework for Driver Feedback Systems,
ITS(14), No. 2, 2013, pp. 955-964.
IEEE DOI 1307
automotive electronics; fuel economy; road traffic BibRef

Schiebi, C., Fricke, N., Staubach, M.,
Identification and analysis of motives for eco-friendly driving within the eco-move project,
IET-ITS(7), No. 1, 2013, pp. 46-54.
DOI Link 1307
BibRef

Llorca, C., Garcia, A., Moreno, A.T., Perez-Zuriaga, A.M.,
Influence of age, gender and delay on overtaking dynamics,
IET-ITS(7), No. 2, 2013, pp. -.
DOI Link 1307
BibRef

Gouy, M., Diels, C., Reed, N., Stevens, A., Burnett, G.,
Do drivers reduce their headway to a lead vehicle because of the presence of platoons in traffic? a conformity study conducted within a simulator,
IET-ITS(7), No. 2, 2013, pp. -.
DOI Link 1307
BibRef

Moreno, A.T., Garcia, A., Camacho-Torregrosa, F.J., Llorca, C.,
Influence of highway three-dimensional coordination on drivers perception of horizontal curvature and available sight distance,
IET-ITS(7), No. 2, 2013, pp. -.
DOI Link 1307
BibRef

Xiong, C., Zhang, L.,
A Descriptive Bayesian Approach to Modeling and Calibrating Drivers' En Route Diversion Behavior,
ITS(14), No. 4, 2013, pp. 1817-1824.
IEEE DOI 1312
Bayes methods BibRef

Gadepally, V., Krishnamurthy, A., Ozguner, U.,
A Framework for Estimating Driver Decisions Near Intersections,
ITS(15), No. 2, April 2014, pp. 637-646.
IEEE DOI 1404
Decision support systems BibRef

Geyer, S., Baltzer, M., Franz, B., Hakuli, S., Kauer, M., Kienle, M., Meier, S., Weissgerber, T., Bengler, K., Bruder, R., Flemisch, F., Winner, H.,
Concept and development of a unified ontology for generating test and use-case catalogues for assisted and automated vehicle guidance,
IET-ITS(8), No. 3, May 2014, pp. 183-189.
DOI Link 1407
BibRef

Ho, C., Gray, R., Spence, C.,
To What Extent do the Findings of Laboratory-Based Spatial Attention Research Apply to the Real-World Setting of Driving?,
HMS(44), No. 4, August 2014, pp. 524-530.
IEEE DOI 1407
Accidents BibRef

Birrell, S.A., Fowkes, M., Jennings, P.A.,
Effect of Using an In-Vehicle Smart Driving Aid on Real-World Driver Performance,
ITS(15), No. 4, August 2014, pp. 1801-1810.
IEEE DOI 1410
driver information systems BibRef

Stahl, P., Donmez, B., Jamieson, G.A.,
Anticipation in Driving: The Role of Experience in the Efficacy of Pre-event Conflict Cues,
HMS(44), No. 5, October 2014, pp. 603-613.
IEEE DOI 1411
biomedical measurement BibRef

Qu, T., Chen, H., Cao, D., Guo, H., Gao, B.,
Switching-Based Stochastic Model Predictive Control Approach for Modeling Driver Steering Skill,
ITS(16), No. 1, February 2015, pp. 365-375.
IEEE DOI 1502
Force BibRef

Fussl, E., Oberlader, M., Beanland, V., Spyropoulou, I., Lenne, M.G., Joshi, S., Roßger, L., Leden, L., Underwood, G., Carvalhais, J.,
Methodological development of a specific tool for assessing acceptability of assistive systems of powered two-wheeler-riders,
IET-ITS(9), No. 1, 2015, pp. 12-21.
DOI Link 1503
driver information systems BibRef

Guo, W.H.[Wei-Hong], Blythe, P.T., Edwards, S., Pavkova, K., Brennan, D.,
Effect of intelligent speed adaptation technology on older drivers: driving performance,
IET-ITS(9), No. 3, 2015, pp. 343-350.
DOI Link 1506
automated highways BibRef

Spyropoulou, I., Antoniou, C.,
Determinants of driver response to variable message sign information in Athens,
IET-ITS(9), No. 4, 2015, pp. 453-466.
DOI Link 1506
behavioural sciences computing BibRef

He, Y.[Yi], Yan, X.[Xinping], Wu, C.[Chaozhong], Zhong, M.[Ming], Chu, D.[Duanfeng], Huang, Z.[Zhen], Wang, X.[Xu],
Evaluation of the effectiveness of auditory speeding warnings for commercial passenger vehicles: A field study in Wuhan, China,
IET-ITS(9), No. 4, 2015, pp. 467-476.
DOI Link 1506
alarm systems BibRef

Yang, Y.[Yan], Wong, A., McDonald, M.,
Does gender make a difference to performing in-vehicle tasks?,
IET-ITS(9), No. 4, 2015, pp. 359-365.
DOI Link 1506
Driver evaluation. behavioural sciences computing BibRef

Lanata, A., Valenza, G., Greco, A., Gentili, C., Bartolozzi, R., Bucchi, F., Frendo, F., Scilingo, E.P.,
How the Autonomic Nervous System and Driving Style Change With Incremental Stressing Conditions During Simulated Driving,
ITS(16), No. 3, June 2015, pp. 1505-1517.
IEEE DOI 1506
Biomedical monitoring BibRef

Wang, J.Q.[Jian-Qiang], Xiong, C.[Chenfeng], Lu, M.[Meng], Li, K.Q.[Ke-Qiang],
Longitudinal driving behaviour on different roadway categories: An instrumented-vehicle experiment, data collection and case study in China,
IET-ITS(9), No. 5, 2015, pp. 555-563.
DOI Link 1507
driver information systems BibRef

Malik, H., Larue, G.S., Rakotonirainy, A., Maire, F.,
Fuzzy Logic to Evaluate Driving Maneuvers: An Integrated Approach to Improve Training,
ITS(16), No. 4, August 2015, pp. 1728-1735.
IEEE DOI 1508
Computer crashes BibRef

Oeltze, K., Schießl, C.,
Benefits and challenges of multi-driver simulator studies,
IET-ITS(9), No. 6, 2015, pp. 618-625.
DOI Link 1509
behavioural sciences computing BibRef

Haupt, J., Kahvežic-Seljubac, A., Risser, R.,
Role of driver assistance experience, system functionality, gender, age and sensation seeking in attitudes towards the safety of driver assistance systems,
IET-ITS(9), No. 7, 2015, pp. 716-726.
DOI Link 1509
driver information systems BibRef

Schindhelm, R., Schmidt, E.,
Evaluation of the tactile detection response task in a laboratory test using a surrogate driving set-up,
IET-ITS(9), No. 7, 2015, pp. 683-689.
DOI Link 1509
haptic interfaces BibRef

Valero-Mora, P.M., Pareja, I., Pons, D., Sánchez, M., Montes, S.A., Ledesma, R.D.,
Mindfulness, inattention and performance in a driving simulator,
IET-ITS(9), No. 7, 2015, pp. 690-693.
DOI Link 1509
cognition BibRef

Eyssartier, C.,
Acceptability of driving an equipped vehicle with drive recorder: The impact of the context,
IET-ITS(9), No. 7, 2015, pp. 710-715.
DOI Link 1509
data recording BibRef

Xu, L.[Li], Hu, J.[Jie], Jiang, H.[Hong], Meng, W.[Wuqiang],
Establishing Style-Oriented Driver Models by Imitating Human Driving Behaviors,
ITS(16), No. 5, October 2015, pp. 2522-2530.
IEEE DOI 1511
automobile industry BibRef

Oorni, R.,
Demand for intelligent vehicle safety systems in Europe,
IET-ITS(9), No. 10, 2015, pp. 916-923.
DOI Link 1512
intelligent transportation systems BibRef

Shi, B., Xu, L., Hu, J., Tang, Y., Jiang, H., Meng, W., Liu, H.,
Evaluating Driving Styles by Normalizing Driving Behavior Based on Personalized Driver Modeling,
SMCS(45), No. 12, December 2015, pp. 1502-1508.
IEEE DOI 1512
Adaptation models BibRef

Tang, K., Zhu, S., Xu, Y., Wang, F.,
Modeling Drivers' Dynamic Decision-Making Behavior During the Phase Transition Period: An Analytical Approach Based on Hidden Markov Model Theory,
ITS(17), No. 1, January 2016, pp. 206-214.
IEEE DOI 1601
Acceleration BibRef

Dey, K.C., Yan, L., Wang, X., Wang, Y., Shen, H., Chowdhury, M., Yu, L., Qiu, C., Soundararaj, V.,
A Review of Communication, Driver Characteristics, and Controls Aspects of Cooperative Adaptive Cruise Control (CACC),
ITS(17), No. 2, February 2016, pp. 491-509.
IEEE DOI 1602
Delays BibRef

Castaldo, F., Palmieri, F.A.N., Regazzoni, C.S.,
Bayesian Analysis of Behaviors and Interactions for Situation Awareness in Transportation Systems,
ITS(17), No. 2, February 2016, pp. 313-322.
IEEE DOI 1602
Analytical models BibRef

Qi, G., Du, Y., Wu, J., Hounsell, N., Jia, Y.,
What is the Appropriate Temporal Distance Range for Driving Style Analysis?,
ITS(17), No. 5, May 2016, pp. 1393-1403.
IEEE DOI 1605
Analytical models BibRef

Bender, A., Ward, J.R., Worrall, S., Moreyra, M.L., Konrad, S.G.[S. Gerling], Masson, F., Nebot, E.M.,
A Flexible System Architecture for Acquisition and Storage of Naturalistic Driving Data,
ITS(17), No. 6, June 2016, pp. 1748-1761.
IEEE DOI 1606
Computer architecture BibRef

Yang, B., Zheng, R., Yin, Y., Yamabe, S., Nakano, K.,
Analysis of influence on driver behaviour while using in-vehicle traffic lights with application of head-up display,
IET-ITS(10), No. 5, 2016, pp. 347-353.
DOI Link 1608
behavioural sciences computing BibRef

Hwang, Y.[Yoonsook], Park, B.J.[Byoung-Jun], Kim, K.H.[Kyong-Ho],
Effects of Augmented-Reality Head-up Display System Use on Risk Perception and Psychological Changes of Drivers,
ETRI(38), No. 4, August 2016, pp. 757-766.
DOI Link 1608
BibRef

Zeng, W., Miwa, T., Morikawa, T.,
Application of hyperpath strategy and driving experience to risk-averse navigation,
IET-ITS(10), No. 5, 2016, pp. 338-346.
DOI Link 1608
navigation BibRef

Morton, J., Wheeler, T.A., Kochenderfer, M.J.,
Analysis of Recurrent Neural Networks for Probabilistic Modeling of Driver Behavior,
ITS(18), No. 5, May 2017, pp. 1289-1298.
IEEE DOI 1705
Acceleration, Hidden Markov models, Mathematical model, Predictive models, Recurrent neural networks, Vehicles, Recurrent neural networks, autonomous vehicles, car-following models, deep learning, prediction, methods BibRef

Wang, D., Ma, X., Ma, D., Jin, S.,
A Novel Speed-Density Relationship Model Based on the Energy Conservation Concept,
ITS(18), No. 5, May 2017, pp. 1179-1189.
IEEE DOI 1705
Automobiles, Data models, Energy conservation, Mathematical model, Psychology, Driver's psychological field, energy conservation concept, fundamental diagram, speed-density, relationship BibRef

Hansen, J.H.L., Busso, C., Zheng, Y., Sathyanarayana, A.,
Driver Modeling for Detection and Assessment of Driver Distraction: Examples from the UTDrive Test Bed,
SPMag(34), No. 4, July 2017, pp. 130-142.
IEEE DOI 1708
Autonomous vehicles, Hidden Markov models, Intelligent vehicles, Sensors, Vehicle safety, Vehicular ad hoc networks, Visualization BibRef

Zhao, L.H.[Li-Hua], Ichise, R.[Ryutaro], Liu, Z.[Zheng], Mita, S.[Seiichi], Sasaki, Y.[Yutaka],
Ontology-Based Driving Decision Making: A Feasibility Study at Uncontrolled Intersections,
IEICE(E100-D), No. 7, July 2017, pp. 1425-1439.
WWW Link. 1708
BibRef

Zeng, X., Wang, J.,
A Stochastic Driver Pedal Behavior Model Incorporating Road Information,
HMS(47), No. 5, October 2017, pp. 614-624.
IEEE DOI 1709
Hidden Markov models, Mechanical power transmission, Predictive models, Roads, Sensors, Torque, Vehicles, Driver attention and cognition, driver modeling and state detection, hidden Markov models, intelligent vehicles, stochastic, systems BibRef

Schnelle, S., Wang, J., Su, H.J., Jagacinski, R.,
A Personalizable Driver Steering Model Capable of Predicting Driver Behaviors in Vehicle Collision Avoidance Maneuvers,
HMS(47), No. 5, October 2017, pp. 625-635.
IEEE DOI 1709
Feedforward neural networks, Mathematical model, Predictive models, Road transportation, Trajectory, Vehicles, Wheels, Collision avoidance, driver modeling and state detection, driver-automation collaboration, steering, model BibRef

Wang, W., Xi, J., Chong, A., Li, L.,
Driving Style Classification Using a Semisupervised Support Vector Machine,
HMS(47), No. 5, October 2017, pp. 650-660.
IEEE DOI 1709
Hidden Markov models, Kernel, Labeling, Optimization, Support vector machines, Training data, Vehicles, Driving style classification, longitudinal driving behavior, nonconvex optimization, quasi-Newton (QN) methods, semisupervised, support, vector, machine, (S3VM) BibRef

McIlroy, R.C., Stanton, N.A., Godwin, L., Wood, A.P.,
Encouraging Eco-Driving With Visual, Auditory, and Vibrotactile Stimuli,
HMS(47), No. 5, October 2017, pp. 661-672.
IEEE DOI 1709
Acceleration, Fuels, Gears, Haptic interfaces, Software, Vehicles, Visualization, Eco-driving, in-vehicle information, multimodal, displays BibRef

You, C., Lu, J., Tsiotras, P.,
Nonlinear Driver Parameter Estimation and Driver Steering Behavior Analysis for ADAS Using Field Test Data,
HMS(47), No. 5, October 2017, pp. 686-699.
IEEE DOI 1709
Data models, Hidden Markov models, Kalman filters, Roads, Vehicles, Visualization, Wheels, Extended Kalman filter (EKF), field test, parameter estimation, two-point visual driver model, unscented Kalman filter (UKF), wavelet, signal, analysis BibRef

Nilsson, P., Laine, L., Jacobson, B.,
A Simulator Study Comparing Characteristics of Manual and Automated Driving During Lane Changes of Long Combination Vehicles,
ITS(18), No. 9, September 2017, pp. 2514-2524.
IEEE DOI 1709
braking, motion control, optimisation, road traffic control, road vehicles, steering systems, A-double long combination vehicle, automated driving, braking, driver acceptance, driver behavior, driver model control, lane changes, lane-change maneuvers, long combination vehicles, manual driving, moving-base truck driving simulator, optimization-based control, safety-critical lane-change scenario, steering behavior, Automation, Automobiles, Lead, Manuals, Roads, Safety, Automated highway vehicle, driving simulator, heavy-duty vehicle, lane, change BibRef

Liu, H., Taniguchi, T., Tanaka, Y., Takenaka, K., Bando, T.,
Visualization of Driving Behavior Based on Hidden Feature Extraction by Using Deep Learning,
ITS(18), No. 9, September 2017, pp. 2477-2489.
IEEE DOI 1709
driving behavior data BibRef

Castignani, G., Derrmann, T., Frank, R., Engel, T.,
Smartphone-Based Adaptive Driving Maneuver Detection: A Large-Scale Evaluation Study,
ITS(18), No. 9, September 2017, pp. 2330-2339.
IEEE DOI 1709
distributed telematics, supervised learning, Driving maneuver detection, anomaly detection BibRef

Tang, T.Q.[Tie-Qiao], Yi, Z.Y.[Zhi-Yan], Zhang, J.[Jian], Zheng, N.[Nan],
Modelling the driving behaviour at a signalised intersection with the information of remaining green time,
IET-ITS(11), No. 9, November 2017, pp. 596-603.
DOI Link 1710
BibRef

Eboli, L.[Laura], Mazzulla, G.[Gabriella], Pungillo, G.[Giuseppe],
Measuring the driver's perception error in the traffic accident risk evaluation,
IET-ITS(11), No. 10, December 2017, pp. 659-666.
DOI Link 1711
BibRef

Ahlstrom, C., Kircher, K.,
A Generalized Method to Extract Visual Time-Sharing Sequences From Naturalistic Driving Data,
ITS(18), No. 11, November 2017, pp. 2929-2938.
IEEE DOI 1711
Data mining, Gaze tracking, Mirrors, Roads, Uncertainty, Vehicles, Visualization, Driver behaviour, glance analysis, visual, time-sharing BibRef

Gruber, T.[Thierry], Larue, G.S.[Grégoire S.], Rakotonirainy, A.[Andry], Poulsen, N.K.[Niels K.],
Developing a simulation framework for safe and optimal trajectories considering drivers' driving style,
IET-ITS(11), No. 10, December 2017, pp. 624-631.
DOI Link 1711
BibRef


Xu, H., Gao, Y., Yu, F., Darrell, T.,
End-to-End Learning of Driving Models from Large-Scale Video Datasets,
CVPR17(3530-3538)
IEEE DOI 1711
Computer architecture, Data models, Motion segmentation, Predictive models, Training, Visualization BibRef

Minhas, S.[Saad], Hernández-Sabaté, A.[Aura], Ehsan, S.[Shoaib], Díaz-Chito, K.[Katerine], Leonardis, A.[Ales], López, A.M.[Antonio M.], McDonald-Maier, K.D.[Klaus D.],
LEE: A Photorealistic Virtual Environment for Assessing Driver-Vehicle Interactions in Self-driving Mode,
VARVAI16(III: 894-900).
Springer DOI 1611
BibRef

Chang, S.P.[Shao-Pin], Chien, J.T.[Jui-Ting], Wang, F.E.[Fu-En], Yang, S.D.[Shang-Da], Chen, H.T.[Hwann-Tzong], Sun, M.[Min],
Extracting Driving Behavior: Global Metric Localization from Dashcam Videos in the Wild,
CVRoads16(I: 136-148).
Springer DOI 1611
BibRef

Bradler, H., Wiegand, B.A., Mester, R.,
The Statistics of Driving Sequences -- And What We Can Learn from Them,
CVRoads15(106-114)
IEEE DOI 1602
Adaptive optics BibRef

Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Lane Departure Detection, Lane Control Assistance, Lateral Control .


Last update:Nov 18, 2017 at 20:56:18