JTTs  Vol.7 No.3 , July 2017
Evaluation of Driver Distraction with Changes in Gaze Direction Based on a Vestibulo-Ocular Reflex Model
Abstract: With the aim of improving parameter identification and, eventually, evaluating driver distraction with changes in gaze direction, we applied a genetic algorithm (GA) method to identify parameters for an existing vestibulo-ocular reflex (VOR) model. By changing the initial inputs to the GA and fixing two parameters pertaining to the horizontal direction, we achieved improved parameter identification with a lower mean-square error. The influence of driver distraction on eye movement with changes in gaze direction was evaluated from the difference between the predicted and observed VOR in the vertical axis. When a driver was given an additional mental workload, the mean-square error between the measured and simulated values was bigger than that in the absence of the mental workload. This confirmed the relationship between driver distraction and eye movement in the vertical direction. We hope that this method can be applied in evaluating driver distraction.
Cite this paper: Son, L. , Aoki, H. and Suzuki, T. (2017) Evaluation of Driver Distraction with Changes in Gaze Direction Based on a Vestibulo-Ocular Reflex Model. Journal of Transportation Technologies, 7, 336-350. doi: 10.4236/jtts.2017.73022.

[1]   Merfeld, D.M. and Zupan, L.H. (2002) Neural Processing of Gravitoinertial Cues in Humans. III. Modeling Tilt and Translation Responses. Journal of Neurophysiology, 87, 819-833.

[2]   Robinson, D.A. (1981) The Use of Control Systems Analysis in the Neurophysiology of Eye Movements. Annual Review of Neuroscience, 4, 463-503.

[3]   Obinata, G., Tokuda, S., Fukuda, K. and Hamada, H. (2009) Quantitative Evaluation of Mental Workload by Using Model of Involuntary Eye Movement. In: Harris, D., Ed., En-gineering Psychology and Cognitive Ergonomics SE-24, Vol. 5639, Springer Berlin Heidelberg, 223-232.

[4]   Obinata, G., Usui, T. and Shibata, N. (2008) On-Line Method for Evaluating Driver Dis-traction of Memory-Decision Workload Based on Dynamics of Vestibulo-Ocu- lar Reflex. Review of Automotive Engineering, 29, 627-632.

[5]   Munster, D. (2009) Parameter Identification: A Comparison of Methods.

[6]   Goldberg, D.E. (1989) Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Longman Publishing Co. Inc., Boston, MA, USA.

[7]   Pearl, J. (2001) Parameter Identication: A New Perspective (Second Draft). Introduction and Preliminary Terminology, 1, 1-19.

[8]   Wang, G.S., Huang, F.K. and Lin, H.H. (2004) Application of Genetic Algorithm to Structural Dynamic Parameter Identification. 13th World Conference on Earthquake Engineering, Vancouver, 1-6 August 2004, Paper No. 3227.

[9]   Petcu, F. and Leonida-Dragomir, T. (2010) Solar Cell Parameter Identification Using Genetic Algorithms. CEAI, 12, 30-37.

[10]   Omura, K., Aoki, H. and Obinata, G. (2015) Objective Evaluation of the Brake Motion by Means of Passenger’s Reflex Eye Movements. 13th International Symposium on Ad-vanced Vehicle Control, Munich, Germany.

[11]   Usui, T., Obinata, G. and Shibata, N. (2007) On-Line Method for Evaluating the Driver Distractions of Memory-Decision Work Load Based on Dynamics of Vestibulo-Ocular Reflex. Proceedings of International Symposium on EcoTopia Science, 7, 1132-1136.

[12]   Obinata, G., Tokuda, S. and Shibata, N. (2008) Mental Workloads Can Be Objectively Quantified in Real-Time Using VOR (Vestibulo-Ocular Reflex). IFAC Proceedings Vol-umes, 41, 15094-15099.

[13]   Kuczapski, A.M., Micea, M.V., Maniu, L.A. and Cretu, V.I. (2010) Efficient Generation of Near Optimal Initial Populations to Enhance Genetic Algorithms for Job- Shop Sched-uling. Information Technology and Control, 39, 32-37.

[14]   Koljonen, J. and Alander, J.T. (2006) Effects of Population Size and Relative Elitism on Optimization Speed and Reliability of Genetic Algorithms. Proceedings of the 9th Scandinavian Conference on Artificial Intelligence, Espoo, Finland, 54-60.

[15]   Son, L.A., Aoki, H., Hamada, H. and Suzuki, T. (2015) Parameters Optimization Using Genetic Algorithm Technique for Vestibulo-Ocular Reflex Model. 3rd International Symposium on Future Active Safety Technology toward Zero Traffic Accidents, Gothenburg, Sweden, 9-11 September 2015, 167-174.

[16]   Zupan, L.H. and Merfeld, D.M. (2003) Neural Processing of Gravito-Inertial Cues in Humans. IV. Influence of Visual Rotational Cues during Roll Optokinetic Stimu- li. Journal of Neurophysiology, 89, 390-400.

[17]   Green, A.M. and Angelaki, D.E. (2010) Internal Models and Neural Computation in the Vestibular System. Experimental Brain Research, 200, 197-222.

[18]   Angelaki, D.E., Merfeld, D.M. and Hess, B.J.M. (2000) Low-Frequency Otolith and Semi-circular Canal Interactions after Canal Inactivation. Experimental Brain Research, 132, 539-549.

[19]   Angelaki, D.E., Wei, M. and Merfeld, D.M. (2001) Vestibular Discrimination of Gravity and Translational Acceleration. Annals of the New York Academy of Sci- ences, 942, 114-127.