Abstract
This paper proposes an unobtrusive way to detect fatigue for drivers through grip forces on steering wheel. Simulated driving experiments are conducted in a refitted passenger car, during which grip forces of both hands are collected. Wavelet transformation is introduced to extract fatigue-related features from wavelet coefficients. We compare the performance of k-nearest neighbours, linear discriminant analysis, and support vector machine (SVM) on the task of discriminating drowsy and awake states. SVM with radial basis function reaches the best accuracy, 75% on average. The results show that variation in grip forces on steering wheel can be used to effectively detect drivers’ fatigue.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Sousanis, J.: World vehicle population tops 1 billion units, Ward Auto World (August 15, 2011), http://wardsauto.com/ar/world_vehicle_population_110815
Lyznicki, J.M., Doege, T.C., Davis, R.M., Williams, M.A., et al.: Sleepiness, driving, and motor vehicle crashes. JAMA: Journal of the American Medical Association 279(23), 1908–1913 (1998)
Desai, A.V., Haque, M.A.: Vigilance monitoring for operator safety: A simulation study on highway driving. Journal of Safety Research 37(2), 139–147 (2006)
Du, R.-F., Liu, R.-J., Wu, T.-X., Lu, B.-L.: Online vigilance analysis combining video and electrooculography features. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds.) ICONIP 2012, Part V. LNCS, vol. 7667, pp. 447–454. Springer, Heidelberg (2012)
Grace, R., Byrne, V.E., Bierman, D.M., Legrand, J.-M., Gricourt, D., Davis, B., Staszewski, J.J., Carnahan, B.: A drowsy driver detection system for heavy vehicles. In: Proceedings of the 17th AIAA/IEEE/SAE Digital Avionics Systems Conference, DASC 1998, vol. 2, p. I36-1. IEEE (1998)
Renner, G., Mehring, S.: Lane departure and drowsiness – two major accident causes-one safety system. In: Mobility for Everyone. 4th World Congress on Intelligent Transport Systems, Berlin, October 21-24 (1997); paper No. 2264
Chieh, T.C., Mustafa, M.M., Hussain, A., Zahedi, E., Majlis, B.: Driver fatigue detection using steering grip force. In: Proceedings of the Student Conference on Research and Development, SCORED 2003, pp. 45–48. IEEE (2003)
Eskandarian, A., Mortazavi, A.: Evaluation of a smart algorithm for commercial vehicle driver drowsiness detection. In: IEEE Intelligent Vehicles Symposium, pp. 553–559 (2007)
Shi, L.-C., Lu, B.-L.: Eeg-based vigilance estimation using extreme learning machines. Neurocomputing 102, 135–143 (2013)
Smith, M.E., McEvoy, L.K., Gevins, A.: The impact of moderate sleep loss on neurophysiologic signals during working-memory task performance. Sleep 25(7), 784 (2002)
Makeig, S., Inlow, M.: Lapse in alertness: coherence of fluctuations in performance and eeg spectrum. Electroencephalography and Clinical Neurophysiology 86(1), 23–35 (1993)
Chang, C.-C., Lin, C.-J.: LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2, 27:1–27:27 (2011), http://www.csie.ntu.edu.tw/~cjlin/libsvm
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, F., Wang, XW., Lu, BL. (2013). Detection of Driving Fatigue Based on Grip Force on Steering Wheel with Wavelet Transformation and Support Vector Machine. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42051-1_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-42051-1_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-42050-4
Online ISBN: 978-3-642-42051-1
eBook Packages: Computer ScienceComputer Science (R0)