Abstract
The paper describes a method and a device for a current permanent observation of driver’s response in the road traffic was described. The task of presented system is not only the "on-line" analysis of the human behavior but primarily the determination of the physiological changes and their fuzzy classification in order to determine the states considered sub-critical. The article is based on authors research and results of experiments, related to the international scientific state of art, in terms of excessive fatigue and aggression as essential biocybernetic factors increasing the road accident risk. A variant of the warning system for notification of driver’s psychophysical condition changes was presented. The system is based on a revised analysis of the human metabolism under a monotonous long-term load. The results of simulations and real measurements are prerequisites for the development of the presented system structure.
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
Haworth, N.L., Triggs, T.J., Grey, E.M.: Driver Fatigue: Concepts, measurement and crash countermeasures, Human Factors Group, Department of Psychology Monash University (June 1988)
AAA Foundation for Traffic Safety, Aggressive Driving: Research Update, Washington, D.C. (April 2009)
Benoit, A., Bonnaud, L., Caplier, A., Ngo, P., Lawson, L., Trevisan, D.G., Levacic, V., Mancas, C., Chanel, G.: Multimodal Focus Attention Detection in an. Augmented Driver Simulator. Journal on Multimodal User Interfaces 1(1), 49–58 (2007)
Healey, J.A., Picard, R.W.: Detecting Stress During Real-World Driving Tasks Using Physiological Sensors. IEEE Transactions on Intelligent Transportation Systems 6(2), 156–166 (2005)
Qing, W., Bing Xi, S., Bin, X., Junjie, Z.: A PERCLOS-Based Driver Fatigue Recognition Application for Smart Vehicle Space. In: 2010 Third International Symposium Information Processing (ISIP), pp. 437–441 (2010), doi:10.1109/ISIP.2010.116
Mitas, A., Bugdol, M., Ryguła, A.: Simultaneous analysis of driver’s physiological and behavioural parameters under the aspect of transport safety. Journal of Medical Informatics & Technologies 13, 241–247 (2009) ISSN-1642-6037
Shunji, K., Masayoshi, A.: Estimation of Rhythmic Movement of Driver’s Head from Nostrils Detection. Papers of Technical Meeting on Intelligent Transport Systems. IEE Japan ITS-02(31-34), 13–18 (2002)
Krajewski, J., Trutschel, U., Golz, M., Sommer, D., Edwards, D.: Estimating Fatigue from Predetermined Speech Samples Transmitted by Operator. In: 5th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design. Driving Assessment, pp. 468–474 (2009)
Boyraz, P., Hansen, J.H.L.: Active Accident Avoidance Case Study: Integrating Drowsiness Monitoring System with Lateral Control and Speed Regulation in Passenger Vehicles. In: 2008 IEEE International Conference on Vehicular Electronics and Safety, Ohio, USA, September 22-24 (2008)
Miyajima, C., Nishiwaki, Y., Ozawa, K., Wakita, T., Itou, K., Takeda, K., Itakura, F.: Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification. Proceedings of the IEEE 95(2), 427–437 (2007)
Ryguła, A.: Driving style as a behavioural biometric in the process of user identification and the current analysis of access to the vehicle. Biometry (2011); editor-in-chief: Mitas, A.W.
Kuge, N., Yamamura, T., Shimoyama, O., Liu, A.: A Driver Behavior Recognition Method Based on a Driver Model Framework. Structure 109(Idm), 469–476 (2000)
Malta, L., Miyajima, C., Takeda, K.: A Study of Driver Behavior Under Potential Threats in Vehicle Traffic. IEEE Transactions on Intelligent Transportation Systems 10(2), 201–210 (2009)
King, D.J., Mumford, D.K., Siegmund, G.P.: An algorithm for detecting heavy-truck driver fatigue from steering-based measures (98-S4-O-10). In: Proc. of 16th International Technical Conference on the Enhanced Safety of Vehicles, pp. 873–882. National Highway Traffic Safety Administration, Washington, DC (1998)
Friedrichs, F.: Drowsiness monitoring by steering and lane data based features under real driving conditions. Signal Processing, 209–213 (2010)
Ryguła, A.: Driving style identification method based on speed graph analysis. In: Proceedings of 4th International Conference on Image Analysis and Biometrics and International Conference on Kansei Engineering & Affective Systems, Cieszyn, June 25-28 (2009)
Cherrett, T., Pitfield, D.: Extracting Driving Characteristics from Heavy Goods Vehicle Tachograph Charts. Transportation Planning and Technology 24(4) (2001)
Islinger, T., Köhler, T., Wolff, C.: A Functional Driver Analyzing Concept. Advances in Human-Computer Interaction, Article ID 413964, 4 pages (2011), doi:10.1155/2011/413964
Rygula, A.: Early warning method in the aspect of tra_c safety. Doctoral Thesis. Faculty of Transport and Electrical Engineering, Technical University of Radom (2012)
Mitas, A.W., Ryguła, A., Pyciński, B., Bugdol, M.D., Konior, W.: Driver Biomedical Support System. In: Piętka, E., Kawa, J. (eds.) ITIB 2012. LNCS, vol. 7339, pp. 277–285. Springer, Heidelberg (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mitas, A.W., Ryguła, A., Pyciński, B. (2012). Driver’s Biocybernetic Monitoring and Early Warning System. In: Mikulski, J. (eds) Telematics in the Transport Environment. TST 2012. Communications in Computer and Information Science, vol 329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34050-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-34050-5_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34049-9
Online ISBN: 978-3-642-34050-5
eBook Packages: Computer ScienceComputer Science (R0)