Abstract
The aim of the article is to present preliminary results obtained by analysis of the behavior patterns of various driver subjects, in the context of an intelligent assistive driving system. We determined the parameters which are involved in determining the car driver’s interaction intent, and extracted features of interest from various measured parameters of the driver, car, and the environment. We discuss how threshold values can be obtained for the extracted features that can be part of rules to decide on specific interaction intents. The results obtained in this paper will be incorporated in a knowledge base to define the rules of an rule-based expert system that will predict in real-time the driver’s interaction intent, in order to enhance the safe driving experience.
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Laffey, T.J., Cox, P.A., Schmidt, J.A., Kao, S.M., Jackson, Y.: Read: Real-Time Knowledge-Based Systems. AI Magazine (1988)
Avci, E., Avci, D.: An expert system based on fuzzy entropy for automatic threshold selection in image processing. Journal of Expert Systems with Applications, 3077–3085 (2009)
Lefèvre, S., Ibanez-Guzman, J., Laugier, C.: Context-based Estimation of Driver Intent at Road Intersections 2011. In: IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (2011)
Doshi, A., Morris, B., Trivedi, M.: On-Road Prediction of Driver’s Intent with Multimodal Sensory Cues. IEEE Pervasive Computing 10(3), 22–34 (2011)
Trivedi, M.M., et al.: Posture analysis with stereo and thermal infrared video: Algorithms and experimental evaluation. IEEE Trans. Vehicular Technology 53(6), 1698–1712 (2004)
McCall, M.T.J., Mallick, S.: Real-time driver affect analysis and tele-viewing system. In: Proceedings of the Intelligent Vehicles Symposium, pp. 372–377. IEEE (2003)
Inagaki, T.: Smart collaborations between humans and machines based on mutual understanding. Annual Reviews in Control 32, 253–261 (2008)
Lorentzen, T., Kobayashi, Y., Ito, Y.: Virtual Reality Simulation: Integrating Infrastructure Plans, Traffic Models, and Driving Behaviors. In: Proceedings of the 16th World Congress on Intelligent Transportation Systems and Services (2009)
Ingebretsen, M.: In the News. IEEE Intelligent Systems 25(4), 4–8 (2010)
Shotton, J., Fitzgibbon, A., Cook, M., Blake, A.: Real-time Human Pose Recognition in Parts from Single Depth Images (2011)
Loiacono, J., Togelius, et al.: The wcci 2008 simulated car racing competition. In: Proceedings of the IEEE Symposium on Computational Intelligence and Games (2008)
SR Research, Eyelink II, http://www.sr-research.com/EL_II_scam.html
Microsoft SDK for Kinect, http://kinectforwindows.org/
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© 2012 IFIP International Federation for Information Processing
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Toma, MI., Datcu, D. (2012). Determining Car Driver Interaction Intent through Analysis of Behavior Patterns. In: Camarinha-Matos, L.M., Shahamatnia, E., Nunes, G. (eds) Technological Innovation for Value Creation. DoCEIS 2012. IFIP Advances in Information and Communication Technology, vol 372. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28255-3_13
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DOI: https://doi.org/10.1007/978-3-642-28255-3_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28254-6
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