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Vol: 53(67) No: 1 / March 2008 Adaptive Fuzzy System for Car Overtaking Assistance on National Roads Florica Naghiu Department of Computers, “Politehnica” University of Timisoara, Faculty of Automation and Computers, 2 V. Parvan, 300223 Timisoara, Romania, e-mail: floricel_naghiu@yahoo.com Simona Petcu Department of Computers, “Politehnica” University of Timisoara, Faculty of Automation and Computers, 2 V. Parvan, 300223 Timisoara, Romania, e-mail: petcu.simona@gmail.com Dan Pescaru Department of Computers, “Politehnica” University of Timisoara, Faculty of Automation and Computers, 2 V. Parvan, 300223 Timisoara, Romania, phone: (+4) 0256-403259, e-mail: dan@cs.upt.ro Keywords: vehicle applications, electronic driving assistance, expert systems, fuzzy logic controllers, overtaking Abstract Driver Assistance Systems are designed to provide active support to a vehicle driver by identifying potentially dangerous situations in advance and helping to avoid them. Overtaking maneuvers generates many hazardous driving situations as proved by several statistical reports. Considering that, this paper proposes a solution for overtaking assistance on national roads. It is based on adaptive fuzzy logic controllers and uses an intuitive interface to help the driver to take the right decision while overtaking. It could also be part of an autonomous vehicle. References [1] Assistance Systems. Empirical Studies of an Online Tutor and a Personalized Warning Display on the Effects of Learnability and the Acquisition of Skill\", TR-0071-06, TU Chemnitz, Germany, 2006. [2] Shaout A. And Jarrahz M. A., \"Cruise Control Technology Review\", Journal of Computers and Electrical Engineering, Elsevier, Vol. 23. No. 4, 1997, pp. 259-271. [3] Audi AG, “Adaptive Cruise Control”, http://www.audi.com/ audi/com/en2/tools/glossary/operation_comfort/adaptive_cruise_control.html, 2007. [4] Macek K., Williams B., Kolski S. and Siegwart R., “A lane detection vision module for driver assistance”, in Proceeding of the IEEE/APS Conference on Mechatronics and Robotics, Aachen, Germany, 2004. [5] Fraichard T. and Garnier P., \"Fuzzy control to drive car-like vehicles\", Journal of Robotics and Autonomous Systems, Elsevier, vol. 34, 2001, pp. 1–22. [6] Clarke D., Ward P.J. and Jones J., “Overtaking Road-Accidents: differences in maneuver as a function of driver age. Accident Anal. & Prev. Journal, Elsevier, vol. 30, 1998, pp. 455-467. [7] Hills B.L., \"Vision, visibility, and perception in driving\", Perception, vol. 9, 1980, pp. 183-216. [8] Tanga T.Q., Huangb H., Wongc S. and Xu X., “A new overtaking model and numerical tests”, Statistical Mechanics and its Applications, Elsevier, vol. 376, March 2007, pp. 649-657. [9] Delft University of Technology, “Overtaking Assistant Could Help Prevent Many Traffic-related Deaths”, ScienceDaily, http://www.sciencedaily.com/releases/2008/02/080226092749.htm, February 2008. [10] Siemens AG, “Wireless Module XT75”, https://pia.khe.siemens.com/ index_wireless_module_xt75-14462.htm, 2008. [11] Gray R. and Regan D., “Perceptual processes used by drivers during overtaking in a driving simulator”, Human Factors Journal, June 2005. [12] Maeda M., Shimakawa M. and Murakami S., “Predictive fuzzy control of an autonomous mobile robot with forecast learning function”, Journal of Fuzzy Sets and Systems, vol.72, no.1, May 1995, pp.51-60. [13] Maeda M., “Fuzzy Drive Expert System for an Automobile”, Journal of Information Sciences Applications, vol. 4, July 1995, pp. 29 – 48. [14] Fletcher L., Petersson L. and Zelinsky Al., ”Driver Assistance Systems based on Vision In and Out of Vehicles” in Proceedings of the IEEE Intelligent Vehicles Symposium, vol. 9-11 June 2003, pp. 322 – 327. [15] Hegeman, G., Brookhuis, K.A., Hoogendoorn, S.P.\"Opportunities of advanced driver assistance systems towards overtaking\",European Journal of Transport and Infrastructure Research, 2005,vol 5, pp. 281-296. |