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A Development of Driving Simulator using Fuzzy Rules and Neural Network  

Hong You-Sik (School of Computer, Information and Communication Engineering, Sangji University)
Kim Tae-Dal (Computer Science, Chungwoon University)
Kim Man-Bae (Road Traffic Safety Authority)
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Abstract
Considering the domestic traffic environment and the increase of traffic accidents, we have been asked to exactly analyze the main causes of accidents for the accident-experienced drivers to be rehabilitated. In this thesis we present the development process and results of a driving simulator using the IPDE method in the interest of safe driving and driving rehabilitation. Through this Driving simulation development the rehabilitated driver has the possibility of experiencing the real driving situation with the driving aptitude and examines the reasons of accidents. Through the examinations the driver has the chance to correct the deformities of driving by choosing the explanatory scenes, and through this process the driver is able to develop the capability to react in the real situation. However this driving simulation system is one of the best developed, depending on weather and road condition the braking distance may change. Therefore the fuzzy rule and neural network have been used in this thesis to solve previously mentioned problem. The simulation exactly calculated the road and weather conditions to adjust the breaking intensity.
Keywords
Driving Simulator; Fuzzy Rules; Neural Network;
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