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• W2400188215 abstract "Driver’s error contributes to over 75 percent of road crashes especially in overtaking maneuvers. Intelligent transport systems (ITS) are under active development worldwide as a means of reducing loss of life. Since overtaking maneuver is a complex maneuver and so many factors affect it, the automation of this maneuver has been considered to be one of the toughest challenges in the development of autonomous vehicles. Extremely nonlinear nature of Overtaking behavior asks for the development of intelligent algorithms to describe, model and control this phenomenon. Uncertainties and inaccuracies, intervention of judgments and human logic in controlling the vehicle, necessitates use of intelligent control methods based on soft computing techniques like neural network and fuzzy logic systems. Integration of human expert knowledge, and learning based on data, are powerful tools enabling fuzzy systems to deal with nonlinear nature of driving behaviors. Usually, classic control methods are not proper to control nonlinear time dependent behaviors. Driving behaviors are certainly among these behaviors [1, 2]." @default.
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• W2400188215 date "2012-03-01" @default.
• W2400188215 modified "2023-09-26" @default.
• W2400188215 title "Modeling and Intelligent Control System Design for Overtaking Maneuver in Autonomous Vehicles" @default.
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