Study on modelling obstacles-avoidance behaviour of virtual driver based on multilayer fuzzy neural network Online publication date: Sun, 02-Dec-2007
by Lou Yan, He Hanwu, Zheng Detao, Lu Yongming
International Journal of Industrial and Systems Engineering (IJISE), Vol. 3, No. 1, 2008
Abstract: In virtual traffic scene of driving simulator, a fuzzy neural network controller Vision Fuzzy Back Propagation (VFBP) for modelling human-like driving obstacle-avoidance behaviour was developed. The obstacle-avoidance behaviour of virtual driver is inspired by the vision information based on real driving behaviour characteristic. VFBP controller consists of six layers. Considering the influence of the vehicle speed on the fuzzy distance, behaviour confidence and award coefficient are used to optimise fuzzy rules. Assessing level is used to ensure behaviour security. Adventure coefficient is used to call VFBP controller. In addition, VFBP controller can avoid the local smallest problem of the potential method, which makes the virtual vehicle go more smoothly. VFBP controller can simulate individual driver's behaviour through VFBP online learning.
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