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The driving safety influence formation was effected distinctly by the highway ramp length. The ramp length and automobile velocity were adopted to build driving safety influence formatting model in the highway ramp environment. The fuzzy logic reasoning rules were applied to construct the computing layers of driving safety cognizing formatting neural network. The driving safety influence experimental samples in the different ramp length were gained under different experimental automobile velocity. Weights of fuzzy-neural network layers were trained and was to analog compute effects on the driving safety influences under different ramp length with different experimental velocity. The resulting analyzing to prove that the relations between the typical ramp length and driving safety influence were calculated accurately. The trained neural network structure of driving safety influence based on the utilizing fuzzy inferences is helpful to improve driving safety influences of the highway ramp under different automobile velocity.

Rampway length, driving safety influence, velocity, fuzzy rules, neural network