Abstract:

The weight vector of the evaluation indexes was determined by the fuzzy hierarchy analysis, the membership functions of the evaluation indexes to the evaluation class were established using the ridge function, and a BP neural network model for evaluation of the vehicle safety status was built using the neural network tool box in Matlab software. The experiments were performed using the preset fault test method, the operation parameters of the vehicle under the road test process were acquired by the vehicle monitoring and early-warning system. The training samples for the neural network were obtained by the fuzzy comprehensive evaluation, and the trained BP neural network was used to evaluate the vehicle safety status in the road test. The road test results showed that the neural network evaluation is more sensitive and more accurate than the fuzzy comprehensive evaluation, providing a new method for identification of the vehicle risk status.

Key words: engineering of communications and transportation, vehicle safety status, fuzzy comprehensive, BP neural network