Combination Evaluation Method Of Road Traffic Safety

Reducing road traffic accidents and improving traffic safety levels have become a major issue of concern to the whole society. In order to improve road traffic safety conditions, first of all, the level of road traffic safety should be made clear, that is to say to evaluate the road traffic safety. At present, there are many ways of traffic safety evaluation, but most of them using a single evaluation method; these evaluation methods exist by its own shortcomings and inadequacies.This paper first analyzes the factors affecting road safety and builds the index system of road traffic safety evaluation. We analyze several single traffic safety evaluation methods deeply and summarize its own advantages and shortcomings. Based on these, we establish several combination evaluation method of road traffic safety.1,Combination evaluation model for traffic safety based on AHP and Neural Networks. The evaluation model uses the network training to amend the evaluation results of AHP, effectively overcomes the AHP subjective high-impact defects, and thus gets more accurate evaluation results.2,Combination evaluation model for traffic safety based on gray correlation degree, fuzzy logic and AHP. The evaluation model uses the correlation coefficient instead of the gray fuzzy relationship matrix to determine the degree of membership of evaluation indexes, effectively overcomes the inadequacies and ambiguity function is difficult to determine in traffic safety evaluation process, which are more accurate evaluation results.3,Combination evaluation model for traffic safety based on fuzzy and Neural Networks. The evaluation model combines fuzzy technology and neural network technology together, which constructs out a combination evaluation model of fuzzy neural network that can be deal with fuzzy information automatically, processing fuzzy information combination of fuzzy neural network evaluation model, which are more scientific and rational evaluation results.