Prediction Of Accidents And Safety Evaluation Of Road Sections On Ordinary Arterial Highways

With the continuous advancement of science and technology in our country and the steady advancement of policies,the highway transportation industry has ushered in new development opportunities.However,frequent traffic accidents hinder the happy life of the masses and threaten the lives and property safety of urban and rural residents.According to the annual data released by the National Bureau of Statistics,the number of traffic accidents has been increasing year by year,and the number of casualties has been on the rise.Therefore,it is particularly important to establish an effective road section safety evaluation system on the basis of fully analyzing the characteristics of common arterial road traffic accidents,and to improve road traffic safety,and to formulate targeted safety protection measures.At present,there are few researches on the safety of ordinary arterial highways,and the accuracy of accident prediction is limited.Based on this background,this article predicts the common arterial highways from two aspects: the number of accidents and the severity of accidents,and establishes a road section safety evaluation index system.First of all,this article analyzes the road traffic characteristics of ordinary arterial highways and accident-causing factors,classifies various causes of accidents,summarizes and judges the accident characteristics of existing ordinary arterial highways;secondly,constructs arterial highways based on accident-causing factors The prediction model of the number of possible accidents on the road section uses the improved multi-factor gray Markov combination model to predict,and the smooth coefficient method is used to optimize the mid-term prediction data;at the same time,according to the accident cause factors,the rough set neural network combination model is used to carry out the ordinary trunk line Forecast the severity of highway accidents;finally,combining the causal factors analyzed by the above two models,constructs a safety evaluation index system for common arterial highway sections,and uses the average multiplier scaling method to optimize the judgment matrix and the weight matrix to obtain The final road section safety evaluation result.This article takes a second-level highway section in Fujian Province as an example to analyze the case.The results of the case analysis show: First,when predicting the number of possible accidents,the improved combined model has an accuracy of 10.4% higher than that of the single model.The data is compared in the combined model.Improved smoothing processing can effectively improve the accuracy of data prediction and reduce the prediction error;secondly,when predicting the severity of common arterial highway accidents,the combined model has an accuracy of about 1.4% higher than that of a single model without rough set reduction,and the calculation speed is accelerated by about 0.02 s,the training time is shortened by 10%,and the prediction of the severity of the accident is more accurate;finally,the safety evaluation system of the road section is constructed,based on the results of the road section division,the safety evaluation is focused on the small area road section,and finally the safety of the road section is realized Grade evaluation.The evaluation results can effectively and objectively evaluate the safety of road sections and lay the foundation for the development of targeted safety measures.