Highway Tunnel Traffic Accident Prediction Research Based On Intelligent Algorithm

Highway tunnels,as a kind of special structure in highway traffic,bring convenience to people,but it is also the frequent occurrence of traffic accidents even the serious accidents.Traffic accidents in tunnels are not only difficult to rescue,but also difficult to divert traffic.Under the influence of line-of-sight,secondary accidents can easily occur,resulting in greater losses.Based on the relevant literature,this article discusses the main influencing factors of highway tunnel accidents.Then it counts 496 traffic accidents in the Qinling tunnel group in the past three years in the Western Han Dynasty,and combines the tunnel design data with local meteorological data to analyze the probability distribution.The effects of various influencing factors on the accident probability and casualties were quantified and analyzed and summarized.Based on the principle introduction and advantages and disadvantages of the statistical regression model and some intelligent models,this paper discusses the superiority of the intelligent model in the prediction of highway tunnel accidents compared with the statistical regression model.Based on the existing research,statistical analysis of accident data and correlation analysis of data,the characteristic attribute variables of traffic accident morphological prediction,severity prediction,casualty prediction,and duration prediction are determined respectively.The article uses matlab software to use BP neural network model,Bayesian model,random forest model,support vector machine model to predict it,and finally through the analysis of the prediction results to determine the most suitable forecasting model.