Research On Short-Term Traffic Flow Prediction Based On Multi-Dimensional Influencing Factors

With the development of social economy and the acceleration of urbanization,traffic congestion has seriously affected the operation efficiency of cities.Intelligent transportation focusing on the wide application and service of traffic information is an important means to effectively alleviate traffic congestion.Intelligent transportation can effectively improve the operation efficiency of existing transportation facilities,and the realization of high-precision short-term traffic flow prediction is a key part of intelligent transportation construction,This study deeply excavates and analyzes the influencing factors of road congestion,and constructs a D-SVM dynamic interference prediction model based on the analysis of the action mechanism of relevant factors of the traffic system,which effectively improves the prediction accuracy of the model.The model considers the impact of time cycle changes on road traffic flow by enhancing the time characteristics,eliminates the differential characteristics of flow in peak and trough periods,and can effectively realize real-time prediction,In order to provide the possibility of congestion relief on Expressway,the research enriches the construction of intelligent transportation theory,which not only helps traffic managers formulate traffic strategies,provide decision support,establish congestion early warning mechanism,but also facilitates travelers to make travel planning in advance and improve travel experience.This paper makes a more comprehensive analysis on the influencing factors of the transportation system.Firstly,by searching the Chinese and English literature related to urban traffic congestion published in high-quality journals of FMS management science and high-quality scientific and technological journals in the field of railway transportation,this paper combs the influencing factors related to urban traffic congestion in recent ten years,and makes a modeling analysis on the influencing factors of journals,literature citations,influencing factors and journal grades,The influencing factors of traffic congestion with high certification degree are calculated as the input variables of DEMATEL-ISM factor analysis,and a five-layer hierarchical structure model is established.According to the hierarchical structure of the model,the causes of normal section congestion and occasional section congestion are analyzed,and the congestion law of complex traffic system is revealed.Combined with the analysis of the causes of road congestion,this paper constructs a D-SVM dynamic interference prediction model based on system analysis,and uses Fourier transform to convert the time-domain signal of traffic flow into frequency-domain signal,so as to calculate the periodic characteristics of traffic flow data.In addition,in order to reduce the interference of outliers with large dispersion to the model,the exponential smoothing method is used to stabilize the outliers.By integrating the road congestion interference and comprehensively considering the change law of road flow,the dynamic interference factors affecting the occasional congestion of the road section are emphatically treated,and the time characteristic differences caused by periodic changes are enhanced to eliminate the prediction differences in peak and trough periods.Finally,the short-term prediction of road flow is realized by improving support vector machine through differential evolution,By calculating the mean absolute error MAE and root mean square error RMSE,it is proved that the prediction accuracy of the model has been significantly improved on the whole.