Analysis And Data Mining Of Intersection Traffic Data

Based on limited urban roads,convenient and efficient travel has become a concern for people.The greater impact on traffic is the traffic junction,which is the hub of the whole city road,its ability to control the city's access to the road,daily traffic congestion and traffic accidents with most of its related.With the development of science and technology,all countries in the world are developing intelligent transportation system(Intelligent Transportation System,ITS),As one of the important ways to solve the intelligent traffic system of city road contradiction can not only the real-time change of the traffic to make rapid response mechanism,but also makes the prediction of reasonable and effective for the future road traffic flow situation.At the same time,it plays a positive role in solving the problem of traffic congestion and reducing the negative impact caused by traffic congestion.This paper first selects the road two adjacent intersection as the research object,a collection of three road traffic in Beijing city in the adjacent(River West Road,North West Lake shade intersection,Wangjing West Road,South Park mouth)the historical traffic data,and the historical data analysis and sorting;Secondly,by means of multiple linear regression and grey multivariate linear regression analysis model for short-term prediction of traffic flow between the two junctions,based on the model analysis of the experimental results can be drawn:the prediction model can accurately predict the future direction of the single intersection 5 to 15 minutes of traffic flow,but also shows the use of model prediction can provide a favorable reference information for induced traffic system as traffic flow control.Finally,all day long flow visual controls designed four direction flow visualization and control of single intersection every single intersection,convenient for the user to view the work day in the same interface,the flow distribution of holidays and different time,more intuitive and profound understanding,understanding,mining,analysis of road traffic data.