Research On Application Technology Of Urban Traffic Dynamic Judgement

The traffic congestion has become a increasingly prominent problem with the rapid development of social economy, vehicle ownership increasing continuously and rapid growth of urban road traffic demand. In this context, Ministry of Public Security clearly suggest traffic police to solve the urban traffic congestion by using ITS, while it’s just the basis for intelligent traffic management and control that urban road traffic conditions judgement. Nowadays, traffic information data acquisition system and traffic guidance information release system construction have begun to take shape in major cities of China,however, some problems still exist urgent need to improve traffic conditions identification in process.Based on the above background and the situation on relative subject at home and abroad, it’s starting from the concept to explain traffic conditions judgement process, to research the urban traffic dynamic judgement application technology that it’s aim at the accuracy of basic data and dynamic of judgement process, and it’s certain referential significance to which improve traffic conditions judgement accuracy and Intelligent Transportation practicality.This paper starts from urban road traffic congestion causes, metric standard and constitution of index system to choice indicators and parameters which reflect the traffic conditions; proposed a data recovery method based on the data in the time series and spatial location proportional relationship to improve the lack of only by using time series, ensured the reasonableness and accuracy of basic data; it has proposed a traffic flow dynamic prediction model based on control theory and space-time relationship,which utilizes difference of predicted and actual collection traffic flow data as deviation control to form dynamic feedback through traffic flow time-space relationship, in order to achieve traffic conditions judgement’s dynamic and improve the accuracy of traffic flow forecasting; It has determined the cluster centers of each traffic condition utilizing the historical traffic information data through fuzzy clustering analysis, according to the membership relationship of real-time traffic data and cluster centers to determine the real-time traffic conditions, and this paper propose a method which use traffic conditions cluster centers as the judgement threshold, to solve the limitations of traffic conditions identification default threshold. Finally, simulation software VISSIM and software MATLAB complete case analysis.