Traffic Status Prediction And Traffic Capacity Evaluation Of The Signal Intersection

Currently,how to relieve the traffic congestion is a problem for all of us.As the key of urban traffic system,analysis on traffic status and traffic capacity of the signal intersection is important to solve the problem.However,the traffic status is with the characteristics of non-linear,multi-variables,random and so on because of various factors,so it is difficult to establish an accurate mathematical model.In this paper,Linguistic dynamic system is put forward to solve the problem by using natural language effectively and dynamically descript the complex system evolution.This paper try to apply it on the evaluation of the traffic status and capacity analysis and provide new ideas for mitigating traffic congestion.Firstly,this paper introduces the research of the traffic status,capacity and the theory of linguistic dynamic system,and introduces computing with words,interval type-2 fuzzy sets(IT2FS)in detail.Secondly,classify an intersection's traffic status of Beijing by use data processing technology,k-means method on the base of traffic status key factors;then interval type-2 fuzzy sets is used to predict the traffic status;the traffic capacity is modeled and evaluated by interval type-2 fuzzy sets and fuzzy comprehensive evaluation.Thirdly,this paper provides a closed loop control model and evaluation result of four parameters is got by this model and specific improvement measures are put forward aiming at the problems that may exist at the intersection.Finally,design a framework of the intersection evaluation system based on IT2 FS and LDS to realize traffic state identification and traffic capacity evaluation of signal intersection,then analyze the key technologies.In this paper,data preprocessing,K-means clustering algorithm and are used to process,classify and predict the traffic status;interval type-2 fuzzy sets and fuzzy comprehensive evaluation are used to model and analyze the traffic capacity of signal intersection.This paper makes full use of language information to provide a new method to relieve the traffic status prediction and capacity evaluation.