The Research Of Traffic State Identification And Traffic Congestion Dispersal On Group Urban

With the rising of urbanization rate and the rapid development of social economy,urban car ownership increases year by year.The increasingly prominent contradiction between supply and demand of city traffic leads to a series of urban traffic congestion.Thus traffic jams become one of the main social problems in great cities of the world.It not onlybrings inconvenience to daily work and life of people,but also restricts the economic growth,accelerate the deterioration of urban environment and harmcity sustainable development.This problem is particularly acute in the city with cluster forms due to its limitation of the innate natural conditions such as topography,the lack of contact channel between different city groups will have lower reliability than the city with "ring-layer" model.Meanwhile,the increase of car ownership brings greater impact of the traffic inthe city,which more likely leads to traffic incident and congestion.However,the existing theory lack systematically research in traffic congestion state recognition and guidance technology theory.So in this article,we will start from the formation mechanism of traffic in clustered city,and then organize theory and method system for traffic state identification and traffic congestion guidance with a rational and effective strategy,so that we can ease traffic congestion and improve the quality of city traffic.In this paper,we firstly definite clustered city and its formation mechanism,analyze its advantages about urban sustainable development,the traffic running smoothlyand the development of the regional economic equilibrium development.Secondly,we will study the urban road network characteristics from the aspects like road network,transportation and traffic flow.And we also take research on space-time evolution characteristics of traffic congestion from both general and special aspects.Based on the clustered city traffic characteristics,we will analyze the influence of different traffic flow parameters in traffic state identification,then we select the most representative traffic flow parameters as the evaluation index after the fittingand the calibration,so that we can build the index system of traffic state identification and determine classification standard.Combined with the adaptive artificial fish algorithm and BP neural network,we will propose the traffic state identification method which is adaptive to artificial fish-neural network,we build algorithm model and give the solving steps.Then,combined with road network featuresand grades inclustered city,we put forward different Traffic Congestion Dispersal methods on channel network among clusters,key trunk road network within cluster and the key network nodes.Finally,combined with background of city road networkin Chongqing(taking Yuzhong Group and Nanping Group as examples),we analyze the space and network characteristics of them and identify traffic status by using elastic and adaptive artificial fish neural network identification methods.Based on hierarchical strategy for induced traffic congestion control and coordination,we will try to ease traffic congestion,improve the traffic efficiency of clustered city,so that the reliability of the method put by this paper will be verified.