Identification On Critical Section And Analysis On Spatial-temporal Evolution Characteristics Of Passenger Flow Over Urban Rail Transit Networks

With the continuous expansion of urban rail transit network and increment of passenger volume,the proportion of urban rail transit in urban public transportation is becoming larger and larger,and thus the safety of urban rail transit network has been paid much attention by the public.The study on identifying the critical sections and spatial-temporal evolution of passenger flow in urban rail transit networks is of great significance to the safety and operational reliability of rail transit,which can prevent the network operation from failing or even collapse.However,most of the existing research only from the full load rate over sections,not from the global network efficiency point of view to identify the critical sections over the network,and there is little research on the subway passenger evolution rules from the perspective of spatial-temporal correlation.Based on this,the paper is divided into four parts to explore:1)Starting from the full load rate of the interval,the critical sections at each time period in the network are identified through high full load rate.In this study,a real-time calculation model of section full load rate is proposed in order to solve the connection problem between the passenger flows in the period of time and to calculate the full load rate sequence of the interval.2)From the point of view of network efficiency,the critical sections which have great influence on network efficiency after failure is identified.First of all,a network efficiency computing index based on traffic network topology is put forward.The reciprocal of the shortest path between any two stations as a measure of network efficiency is used to identify the static critical interval of urban rail transit network.Further,the paper also adds passenger flow in the network,and identifies the network dynamic critical interval of different periods from the random user equilibrium point of view.In order to reflect passengers' perception of path differences,a network efficiency measurement index based on OD satisfaction function is proposed,which can reflect passengers' choice behavior.3)Based on the theory of spatial-temporal autocorrelation,intervals full load ratio sequence as the attribute values,explore temporal and spatial distribution and evolution characteristics of network passenger flow,so as to study the generation and dissipation process of congestion around critical intervals,so as to provide references for operators to predict the arrival rules of large passenger traffic ahead of time.Because the traffic state is not isotropic,the paper proposes a spatial-temporal autocorrelation model based on the importance degree of adjacency interval,which can reflect the temporal and spatial variation of passenger flow more truly.4)Finally,this paper takes the actual urban rail transit network in China as an example,and uses the AFC data in one day to analyze the critical intervals identification and the evolution rule of passenger flow.