Analysis And Control Of Passenger Flow State Of Urban Rail Transit Network During Peak Hours

Urban rail transit attracts a large number of passengers with its convenient,fast and on-time features,and has gradually become the backbone of urban public transportation.In the morning and evening commute peak periods,the passenger traffic increases sharply,and there are often situations where station passengers accumulate and the line capacity is tight,and the congestion will spread from one station to the neighboring area or even a larger area with trains in motion,bringing to the rail transit system operational safety hazards.This paper takes the passenger flow state of the urban rail transit network as the research object during peak hours,describes the propagation and diffusion process of passenger flow congestion in the network through the recurrence model,and grasps the evolution circumstances of the network passenger flow state,theoretically for the organization of passenger flow in the network level of operating companies providing decision supports,and getting the point to reducing operational safety risks during peak hours.This article mainly carried out the following research work:(1)This paper defines the peak-hour large passenger flow that occurs during normal commuting peaks.It is actually a crowded state of passenger flow rather than the value of passenger flow.Based on the analysis of the causes of peak passenger flow,it summarizes its characteristics under networked operating conditions,which are characterized by time-changing,diffusion and fixedness.(2)In this paper,the section passenger flow is introduced to construct an urban rail transit trip network,using the passenger flow degree and the optimized shortest distance to analyze the statistical characteristics of the network in peak hours.Through the analysis of the characteristics of the local network of Beijing in the morning peak,it is found that the passenger flow degree can more accurately identify the importance of the station than the node degree;the optimized shortest path is unique,and its standardized length is greater than the original shortest path length,whitch is consistent with travel characteristics during peak hours.(3)In this paper,based on the cellular automata framework and the fusion of SIS virus propagation model and network propagation dynamics theory,a recurrence model of passenger flow status in urban rail transit network is established.Using the preprocessed passenger flow data as a parameter at the initial time to enter the model,the passenger flow status of all stations in the network at any time can be estimated.In order to identify and analyze the hidden dangers caused by the peak passenger flow,three network passenger flow status evaluation indicators are proposed,in which the network capacity can reflect the passenger flow status of the line section.A simulation experiment was conducted on a local network in Beijing during a morning peak on a certain working day,which can reflect the true state of the network passenger flow at a typical time to a certain extent,and the validity of the model is verified based on this.(4)This paper proposes two methods for controlling urban rail transit peak-hour large passenger flow,and uses them to preprocess the input of the recurrence model.By comparing and analyzing the network passenger flow status indicators after using different methods,the results show that the effect of current limiting on the spread of peak-hour large passenger flow in the network is better than reducing the line departure interval.This paper contains 54 pictures,37 tables and 75 references.