Research On Bottleneck Identification,optimization And Simulation Of Urban Rail Transit Station

Rail transit is an effective means to alleviate urban traffic congestion,but the increasing passenger flow makes it bear more and more pressure.Among them,the transfer station is an important node of the rail network,which is the daily gathering and transferring place for urban residents.Within the transfer station,the passenger flow lines are interwoven densely,and the transfer lines are complex.Especially in the morning and evening rush hour,the efficiency of passenger transfer is low,the service level of the station decreases,and congestion easily occurs,which results in bottlenecks,leading to reduced carrying capacity of the station.At the same time,it increases the internal security risk.In order to solve the congestion problem and improve the carrying capacity of the station,this paper studies the identification and optimization method of the station bottleneck,improves the passenger travel efficiency,and ensures the rational,orderly and safe operation of the station.Through the analysis of the factors inside and outside the station,this paper puts forward the definition of the basic carrying capacity of the station and the carrying capacity of the station system,and analyses the five factors affecting the facilities and equipment inside the station,passenger flow organization,train operation,land use and transportation connection.After that,through Origin software,the passenger flow density,passenger flow speed will be collected at the facilities and equipment inside the station.The passenger flow data is fitted and calculated,and the influence relationship of each facility and equipment on the station’s carrying capacity is obtained,which paves the way for further finding the bottleneck.The definition of station bottleneck based on restriction theory is proposed,and the average queue length and waiting time are selected as the criteria to identify the station bottleneck.Based on the four cluster centers obtained by K-means clustering algorithm,the recognition index is divided into five levels.Then,based on queuing theory,a queuing model for each facility and equipment is established,and the membership functions of average queue length and average waiting time are determined.Finally,the location and level of the bottleneck of the rail transit station are identified by the improved membership function.Many bottleneck optimization methods such as enlarging facility area,passenger flow control and guiding passengers to change routes are proposed.A bottleneck optimization model aiming at average queuing time and average travel time of passengers is determined.On this basis,the restrictions of bottleneck optimization are determined as passenger flow inbound restriction,passenger flow outbound restriction,passenger flow inbound and outbound balance restriction.Node service capacity constraints and node maximum capacity constraints are solved using adaptive particle swarm optimization algorithm.Taking two intersections in Chongqing as an example,the passenger flow condition during the peak period of the station is simulated by using Massmotion software.The bottlenecks in the station are identified and optimized by means of thermogram of average passenger density and stack chart of passenger density.By comparing with queue theory model,the same result of identifying bottleneck is obtained,which verifies the validity of the model.Then,the optimization result is compared with the result of particle swarm algorithm.The best optimization scheme is scheme 3,which guides passengers to change routes based on passenger flow control.The time of scheme 3 is reduced by 23.2%compared with that of scheme 1,which has a comprehensive weight.The time is reduced by 10.3% compared with the second scheme combined weight.