Research On Collaborative Inflow Control For Urban Rail Transit Networks In Peak Periods

With the acceleration of urban rail transit construction in China,more and more urban rail transit systems have entered the era of network operation.Under the conditions of network operation,the passenger flow of rail transit presents a geometric increase,which leads to the uneven distribution of passenger flow,the mismatch between the passenger flow demand and the supply of transportation,and the passengers' detention.These problems are particularly prominent during the morning and evening peak period.In order to alleviate the contradiction between supply and demand,ensure the safety of operation and improve the quality of passenger service,the operation management Department expects to adjust the supply and demand by means of operational organization,improve the spatial and temporal distribution of passenger flow,and optimize the matching between supply capacity of space-time configuration and travel demand.Therefore,this paper focuses on the contradiction between supply and demand in the peak period of urban rail transit,and studies the characteristics of network passenger flow,the similarity analysis of travel law,passenger flow prediction,passenger flow regulation and management,and provides theoretical support for the management of passenger flow in urban rail transit network operation.The research contents are as follows:(1)Network traffic characteristics research:using the metro automatic fare collection system(AFC)credit card data to analyze the overall distribution characteristics,from the aspects of network passenger volume,passenger flow distribution,transfer passenger flow,as well as the passenger travel characteristics such as arrival time distribution,travel time,departure distance.Based on historical travel data,passengers were clustered to analyze the travel habits and regularity of different types of passengers.(2)Travel regularity similarity analysis and station passenger flow forecast:in order to fully excavate the fluctuation rule of passenger flow with time granularity and find out the minimum time granularity and time segment of the strong regularity of passenger flow,16 different time granularity are selected to measure the similarity degree between the historical passenger flow and current passenger flow respectively,analyze the volatility and correlation of passenger flow in different scales more carefully and systematically,and provide the empirical basis for the use of the information of the prior passenger flow.Based on this,the GMDH(the Group Method of Data Handling)algorithm is used to predict the station passenger flow in short time,so as to provide basic input for subsequent passenger flow management.(3)Urban rail transit station passenger flow control model building and analysis:using three layers coupling network of physical structure layer,trip path layer and train running layer to depict the hierarchical structure of rail traffic network,through network topology expression,K short path search,passenger flow distribution,train timetable transformation and other means to realize the dynamic transmission simulation of passenger flow.The CPLEX dynamic limit scale module is used to establish the LP planning model for collaborative inflow control for urban rail transit networks.(4)Based on the model of the station coordinated flow,the dynamic analysis of the traffic congestion in the early peak period is carried out,and the overall passenger flow restriction scheme is formulated from two different angles of adjusting the passenger demand and adjusting the supply capacity of the station.The study of intake passenger flow regulation provides a calculation method for the setting of limited flow scheme,which provides theoretical support for the management practice of road network passenger flow,and helps to improve the service level of passengers and enrich the experience of passenger transport organization.