Research On Passenger Flow Data Analysis Of Urban Orbit And Optimization Of Trains Headway Time

Urban rail transit plays an important role in urban public transport.It is of great significance to analyze the passenger flow data of urban rail transit and study the optimization method of train departure interval in order to improve the operation capacity of urban rail transit,relieve traffic pressure and ensure the safe operation of trains.In this paper,the passenger flow data of urban rail transit are analyzed in detail.On this basis,the train departure interval is optimized.The main work is as follows:1.Statistical analysis of passenger flow data.In order to analyze the distribution characteristics of passenger flow,the distribution characteristics of daily passenger flow at various stations of Shanghai Metro Line 1 are analyzed in time and space;the Gauss mixture distribution model of daily passenger flow at Shanghai Railway Station is established,and the parameters of the model are solved by EM algorithm;furthermore,the time series of monthly passenger flow at Fujin Road Station is analyzed.The ARIMA product seasonal model of monthly inbound passenger flow time series is established based on correlation function graph and partial autocorrelation function graph.In order to study the changing trend of passenger flow,a twin support vector regression(WTDTS)short-term combined passenger flow prediction method based on wavelet threshold denoising is proposed.The WTDTS prediction method has the advantages of small prediction error and high efficiency.Prediction and short-term forecast of passenger flow show that the passenger flow of urban rail transit has obvious morning and evening peaks at present and in the future,which provides data support for the optimization of train departure interval.2.The optimization of train departure interval.Based on the statistical analysis of passenger flow data,the optimization model of train departure interval in early rush hours is established.Firstly,the passenger flow data of Shanghai Metro Line 1 are collected by AFC system,and the data are cleaned and fused.The change characteristics of passenger flow data in different time periods are analyzed by using the method of agglomerated Q-type hierarchical clustering,and the results are confirmed.Then,taking the maximum benefit of operators and passengers as objective function and ensuring safe operation as constraints,a multi-objective optimization model is established.Finally,the specific scheme of train departure interval is obtained by using the fuzzy objective programming algorithm.