Research On Optimization Of Beijing-shanghai High-speed Railway Stopping Plan Based On Dynamic Passenger Flow Characteristic Analysis

With the development of economy and society,railway transportation is playing an increasingly important role.In particular,the characteristics of efficient and fast passenger transportation have always been favored,and a large-scale passenger flow has been formed.The passenger flow will change continuously over time,and will eventually lead to incompatibility between the transportation demand and the existing train operation plan.Therefore,it is necessary to adjust the train operation plan in a timely manner to make it most compatible with the actual passenger flow.To better meet people’s travel needs,one of the main tasks to achieve this is to optimize the stop plan.Firstly,the content and influencing factors of the stop plan are discussed,and the status of the stop is analyzed with the Beijing-Shanghai high-speed rail as the research object.Based on the actual passenger flow data,the panel data analysis method is used to display the characteristics of the passenger flow,and the dynamic passenger flow characteristics are discovered.Secondly,the passenger flow characteristics of the Beijing-Shanghai high-speed railway are summarized,and the spatial characteristics of passenger flow are analyzed using Sankey diagrams.The time series analysis is performed using passenger flow data of two years.An autoregressive moving average model is established and passed the test.Time characteristics of the cycle.Then,with the constraints of passenger flow,occupancy rate,train stop rate,and stop variables as constraints,a multi-objective stop plan optimization model with the least total number of stops,the minimum deviation from the stop target value,and a balanced stop distribution is established.Algorithm to solve.Finally,the optimization and adjustment model was used to verify the Beijing-Shanghai high-speed train stopping plan.The results show that the total number of stops has been reduced by 12 times,2.5% compared with the previous optimization.The number of stops at the first-level node stations has remained unchanged.The tertiary nodes are all lower than before optimization.The station service frequency of other stations except Xuzhou East Station has decreased.Xuzhou East Station increased 13 stops.The reason why Xuzhou East Station did not decrease but increased instead can be explained.As a result of more transfers due to the status of the transportation hub.According to the stop plan of the train to be adjusted in the downlink direction after the termination of the calculation,the minimum stoppage value is 9.89,the variance of the average stoppage of each train before optimization is 3.28,and the variance of the average stoppage of each train after optimization is 2.42.The average number of train stops has been optimized by 26.1% compared with the previous one,which verifies the feasibility and effectiveness of the optimization scheme.