Train Operation Adjustment Under Typical Scene Based On Particle Swarm Optimization

With the advantages of safety,high efficiency,convenience and reliability,rail transit has become an important means of public transportation for residents.The actual operation of rail transit is highly disturbed by many factors,and these factors affect the efficiency and quality of service.The disturbance during the train operation is different,and the adjustment method will also be changed,effective adjustment measures are faster to recover the running order and reduce the impact of the disturbance.Therefore,the study of train operation adjustment under different scenes has a great significance for rail transit.In this paper,the typical scenes of delay adjustment are studied and the improved Particle Swarm Optimization(PSO)algorithm is used to solve the adjustment model.The detailed research contents are as follows:Firstly,the research on the adjustment of urban rail transit train fault in emergency situation is studied and the model of short-turning strategy is built.The delay time model is established according to the process of fault train processing,and the number of stranded passengers is got by analyzing the relationship of passengers that getting on and off trains and the time of handling fault.At the same time,the dwell time is established by associating with the clearing-off passengers at the switchback station.The efficiency of passenger evacuation and the total delay time of the switchback line are taken as the optimization objective,the improved PSO algorithm is used to solve the adjustment problem.The simulation results verify the effectiveness of the short-turning adjustment strategy in maintaining the transport capacity and alleviating the problem of passengers stranded.Secondly,the train operation adjustment in single line is studied,the model of up and down trains operation adjustment is built.Based on the running characteristics of trains in single-track lines,the train operation adjustment is transformed to solve the conflict optimization problems of up and down trains.Considering the effect of train operation level,when the train class is same during adjustment time,the total delay time of trains is taken as the optimization objective.And when the operation level is different,it is necessary to take the satisfaction of the adjustment results into account and establish the satisfaction optimization model.The improved PSO algorithm is used to solve the problem and resume normal operation of trains.Finally,according to the running process and delay adjustment model,the train operation adjustment module including the function of train running diagram,train dynamic simulation and operation adjustment is designed.The train dynamic simulation module simulates the running process of the train on the diagram and realizes the inquiry of the running information in the corresponding running time.The train adjustment module realizes the adjustment of the delay information in different situations.The delay data is analyzed after adjustment,and the module realizes the optimization adjustment under different delay information.