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Research On Setting Method Of Buffer Time For Train Interval Operation Of Urban Rail Transit

Posted on:2021-03-30Degree:MasterType:Thesis
Country:ChinaCandidate:Z HuaFull Text:PDF
GTID:2392330614971697Subject:Transportation planning and management
Abstract/Summary:PDF Full Text Request
The interval operation buffer time of urban rail transit trains has the functions of improving the punctuality rate of train operation,improving the anti-interference of train operation diagram and reducing the energy consumption of train operation.On the basis of taking into account the characteristics of the deviation of the actual train operating time,this paper also considered the factors such as station spacing and line conditions of the urban rail transit system.Taking the minimum weighted sum of the deviation of the train interval operation time and the train energy consumption as the optimization goal,the optimal setting of the train interval operation buffer time between the stations of the urban rail transit line was studied.The main research results of the paper include:(1)Summarized the definition and classification of buffer time,and analyzed the advantages and disadvantages of the existing buffer time setting methods.From the aspects of late recovery of train operation and energy saving of operation,the function mechanism of urban rail transit train interval operation buffer time was analyzed,and the setting ideas and principles of urban rail transit train interval operation buffer time were discussed.(2)The characteristics of the time division of urban rail transit trains interval operation were studied.A log-normal distribution function is adopted,the function parameters of train operation time division deviation between different stations were obtained by sorting and fitting the actual operation time data of urban rail transit trains.Then generated a random disturbance plan for the running time of the train section.The optimization goal is to minimize the deviation degree between the actual interval running time of the train after being randomly disturbed and the planned running time.On the basis of a certain sum of the train running buffer time,an optimization model for the setting of train interval operation buffer time was established.An improved adaptive genetic algorithm was designed to solve the model.(3)From the aspects of train attributes and line conditions,the main influencing factors of train operation energy consumption were summarized and analyzed,and the influence of line longitudinal section and station spacing on train operation energy consumption was analyzed.Using the train operation calculation method,the train interval operation energy consumption and the running time under different line profiles and station spacing was analyzed and calculated.A comprehensive optimization model for setting the train interval operation buffer time was established considering the weighted minimum of train running time deviation and operation energy consumption.And a model solving algorithm based on an improved adaptive genetic algorithm is designed.(4)A practical urban rail transit line is taken as an example to study the calculation example.Firstly,with the minimum deviation degree of train running time as the optimization goal,the optimization plan for setting the train interval operation buffer time in each section of the line was calculated.Compared with the existing plan,the optimization plan reduced the deviation of train running time by 5.31%.Secondly,taking the minimum energy consumption of the trains as the optimization goal,the optimization plan for setting the running buffer time of each section was calculated.Compared with the existing plan,the energy consumption reduced by 1.98%.Finally,taking the weighted sum of the train running time deviation degree and the running energy consumption as the minimum optimization goal,the comprehensive optimization plan for setting the running buffer time between each station was calculated,and the optimization effect was 1.86%.
Keywords/Search Tags:Urban Rail Transit, Train interval operation buffer time, Operation deviation, Energy saving, Genetic algorithm
PDF Full Text Request
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