Optimizing Train Operation Scheme Based On Passengers’ Travelling Choice Behavior For High-speed Rails

The determination of the high-speed railway train operation scheme should be people-centered,paying attention to the benefits of transportation enterprises while taking into account the travel needs of passengers.The travel choice behavior of passengers can fully reflect the distribution of passenger demand.Passengers choose the most suitable travel route according to their own needs and train operation scheme;the railway department adjusts the train operation scheme according to the passenger flow distribution within a day to achieve the best operation cost and operation scheme.It is necessary to optimize a high-speed railway operation scheme that not only meets the travel needs of passengers and realizes the sustainable goals of the railway sector,but also can optimize a demand-oriented,economical,and environmentally friendly high-speed railway operation scheme.The article analyzes the travel choice behavior of passengers to better understand the needs of passengers to improve the quality of railway transportation services,and uses a bi-level programming model to optimize the problem.An advanced heuristic algorithm nested by Frank-Wolfe is used to complete the solution.Finally,numerical experiments on real-world train operation scheme test cases further verify the effectiveness of the model.The concrete work is as follows:(1)After reviewing related issues such as passengers’ travel choice behavior,train operation scheme,optimization algorithm,etc.,a questionnaire survey is adopted to analyze passenger travel choice behavior.The whole travel process of passengers is divided into pre-convergence stage and travel stage to analyze the composition of generalized travel expenses.(2)Study on optimization of high-speed train operation scheme considering passenger travel satisfaction.Firstly,passenger travel satisfaction function is constructed by quantifying travel time convenience and passenger comfort.On this basis,a mixed integer bi-level programming model is established.From the enterprise perspective,the upper layer determines the train operation scheme with the goal of minimizing the train operation cost.The lower layer takes the minimum passenger dissatisfaction as the goal to obtain the passenger flow distribution results.(3)Optimization of high-speed train operation scheme considering flexible pricing strategy.The ticket price factor is added to calculate the generalized travel cost according to the whole process of passenger travel,and the passenger flow distribution is guided by adjusting the ticket price in different periods to reduce the travel impedance.A bi-level programming model is established.The upper level is a mixed integer programming model with the goal of maximizing the benefit of the railway sector,and the ticket price and operation scheme of each period are determined.The lower layer is a model based on the idea of uses equilibrium,which means that all passengers’ generalized travel costs are minimized.The bi-level programming realizes the feedback of passenger flow and time ticket price to guide passengers to travel.(4)The upper and lower decision variables in the two models interact with each other,and the heuristic algorithm of the nested Frank-Wolfe method is designed.According to the characteristics of the two models,the chromosomes in the genetic algorithm are designed,and the users equilibrium distribution method is used to assign the passenger demand to each train.