Research On Hybrid Pricing Of Rail Transit In Belt Cities At Different Time Periods And Road Segments

Belt cities are influenced by geographical spatial morphology and historical industrial layout,with the characteristics of different functional locations being far apart and concentrated distribution of the same functional location.This causes the public transportation system in the city to be affected by passenger travel time,travel purpose,travel preference,and other factors,resulting in uneven distribution of passenger flow and mismatched public transportation capacity within time and space.By optimizing the ticket prices of urban rail transit in different time periods and sections,it is possible to adjust the travel time and modes of passengers with high price elasticity to a certain extent,thereby alleviating the problems of passenger travel concentration and energy waste within the city.At present,the dynamic pricing strategy of rail transit mainly studies "peak shaving and valley filling" from the time dimension,lacking consideration for the shared passenger flow and capacity matching between road public transportation and urban rail transit within the main passenger transportation channels of the city.Therefore,this article combines the characteristics of urban passenger transportation corridors in strip cities to establish a dual level programming dynamic pricing model based on a mixture of time periods and road sections,providing new ideas and methods for pricing strategies of urban rail transit in strip cities.The specific research is as follows:(1)Through an overview of the current situation of urban rail transit ticket pricing system,time-sharing pricing strategies,and passenger travel choices,this paper proposes a research method and technical route for time-sharing and segmented hybrid pricing of strip urban rail transit.(2)Systematically elaborated on the basic theoretical knowledge of urban rail transit ticket pricing,including: pricing principles,commonly used ticket systems,and main methods of time sharing pricing for urban rail transit;At the same time,the introduction of traffic balance allocation theory provides an important theoretical basis for quantifying the generalized travel costs of passengers.And a questionnaire survey method combining SP and RP was adopted to analyze and quantify passenger behaviors such as personal attributes,travel time periods,and route preferences.(3)Based on the above research,a two-level planning model was established for the travel characteristics of passengers in the passenger corridors along the strip urban rail transit line.In the upper level planning,the unit passenger time-sharing and segmented ticket price is taken as the variable,and the passenger flow and operating cost are combined to establish a linear programming function with the maximum daily profit of urban rail transit enterprises as the goal;The lower level planning is based on passengers’ understanding of existing road conditions and transportation attributes,taking into account the differences in passenger satisfaction index within the time and space range.A lower level planning model is established with the time-sharing and segmented passenger flow of subway and public transportation as variables and the minimum generalized cost of passenger travel as the goal.(4)In order to solve the bilevel programming model,the nested Frank-Wolfe genetic algorithm is designed by improving the genetic algorithm to solve the upper level linear programming and Frank-Wolfe algorithm to deal with the form of the lower level integral function linearly,combining the characteristics of the objective function and constraints.Taking the passenger transportation channel along Lanzhou Urban Rail Transit Line 1 as an example,the feasibility of the algorithm was verified.The optimal ticket price system and passenger flow redistribution results obtained from the solution proved the effectiveness of the research on time-sharing and segmented hybrid pricing of strip urban rail transit.