Research On Time-sharing Pricing Strategy For Urban Rail Transit Facing Peak-hour Congestion

With the rapid development of urban rail transit,the passenger flow of rail transit increases year by year,leading to serious congestion in peak hours.This problem not only reduces the level of passenger service,but also causes security risks.In the face of the huge pressure of passenger flow in peak hour,the demand management measures based on time-sharing pricing are widely concerned.Previous domestic scholars have carried out relevant studies on time-sharing pricing strategy.However,there are few studies on passengers’ travel choice behavior and time division in time-sharing pricing strategy.However,in actual operation,the division of pricing period,passengers’ travel choice behavior(including travel time and travel mode)and fare change ratio directly affect the implementation effect of time-sharing pricing strategy.Therefore,it is of great significance to take the above factors into consideration and make the time-sharing pricing strategy to alleviate the peak-hour congestion of urban rail transit.This paper analyzes the coupling mechanism between the passengers’ travel choice behavior and the fare change ratio.Secondly,the time-sharing pricing period is determined,and the models of price reduction in off-peak hours,price increase in peak hours and combination pricing(price reduction in off-peak hours and price increase in peak hours)are established.Finally,taking the Line BT of Beijing subway as an empirical study to verify the effectiveness of the model.Specific research contents are as follows:(1)Analyze the basic theory.This paper expounds the fare system of urban rail transit in China and the principle of fare formulation,introduces the basic theory of operation period division,and summarizes the advantages and disadvantages of common timesharing pricing methods.Based on the above theory,the key factors to be considered in time-sharing pricing strategy are proposed from multiple dimensions.(2)The travel choice behavior of passengers is analyzed.Firstly,the attribute information of passengers was obtained through SP and RP questionnaire survey,and passenger types were classified by second-order clustering method.Secondly,for different types of passengers,multiple Logistics regression models are established to analyze the travel choice behaviors of various passengers.Finally,the elastic coefficients of passenger transfer are calculated to calibrate the parameters for the establishment of the reasonable time-sharing pricing model.(3)Division of operation period and determination of pricing period.The Affinity Propagation algorithm is used to divide the operation period,and the pricing period is further determined by the clustering effectiveness index.As an important parameter of the time-sharing pricing model,the result of time-sharing pricing is helpful to make the time-sharing pricing strategy that matches the real travel time of passengers.(4)Build the time-sharing pricing model.The model takes passenger travel choice behavior,pricing period and fare variation range into account.Taking narrowing the difference of passenger load intensity between peak hours and off-peak hours as the objective function,and comprehensively considering the operating enterprise’s income loss,the range of ticket price change proportion,and the range of full load ratio,the price reduction model in flat peak period,the price increase model in peak period and the combined pricing model were established.(5)Example analysis.At the line level and station level,three time-sharing pricing strategies were implemented.The best solution was determined by comparing the results of the model.Compared with the current situation,the time-sharing pricing strategy proposed in this paper can transfer 24% of the peak-hour passenger flow and reduce the peak-valley difference by 35%,thus verifying the feasibility and effectiveness of the timesharing pricing model.