Research On Ticket Price Optimization Of Shijiazhuang Metro Stored Value Ticket Based On Consumer Travel Characteristics

With the continuous acceleration of urbanization in China,urban rail transit is becoming one of the important travel modes to alleviate urban congestion and promote urban development with its advantages of safety,speed,green and large traffic volume.For this reason,in recent years,many urban rail transit construction in China has entered the fast lane,and the mileage of operating lines has increased year by year.However,for operation managers,many problems are gradually exposed with the increase of the density of rail transit network and passenger flow.At present,the problem of unbalanced passenger flow during the whole day operation period is widespread.There is more passenger flow during the morning and evening peak hours,resulting in crowding and potential safety hazards;During the off peak period,there is less passenger flow and the full load rate of trains is low,resulting in waste of public resources.Therefore,it is of great significance to guide and grasp the travel of subway consumers through scientific adjustment of ride prices,and it is also an effective means to promote the improvement of subway service level and maximize the use of resources.This thesis takes Shijiazhuang subway consumers as the research object.First,based on the card swiping data in the process of passenger travel,mining the macro characteristics emerging from consumer travel,mainly research and analyze the whole day travel time,and divide the peak hours and peak hours of working days and rest days in a weekly cycle.Secondly,based on the macro travel characteristics of consumers,take consumers as individuals to select their travel characteristic values in six aspects of weekly travel times,peak travel times,average peak travel times,weekly consumption amount,peak consumption amount and average peak consumption amount as clustering indicators,and use K-Means clustering algorithm for clustering analysis.Finally,Shijiazhuang Metro consumers are divided into four categories,And describe the travel characteristics and preferences of each type of population,and use the data to calculate later.Thirdly,propose ticket management optimization suggestions for the unbalanced distribution of passenger flow at high and flat peak and the low passenger flow at flat peak.On the one hand,implement time-sharing pricing,that is,the proportion of ticket price increase at peak hours is,and the proportion of ticket price decrease at flat peak hours is.Based on the passenger flow transfer rate model and the total enterprise ticket revenue model,calculate the passenger flow transfer rate and the total enterprise ticket revenue under different conditions,The final choice is the optimal and reasonable scheme that does not reduce the enterprise income but also takes into account the public nature of the subway;On the other hand,the preferential time card is issued during the peak hours to increase the passenger flow during the peak hours of the subway,increase the enterprise income and maximize the utilization of public resources.Finally,through the simulation and prediction results,the suggestions for ticket card pricing of Shijiazhuang Metro are obtained: it is suggested that the ticket price of Shijiazhuang Metro be increased by 30% during peak hours and reduced by 20% during normal peak hours.This scheme can make the transfer rate of passenger flow reach 8.95%,the average hourly passenger flow ratio of high and low peak decreases by 17.3%,and the imbalance coefficient of hourly passenger flow decreases by 8.4%.At the same time,Based on the theoretical analysis of elastic demand,the reduction of ticket prices during the off-peak period will increase the number of subway consumers.It is estimated that the average daily passenger flow will increase by 47138 person-times,the daily income of enterprises will increase by 29700 yuan,and the monthly income will increase by890700 yuan.