Research On The Optimization Of Express Transportation Network Of High-speed Railway Under The Evolution Of Express Transportation Demand Space

With the continuous improvement of national living standards and the rapid upgrading of e-commerce economy,the demand of express delivery market is expanding rapidly,which stimulates the blowout growth of express delivery business.In 2020,the express business volume of China has reached 83.36 billion pieces,with a year-on-year growth of more than30%.In addition,under the influence of the rapid upgrading of income and living standards,consumers put forward higher requirements for the timeliness,convenience,safety and reliability of express transportation.China’s express market is facing an increasingly severe development situation.The rapid development of China’s high-speed railway transportation provides a powerful carrier for the delivery of express goods,as the main business of China Railway Express Company,the market demand of high-speed railway express is increasingly strong,with the business system gradually mature.In the existing operation,high-speed railway express carries out fast freight transportation by using the high-speed railway confirmation car and passenger car piggyback.However,limited by the transportation conditions,carrying capacity and operation time,its ability to meet the express transportation needs to be strengthened.Based on this,the new mode of high-speed railway express train is introduced with the advent of high-speed railway freight train in 2020,on basis of the spatial evolution law of express market transportation demand and the existing operation nodes of high-speed railway,this paper optimizes the high-speed railway express train transportation network and puts forward the planning scheme of China’s high-speed railway express train pilot area and network nodes.Firstly,based on the geographical distribution characteristics of express delivery demand,the spatial econometric model of 31 mainland provinces is established.The visualization map of standard deviation ellipse reveals the two-stage migration law of the center of gravity and the main trend direction of express business.The spatial Gini coefficient and coefficient points out that China’s express transportation network is a large hub and spoke network with 3-4 hub nodes.According to the global local spatial autocorrelation analysis,it points out that there is a spatial distribution difference of "hot spots in the East and cold spots in the west" in China’s express transportation demand.Then,the geographically weighted regression model based on the influencing factors of spatial correlation reveals that CPI is the key geographical economic parameter affecting the demand of express market in China.Next,according to express business volume’s data characteristics,the "grey index neural network" spatial combination prediction model is established by combing the BP neural network prediction,grey prediction and cubic exponential smoothing prediction.Through the feasibility of express transportation of high-speed railway and the types of goods suitable,the adaptability of high-speed railway express train to the spatial evolution of express transportation is analyzed.Based on the random utility theory,this paper constructs the space improvement sharing rate model of high-speed railway express train,calculating that the highspeed railway express train sharing rate of China is 38.61%.Finally,with a "macro regional-micro node" process established,this paper establishes the spatial econometric model based on the predicted value of high-speed railway express train of 31 provinces,it is pointed that the determines eight coastal provinces including Shandong,Jiangsu,Anhui,Shanghai,Zhejiang,Jiangxi,Fujian and Guangdong would be selected as the pilot areas of high-speed railway express train.Then,from the 223 existing operation stations of high-speed railway express,35 stations are selected as candidate nodes of high-speed railway express network,with the index system data in 2025 predicted.Later,the improved K-means clustering model based on geographical weighting is established for node planning.Ultimately,this paper completes the establishment of the optimization construction of highspeed railway express train’s "3+8+24" three-level node transportation network in eight coastal provinces,which is shown as the level of "Regional express distribution base-local express transfer node-ordinary express transportation station".