Urban Freight Traffic Analysis and Forecasting Models Based on Improved Four-Stage Method
Logistics hubs are important nodes for goods circulation and transformation in a city.In order to clarify urban logistics characteristics and freight traffic scale,the paper improved and optimized the"four stage method"of transportation,and used it to construct a freight traffic analysis and prediction model for urban logistics hubs.Firstly,the current freight generation algorithm was proposed based on different types of goods and lorries,and the calculation method for the target year was given based on the planned ar-ea.Secondly,for the logistics"input"city,the ARIMA time series model was constructed to predict the characteristic values of the influencing factors of each goods type in the target year,and an freight attractive algorithm between each logistics hub and various districts within the city was proposed.Thirdly,multi-source data analysis and clustering method were used to analyze the spatial-temporal distribution of lorries and the characteristics of goods travel chain,and to classify the types of lorries for urban external and internal transportation of logistics hubs.Fourthly,an algorithm was proposed to convert the freight volume of different types of goods into different types of lorry traffic volumes,as well as a method to solve the generation and attraction rate of traffic per unit area.Finally,taking Bei-jing logistics hubs as the empirical research object,it was obtained that the freight volume would in-crease from the current 33.44 million tons per year to 90 million tons per year in 2035,and the traffic volume would increase from the current 44,000 vehicles per day to 115,000 vehicles per day.The re-sults show that it is an effective way to analyze and forecast urban freight traffic by constructing an im-proved four-stage model based on goods,lorries and the characteristics of travel chains and consider-ing the conversion of freight volume to traffic volume.
万方数据
维普
