Research On Parking Demand Forecasting Of City Based On Car Ownership

With the improvement of GDP of urban residents in China and the improvement of the quality of life,the number of cars increases rapidly,and the motorized features of the urban traffic structure are increasingly prominent,which has brought many uncontrollable problems to the city.Congestion pressure in the road traffic environment has increased dramatically,and the speed of constructing urban parking lots can't match the growth rate of cars,which make problems such as “parking difficulty” and “parking disorder” emerge.In order to make up for vacant berths,new parking lots blindly build,the problem of land resources and parking has become more strained.How to solve the problem of urban parking effectively,parking demand forecast is the primary task and basis of urban parking planning.Car ownership is a key indicator in the forecast of parking demand.Therefore,this paper takes urban parking demand forecast as the research object,and proposes a city parking demand forecasting model based on car ownership.The main contents include the following parts:(1)Introduction of parking demand theory.The influencing factors of the parking basic characteristic parameters and parking demand forecasting is analyzed,which paves the way for the statistics and analysis of the parking status survey data.The existing parking demand forecasting methods are analyzed and summarized,which provides a basis for the establishment of parking demand forecasting models.(2)Establish of parking demand forecasting model based on traffic structure optimization.The demand for urban parking is divided into two parts: basic parking demand and flexible parking demand.Firstly,the relationship between car ownership and urban transport structure is analyzed.Based on the analysis of the factors affecting the definition of traffic structure,traffic structure model,and traffic trip structure,a dual-objective constrained model is established that optimizes the traffic structure with “the highest transportation efficiency and the least environmental pollution”.The sharing rate of various modes of transportation for the planning year is obtained and then the car ownership in the planning year is got based on car carrying rate.Based on this,a basic parking demand forecasting model is established.Then,a flexible parking forecasting model is established based on the correction of the elastic parking demand coefficient,and the method for parameter selection of the model is given.Finally,the total amount of urban parking demand is obtained.(3)Establish of Parking demand forecasting model based on combined forecasting model.Firstly,basic theory and test ways of gray model and exponential smoothing model to forecast car ownership method are discussed,and advantages and disadvantages of two models are analyzed.Then the car ownership combination forecasting model based on the principle of variancecovariance is built.Finally,the urban parking demand in the planning year is obtained which combined with the elastic parking demand forecasting model.(4)Taking Jintan district of Changzhou as an example for model verification.Firstly,the basic conditions and parking status of Jintan's downtown area are investigated,including the urban traffic characteristics,the overall situation of parking facilities,and the parking characteristics.Then,the obtained data were respectively substituted into the urban parking demand forecasting model based on traffic structure optimization and combination forecasting.Lingo software was used to solve the dual-objective function to get the parking demand.Finally,comparing the two models with the traditional model,the results show that the two models proposed in this paper can predict the city parking demand reasonably,and the urban parking demand forecasting model based on traffic structure optimization is more scientific and more consistent with the green and sustainable development of the city.