Study On The Urban Parking-demand Prediction And Prking Management

Currently, the city parking problem is one of the main problems plagued the development of urban transport, a reasonable forecast of city parking demand is crucial to solve urban parking problems. The usual parking demand forecasting methods are mostly considered the number of static data, such as urban land use, vehicle fleet, population, few consider the dynamics of motor vehicle travel, and ignoring the relationship between static and dynamic traffic. Parking demand arises from travel, so trips as a factor of parking demand forecasting is a very important section.This paper analyzes the characteristics of parking and parking problems currently exist in the city. Based on the foreign successful parking demand management policies, and analyzes parking demand management methods and parking demand forecasting method. The article discussed the advantages and disadvantages of the existing parking demand forecasting model. Based on the traffic distribution forecast model- "gravity model" and "a supply of parkingdemand forecasting model", to find the relationship between the two models in the value of establishing iterative model used to predict the parking demand. Take Xi’an as an example, analysis the survey of the economic situation in Xi’an, population, vehicle ownership, parking lots and other status quo. Using the Spss software to forecast Xi’an population based on historical data. Trough Matlab software programming, using the iterative model to predict the parking demand in Xi’an regional 2015. Compared with the land use model, the results show that the iterative model is more reliable. It is an effective parking demand prediction. Finally, base on the predictions of the parking demand, proposing the corresponding demand management policies to Xi’an parking problem.