Parking Demand Forecasting Model for Urban Complex Based on Shared Parking: A Case Study of Harbin City

The paper takes urban complex as research object, aiming at the problem that the current parking facilities allocation neglects the difference of parking demand features of various buildings, which worsens the contradiction between supply and demand of parking. Analysis shows that the peak parking hour of various buildings in the urban complex is complementary, and the supply and demand are seriously imbalanced based on the parking survey data in Harbin. The main influence factors of urban complex parking demand are analyzed, and the revision coefficient of parking generation rate model of urban complex under the influence of a single factor is constructed combining with the actual parking demand. Based on the idea of shared parking, a parking demand forecasting model of urban complex under the comprehensive action of multiple factors is established by using regression analysis method, and the Yuguang-Intel Industrial Park in Harbin is taken as an example to verify the validity of the model. The results show that the predicting value of parking demand by the model is closer to the actual parking demand, which can effectively avoid the imbalance between supply and demand, and improve the utilization efficiency of parking facilities.