Off-road Public Parking Pricing Based On Individual Choice Behavior

In recent years,the number of urban motor vehicles has increased sharply,while the land and road resources are relatively limited,which leads to the increasingly prominent contradiction between parking supply and demand.Because drivers cannot get accurate parking information,and parking pricing is out of line with the supply and demand of parking spaces,some parking spaces have more spare space,which is not conducive to the improvement of the operating income of the parking lot operators while wasting social resources.In this context,how to regulate the space-time balance between parking demand and supply through reasonable guidance information and pricing measures,to achieve a win-win situation of public interest and corporate income,has become a hot topic in academia and industry.In this study,we will systematically explore the solutions to the above problems from three aspects: the prediction of the number of available parking spaces in the parking lot,the analysis of drivers’ parking choice behavior and the joint pricing of regional parking.First,this study constructs the prediction model of available parking spaces.Based on the 6-day continuous vehicle entry and exit records of three cases,a dynamic prediction method of available parking spaces is established based on long-term memory network,differential integrated moving average autoregressive model and dynamic neural network,which realizes the dynamic prediction of available parking spaces for a single parking lot in steps of 5min,10 min,15min and 30 min.The research shows that the first mock exam is more accurate for the available parking spaces,but with the increase of time step,the prediction accuracy of single model is generally reduced.To further overcome the prediction error of a single method,a combined prediction method is studied to improve the prediction accuracy of the model in a long-time step.Secondly,this study constructs the driver’s parking choice behavior model and analyzes the influence degree of each factor.Based on the intention survey data,the utility function of driver’s parking choice is constructed,and the parameters are calibrated by discrete choice model.The results show that the parking rate,the number of available cars and the walking time all significantly affect the parking choice behavior of drivers.The parking choice behavior is the most sensitive to the change of parking rate,and the adjustment of parking rate can affect the parking choice behavior.Finally,this paper establishes a parking pricing model.The objective function of the model is to maximize the economic benefits of parking lot and to balance the utilization of parking space in the region.Under the condition that the vehicles will not have patrol parking due to the shortage of parking space and the government’s control on parking price,the sequential quadratic programming method is used to solve the model and determine the optimal rate of parking lot.At the same time,considering the multi management system of parking lot,on this basis,the model is verified by numerical examples.The results show that the parking pricing model can improve the economic benefits of parking lot,and the economic benefits of monopoly management system are higher.Parking pricing model can improve the unbalanced occupancy of parking spaces between different parking lots caused by the original pricing strategy.In addition,parking rate can reduce private car travel and adjust traffic demand.To sum up,the prediction of available parking spaces in the parking lot studied in this paper can enable the driver to obtain more accurate parking space information and reduce the phenomenon of vehicle cruise.In this paper,the driver’s parking behavior is modeled,and the factors that affect the driver’s parking behavior are analyzed.In addition,based on the driver’s parking choice behavior model,the parking pricing model is constructed to guide the travelers’ parking decision-making to a certain extent,relieve the parking pressure and solve the imbalance between the supply and demand of parking space resources.