Modeling And Optimization Of Automated Parking System Of Paternoster Type Parking Space Allocation

With China’s urban population has increased dramatically,the per capita land area has decreased sharply.In particular,the per capita possession of vehicles has increased significantly in recent years.The automated parking system(APS)can greatly save parking space and provide more parking spaces under the same occupied area.The APS of paternoster type has the characteristics of high parking density,flexible layout and economical operation.It is of great theoretical and practical value to study the optimization of APS of paternoster type operation.In this paper,it is a problem of long waiting time and high energy consumption for parking and picking up in an APS of paternoster type.We model the way this new APS works.According to the characteristics of models,some solution methods are selected to obtain the corresponding optimization models.The main contents are as follows:(1)Consider the case where there is only one APS of paternoster type in the entire garage.Modeling the operation of a single APS of paternoster type.Taking the garage running time and running energy consumption as the optimization goals,the parking space allocation is used as the decision variable,the relevant optimization model is established.The model is solved using an adaptive genetic algorithm(AGA)and a reasonable location allocation method was obtained.Finally,the method validation experiment.The solution analysis is carried out by multiple sets of examples,and compared with the traditional greedy method of location allocation,the effectiveness of the proposed method is verified.(2)Consider the case where the entire garage is composed of multiple APS of paternoster type.Analyze its operation process and principle,model the overall operation mode of multiple APS of paternoster type,and decide the garage and parking space selected by each vehicle.Based on the ABC classification,the garage is divided into three areas based on factors such as the location of the entrance and exit of each garage and vehicle historical data.Use the M/G/∞ queuing model to determine the number of parking spaces and the basis for each type of garage.The optimization model of location allocation is established and solved by fast non-dominated sorting genetic algorithm(NSGA-Ⅱ).Finally,experiments were carried out to obtain optimized partition parameters using different examples,verifying the effectiveness of the proposed partitioning method,and verifying the performance of the parking space allocation method.(3)Designed and implemented an APS of paternoster type operation optimization system.Based on SSH framework and Java Web and other related technologies,the overall architecture,functional modules,system view layer,system control layer and database of the system are designed through the analysis of the needs of garage managers in the actual research work.The system was developed based on IntelliJ IDEA 2019,which mainly realized the functions of accepting user reservation requests,generating planning period information,and optimizing allocation of parking spaces.Finally,the system was initially tested.