Research On Optimization Of Dwell Point Policy In Plane Mobile Stereo Garage

As the growth of the urbanization,urban population and per capita income,the rise of car ownership in cities take place accordingly.Considering the limited urban land and the lag in the construction of parking infrastructure,parking has become an urgent problem.The land utilization rate is improved by the automated stereo garages.Besides,it has a high level of automation,which helps to solve the city parking difficulties.Plane mobile stereo garage is one of the nine main types of stereo garages,which is characterized by a large storage capacity and a high degree of automation.However,there is a problem that the access time is long.In a plane mobile stereo garage,dwell point policy is defined as the position that RGV(Rail Guide Vehicle)is in the state of idle and waiting.It affects the efficiency of the garage.Dwell point policies are conducted the optimized research towards reducing the car access time,improving the efficiency of garage operation and improving the customers' service satisfaction.By analyzing the related research of scholars at China and abroad,the thesis take the dwell point policy of the plane mobile stereo garage as the research object and the main contents are carried out in the following aspects:(1)Facilities and structure of the plane mobile stereo garage are given a briefly illustration.The average waiting time,average staying time,average service energy and average service time are used as the operating efficiency evaluation indexes of the stereo garage.Additionally,the storage and the retrieval process of the plane mobile stereo garage are introduced.Mathematical formulas of service time and service energy are set up.Consequently,a plane mobile stereo garage simulation software is implemented by PyQt5 graphical interface library,which realizes the output of evaluation indicators under any garage structure,customer arrival and dwell point policies;(2)The historical operating data from a market in Xi'an and a hospital in Beijing are imported into the simulation software.Three dwell point policies,i.e.,the storage priority policy,the retrieval priority policy and the in-situ standby policy are simulated and analyzed,respectively.(1)The three existing dwell point policies have different applicability for different garage in terms of the storage and retrieval arrival states;(2)There is a link between the space allocation strategy and the dwell point policy.On this basis,two kinds of ideas for optimizing the dwell point policy are inferred:(1)The dwell points are dynamically adjusted according to the predicted access and arrival state;(2)The dwell point policies and the space allocation strategy is optimized comprehensively.(3)To provide a theoretical basis for the optimizing solution of adjusting the dwell point dynamically according to the predicted access and arrival state,FCM(Fuzzy C-Means)and KNN(K-Nearst Neighbour)algorithm are used to cluster and predict.In order to improve the accuracy of predict results,the traditional KNN algorithm are altered from the following two aspects:(1)The autoregressive model is used to optimize the arrival trend;(2)The information gain is used to optimize the state vector similarity measure.The FCM algorithm can efficiently cluster the access and arrival state,the improved KNN algorithm has a prediction accuracy of 69.08%.It is proved that the FCM algorithm and improved KNN algorithm is effectively applied to the cluster and prediction of access and arrival state in the stereo garage.In addition,it provides the proof for the optimization of dwell point policy;(4)Two strategies for optimizing the dwell point policy are designed:(1)Based on the clustering and prediction of the access and arrival status,the proportion of vehicles stored and picked up,and the average arrival interval and average service time are counted.The RGV dwell point position is allocated according to the statistical index.Besides,a dynamically optimized dwell point policy is designed according to the predicted access and arrival state.(2)Based on the analysis of the relationship between the dwell point policy and the parking space allocation strategy,the improved annealing simulation algorithm is used to optimize the car storage procedure.The dwell point policy with the parking space allocation is designed.According historical operating data from the two garage,the two optimized as well as the three traditional dwell point policies are simulated and compared in the software to obtain the evaluation indicators.Results show that the average customer waiting time and vehicle service time are reduced by the two optimized dwell point policies designed in this thesis.The efficiency of the garage operation is improved.The proposed optimizing solution provides a reference for the research of the dwell point policy in plane mobile stereo garage.