Research On The Construction Of Urban On-road Parking Platform System And Intelligent Equipments Selection

Along with the new trend of digitalization and wisdom development of urban parking,major cities across the country gradually carry out the construction of citylevel on-street parking platform,the continuous maturity of the front-end collection equipment of on-street parking information coupled with the continuous improvement of the big data analysis function of the city-level wisdom parking platform provides a new solution to alleviate the problem of on-street parking.At present,the parking data platform built in most cities mainly focuses on the implementation of parking space display and electronic payment function,which not only has the problem of single platform function and poor experience,but also commonly exists in a city with multiple platforms repeatedly built in various jurisdictions,and there is a data island phenomenon that data cannot be shared by multiple platforms.In the front-end equipment selection of on-street smart parking,the current decision-making method is mostly subjective,without full consideration of socio-economic needs,urban characteristics and dynamic and static traffic characteristics,without a comprehensive evaluation of the deployment of road mitigation and equipment performance,resulting in improper selection of the function of each module of the platform and the city’s onstreet smart parking equipment,which seriously affects the function of smart parking equipment,resulting in construction costs High,poor management effect and other outstanding problems.Based on this,this study conducts research on the construction of city-level on-street parking platform system functions and front-end collection equipment layout selection,and proposes corresponding planning and management strategies to alleviate the problem of difficult urban parking and wasted parking resources,as follows:(1)Analyze the current situation of urban on-street parking construction and management,and analyze the current situation of on-street parking system application with the characteristics of urban parking management platform.Focus on the current urban on-street parking management work in the high cost of management,low management efficiency parking information is not interoperable,data mining depth shallow,low level of intelligence,and other aspects of the focus of the analysis.(2)Combined with cloud computing and big data mining related features,according to combined with cloud computing and big data mining related features,according to the D&M information system model analysis of management-oriented intelligent system requirements,the establishment of cloud-based data center and management center general framework,based on this analysis of the application side,the proposed management-oriented intelligent application terminal module design scheme.Based on Spring MVC + Spring + Mybatis(SSM)framework,and combined with city-level mobile interconnection technology,taking into account the system’s large amount of stored data,high processing performance requirements,and cloud deployment characteristics,the My SQL database is applied,and a software technology structure framework for efficient and stable operation is proposed,and the system modules of the city-level on-street smart parking platform are exhaustively(2)We propose an overall solution for building a city-level intelligent parking management system through the implementation and association of each module.(3)On the basis of analyzing the operation principle and equipment characteristics of the front-end information collection equipment of urban on-street smart parking,the principles and methods of preferential selection of urban on-street parking equipment are proposed.Combining with the expert scoring method and considering the advantages and disadvantages of on-street smart parking equipment and the applicable scenarios,a typical index is selected to build an evaluation and selection index system for on-street smart parking equipment in the city.(4)On the basis of constructing the preferred index system for the evaluation of urban on-street smart parking equipment,we use the improved hierarchical analysis method and entropy value method to assign subjective and objective weights to the evaluation indexes,adopt cooperative game theory to determine the comprehensive weights of the indexes,and obtain the importance ranking of each first-and secondlevel index;then,we analyze the cloud meta-topologically representable method of the target layer and first-level evaluation indexes,establish the index system comment set and Then,the cloud model is expressed by the cloud model,and the cloud model of urban on-street smart parking equipment evaluation based on the cloud object elementTOPSIS is finally completed.Finally,the cloud-TOPSIS-based urban on-street smart parking equipment selection model is applied to the Chongqing Yuzhong District on-street parking wisdom transformation project as an example to verify the validity and applicability of the model.