Public parking resource management method and system based on big data technology

Abstract

The invention discloses a public parking resource management method and system based on a big data technology, and relates to the field of public parking resource management. The method comprises the following steps: acquiring parking space resource information published by a resource end user providing parking spaces, basic information of a demand end user having parking demands and parking space demand information at a current t moment within a time threshold T, constructing a parking space resource information set of parking space resources and a parking space demand information matrix, and constructing a resource-demand matching model; matching the parking space demand information and the parking space resource information at the current t moment by using the model, generating a first recommendation strategy and a second recommendation strategy which are preferential to the cost and the distance of a demand end user according to a matching result, and obtaining selectable parking space resource information under the recommendation strategies, and selecting the selectable parking space resources by a demand end user, and dynamically updating the parking space resource information matrix and the parking space demand information set according to a selection result of the demand end user.

Description

Technical Field

[0001] The present invention relates to the field of public parking resource management, and in particular to a public parking resource management method and system based on big data technology. Background Art

[0002] In most cities in my country, the phenomenon of insufficient utilization of parking resources is common, and parking resources are seriously wasted. This is mainly reflected in the fact that parking demand is concentrated in work areas during the day and in residential areas at night. This imbalance in time and space distribution makes shared urban parking spaces feasible. The current problems of shared parking spaces in cities in practice are: 1) Unreserved vehicles occupy parking spaces after entering the city; 2) Reservation vehicles enter the city but are not parked in the reserved parking spaces. Therefore, how to integrate fragmented and limited parking space resources from the perspective of parking resource complementarity to solve the problem of time and space imbalance in urban parking demand is of great significance for the efficient use of urban dedicated parking spaces.

[0003] In the existing technology, many experts and scholars have conducted theoretical and applied research on shared parking spaces: Xu Xin (2018) designed a smart ground lock and proposed a community parking space sharing platform, providing a reservation management system for parking space managers, maintenance personnel and parking space owners, which can realize the release of vacant parking space information, parking space reservation and use; Lu Danping (2019) designed a WeChat applet for self-service parking based on a network cloud server, optimized the user management mode to reduce users' malicious reservation and occupation of parking spaces; Zhang Heng (2022) designed a shared parking space cloud platform based on NB-lot, and provided parking space lock management functions for private parking space owners through WeChat applet. Parking space owners can remotely control parking space locks through the applet and share parking spaces with friends and visitors. Chen Jun et al. (2023) used traffic data such as parking arrival and departure, parking and departure, and proposed a method for sharing spatiotemporal resources of parking spaces based on single land use measures and combined land use facilities.

[0004] In summary, although there are a large number of literatures and applications on the research of shared parking spaces in parking lots, there are still some deficiencies in the design of shared parking spaces in cities. This is mainly reflected in the following aspects: On the technical level, although the research on intelligent ground locks, shared parking space cloud platforms, and the sharing of spatiotemporal resources of parking spaces has achieved relatively remarkable results in public parking lots, it has failed to integrate the fragmented and limited parking space resources, making it difficult to adapt to the increasingly complex urban parking needs. To this end, we propose a public parking resource management method and system based on big data technology. Summary of the invention

[0005] The main purpose of the present invention is to provide a public parking resource management method and system based on big data technology, which can effectively solve the problems in the background technology.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] The public parking resource management method based on big data technology includes:

[0008] Get time threshold Current At this moment, the parking space resource information released by the resource end user who provides parking space is constructed A parking resource information collection of parking resources , organize the collection Get Parking space resource information matrix at each moment = ,in, For the current The number of parking spaces available at the time, and ∈ ;

[0009] The parking space resource information includes the parking space location, parking space type, idle time, and charging conditions; The expression of the parking space resource information set of parking space resources is: ={ , , , }, where for Moment Parking space location information of parking space resources; for Moment Parking space type information of parking space resources; for Moment Idle time information of parking space resources; for Moment The functional relationship between parking fee and time for each parking space resource.

[0010] Get Current At this moment, the basic information of demand-side users with parking needs and parking space demand information are constructed The parking space demand information set of demand-side users , organize the collection Get Parking space demand information matrix at each moment = ,in, For the current At the moment, the number of demand-side users with parking needs, and ∈ ;

[0011] The basic information includes the location of the vehicle and the type of vehicle; the parking space demand information includes the parking time; The expression of the parking space demand information set of the demand-side user is: ={ , , }, where for Moment The vehicle location information of the demand-side user; for Moment Vehicle type information of demand-side users; for Moment The parking duration information of each demand-side user.

[0012] Construct a resource-demand matching model and use it to Match the parking demand information at the moment with the parking resource information, and generate parking recommendation strategies for demand-side users based on the matching results, including a first recommendation strategy that prioritizes cost and a second recommendation strategy that prioritizes distance;

[0013] The resource-demand matching model is specifically:

[0014]

[0015]

[0016] In the formula, , is the weighting coefficient.

[0017] Obtain the selectable parking space resource information under the recommended strategy, let the demand-side user select the selectable parking space resources, and dynamically update the parking space resource information matrix according to the selection result of the demand-side user and parking space demand information collection .

[0018] Parking space resource information matrix and parking space demand information collection The dynamic update frequency is determined according to the following principles:

[0019] Principle 1: At the time threshold When any of the demand-side users makes a selection, the parking space resource information matrix and parking space demand information collection Make updates;

[0020] Principle 2: If the time threshold If there is no selection behavior by any demand-side user, the parking space resource information matrix is ​​processed with a fixed time frequency λ. and parking space demand information collection Update, where 0<λ≤ .

[0021] The method further comprises:

[0022] According to the obtained information of selectable parking space resources under the recommendation strategy, respectively calculating the distance value between the demand-side user and the selectable parking space resource and the parking fee generated when any selectable parking space resource is selected;

[0023] Arrange the obtained distance values ​​in order from small to large, which is the distance-first second recommendation strategy;

[0024] Arranging the acquired parking fees in order from low to high is the first recommended strategy of fee priority.

[0025] The public parking resource management system based on big data technology includes:

[0026] The user-side module is used for the parking space resource information published by the resource-side user who provides parking spaces and the basic information and parking space demand information of the demand-side user who has parking needs;

[0027] Parking space resource information acquisition module, used to obtain time threshold Current At this moment, the parking space resource information released by the resource end user who provides parking space is constructed A parking resource information collection of parking resources , organize the collection Get Parking space resource information matrix at each moment = ,in, For the current The number of parking spaces available at the time, and ∈ ;

[0028] The demand-side user information acquisition module is used to obtain the current At this moment, the basic information of the demand-side users with parking needs and the parking space demand information are used to build the first The parking space demand information set of demand-side users , organize the collection Get Parking space demand information matrix at each moment = ,in, For the current At the moment, the number of demand-side users with parking needs, and ∈ ;

[0029] The matching model building module is used to build a resource-demand matching model and use the model to Match the parking demand information at the moment with the parking resource information, and generate parking recommendation strategies for demand-side users based on the matching results, including a first recommendation strategy that prioritizes cost and a second recommendation strategy that prioritizes distance;

[0030] Information update module, used to dynamically update the parking space resource information matrix according to the selection results of the demand-side user and parking space demand information collection .

[0031] The system also includes a memory, a processor, and a computer program stored on the memory and executable on the processor.

[0032] The present invention has the following beneficial effects:

[0033] Compared with the existing technology, by obtaining the time threshold Current At this moment, the parking space resource information released by the resource end user who provides parking space is constructed A parking resource information collection of parking resources , organize the collection Get Parking space resource information matrix at each moment , get the current At this moment, the basic information of demand-side users with parking needs and parking space demand information are constructed The parking space demand information set of demand-side users , organize the collection Get Parking space demand information matrix at each moment , build a resource-demand matching model, and use the model to The parking space demand information at the moment is matched with the parking space resource information, and a parking space recommendation strategy for the demand-side user is generated according to the matching result, including a first recommendation strategy with cost priority and a second recommendation strategy with distance priority, and the selectable parking space resource information under the recommendation strategy is obtained. The demand-side user selects the selectable parking space resource, and the parking space resource information matrix is ​​dynamically updated according to the selection result of the demand-side user and parking space demand information collection , can integrate fragmented and limited parking space resources, optimize the allocation of idle parking space resources using matching models, and make full use of public parking resources, thereby improving the current situation of tight and uneven distribution of urban parking space resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] FIG1 is a flow chart of a method for managing public parking resources based on big data technology according to the present invention;

[0035] Figure 2 It is a structural block diagram of the public parking resource management system based on big data technology of the present invention. DETAILED DESCRIPTION

[0036] The present invention will be further described below in conjunction with specific implementation methods, wherein the accompanying drawings are only used for exemplary descriptions and represent only schematic diagrams rather than actual drawings, and should not be understood as limiting the present invention. In order to better illustrate the specific implementation methods of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product.

[0037] In this embodiment, a technical solution is provided. By designing a smart parking lock and a client application, after the resource-side user installs the smart parking lock, the user can publish parking resource information through the client background management interface and set the parking space status, which can be divided into shared status and busy status. In the shared status, the parking space can accept reservations from demand-side users.

[0038] After logging into the client, users on the demand side can search for shared parking spaces near their destination, browse their specifications, locations, available reservation periods, and make reservations on their own. They can also publish parking demand information through the client, and the platform will make unified parking resource allocations through a resource-demand matching model.

[0039] When the reservation is completed, the user on the demand side will receive information such as the dynamic unlocking password. After the parking space manager verifies the information and confirms the existence of the reservation order, the user can drive into the parking area at a specific time, enter the password to unlock the smart parking lock, and park the vehicle. After the use is completed, the user must pay the fee as required, leave the parking area, and complete the use. If the user on the demand side exceeds the time limit or uses the parking space in an irregular manner, he or she will be punished.

[0040] The specific implementation process includes the following steps:

[0041] Step 1: The resource end user publishes parking space resource information through the client backend management interface, and the backend obtains the time threshold Current At this moment, the parking space resource information released by the resource end user who provides parking space is constructed A parking resource information collection of parking resources , organize the collection Get Parking space resource information matrix at each moment = ,in, For the current The number of parking spaces available at the time, and ∈ ;

[0042] Among them, parking space resource information includes parking space location, parking space type, idle time, and charging situation; The expression of the parking space resource information set of parking space resources is: ={ , , , }, where for Moment Parking space location information of parking space resources; for Moment Parking space type information of parking space resources; for Moment Idle time information of parking space resources; for Moment The functional relationship between parking fee and time for each parking space resource.

[0043] Step 2: The user on the demand side publishes parking space demand information through the client backend management interface and obtains the current At this moment, the basic information of demand-side users with parking needs and parking space demand information are constructed The parking space demand information set of demand-side users , organize the collection Get Parking space demand information matrix at each moment = ,in, For the current At the moment, the number of demand-side users with parking needs, and ∈ ;

[0044] Basic information includes the location and type of vehicle; parking space demand information includes parking time; The expression of the parking space demand information set of the demand-side user is: ={ , , }, where for Moment The vehicle location information of the demand-side user; for Moment Vehicle type information of demand-side users; for Moment The parking duration information of each demand-side user.

[0045] Step 3: Build a resource-demand matching model and use the model to The parking demand information at the moment is matched with the parking resource information, and a parking recommendation strategy for demand-side users is generated based on the matching results, including a first recommendation strategy with cost priority and a second recommendation strategy with distance priority. The resource-demand matching model is specifically as follows:

[0046]

[0047]

[0048] In the formula, , is the weighting coefficient.

[0049] Step 4: Obtain the selectable parking space resource information under the recommended strategy, let the demand-side user select the selectable parking space resources, and dynamically update the parking space resource information matrix based on the selection results of the demand-side user and parking space demand information collection .

[0050] Parking space resource information matrix and parking space demand information collection The dynamic update frequency is determined according to the following principles:

[0051] Principle 1: At the time threshold When any demand-side user makes a selection, the parking space resource information matrix and parking space demand information collection Make updates;

[0052] Principle 2: If the time threshold If there is no selection behavior by any demand-side user, the parking space resource information matrix is ​​processed with a fixed time frequency λ. and parking space demand information collection Update, where 0<λ≤ .

[0053] Step 5: According to the information of selectable parking space resources under the recommended strategy, the distance value between the demand-side user and the selectable parking space resource and the parking fee generated when any selectable parking space resource is selected are calculated respectively;

[0054] Arranging the acquired distance values ​​in order from small to large is the second recommended strategy of distance priority; wherein the distance value can be acquired through the GPS positioning module.

[0055] Arranging the obtained parking fees from low to high is the first recommended strategy of fee priority.

[0056] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A public parking resource management method based on big data technology, characterized in that: include: Get time threshold Current At this moment, the parking space resource information released by the resource end user who provides parking space is constructed A parking resource information collection of parking resources , organize the collection Get Parking space resource information matrix at each moment = ,in, For the current The number of parking spaces available at the time, and ∈ ; Get Current At this moment, the basic information of demand-side users with parking needs and parking space demand information are constructed The parking space demand information set of demand-side users , organize the collection Get Parking space demand information matrix at each moment = ,in, For the current At the moment, the number of demand-side users with parking needs, and ∈ ; Construct a resource-demand matching model and use it to Match the parking demand information at the moment with the parking resource information, and generate parking recommendation strategies for demand-side users based on the matching results, including a first recommendation strategy that prioritizes cost and a second recommendation strategy that prioritizes distance; Obtain the selectable parking space resource information under the recommended strategy, let the demand-side user select the selectable parking space resources, and dynamically update the parking space resource information matrix according to the selection result of the demand-side user and parking space demand information collection .

2. The public parking resource management method based on big data technology according to claim 1 is characterized in that: The resource-demand matching model is specifically: In the formula, , is the weighting coefficient.

3. The public parking resource management method based on big data technology according to claim 1 is characterized in that: The parking space resource information includes the parking space location, parking space type, idle time, and charging conditions; The expression of the parking space resource information set of parking space resources is: ={ , , , }, where for Moment Parking space location information of parking space resources; for Moment Parking space type information of parking space resources; for Moment Idle time information of parking space resources; for Moment The functional relationship between parking fee and time for each parking space resource.

4. The public parking resource management method based on big data technology according to claim 1 is characterized in that: The basic information includes the location of the vehicle and the type of vehicle; the parking space demand information includes the parking time; No. The expression of the parking space demand information set of the demand-side user is: ={ , , }, where for Moment The vehicle location information of the demand-side user; for Moment Vehicle type information of demand-side users; for Moment The parking duration information of each demand-side user.

5. The public parking resource management method based on big data technology according to claim 1 is characterized in that: Parking space resource information matrix and parking space demand information collection The dynamic update frequency is determined according to the following principles: Principle 1: At the time threshold When any of the demand-side users makes a selection, the parking space resource information matrix and parking space demand information collection Make updates; Principle 2: If the time threshold If there is no selection behavior by any demand-side user, the parking space resource information matrix is ​​processed with a fixed time frequency λ. and parking space demand information collection Update, where 0<λ≤ .

6. The public parking resource management method based on big data technology according to claim 1 is characterized in that: The method further comprises: According to the obtained information of selectable parking space resources under the recommendation strategy, respectively calculating the distance value between the demand-side user and the selectable parking space resource and the parking fee generated when any selectable parking space resource is selected; Arrange the obtained distance values ​​in order from small to large, which is the distance-first second recommendation strategy; Arranging the acquired parking fees in order from low to high is the first recommended strategy of fee priority.

7. The public parking resource management system based on big data technology is characterized by: The system is used to implement the steps of the public parking resource management method based on big data technology according to any one of claims 1 to 6, including: The user-side module is used for the parking space resource information published by the resource-side user who provides parking spaces and the basic information and parking space demand information of the demand-side user who has parking needs; Parking space resource information acquisition module, used to obtain time threshold Current At this moment, the parking space resource information released by the resource end user who provides parking space is constructed A parking resource information collection of parking resources , organize the collection Get Parking space resource information matrix at each moment = ,in, For the current The number of parking spaces available at the time, and ∈ ; The demand-side user information acquisition module is used to obtain the current At this moment, the basic information of the demand-side users with parking needs and the parking space demand information are used to build the first The parking space demand information set of demand-side users , organize the collection Get Parking space demand information matrix at each moment = ,in, For the current At the moment, the number of demand-side users with parking needs, and ∈ ; The matching model building module is used to build a resource-demand matching model and use the model to Match the parking demand information at the moment with the parking resource information, and generate parking recommendation strategies for demand-side users based on the matching results, including a first recommendation strategy that prioritizes cost and a second recommendation strategy that prioritizes distance; Information update module, used to dynamically update the parking space resource information matrix according to the selection results of the demand-side user and parking space demand information collection .

8. The public parking resource management system based on big data technology according to claim 7 is characterized in that: The system also includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the steps of the public parking resource management method based on big data technology described in any one of claims 1 to 6 can be implemented.

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