Private shared parking matching method and system for residential areas considering user characteristics

Abstract

The present invention provides a residential private shared parking matching method and system considering user characteristics, belonging to the technical field of urban parking operation and optimization management, collecting parking supply information and parking request information, defining parking supply matrix and parking request matrix respectively according to sharing period, subdividing the return demand of supply users based on user characteristics and performing guarantee processing, constructing a shared parking matching model based on binary integer programming, solving the matching model to adjust the price parameters in sharing, determining a reasonable supply and demand ratio, and obtaining a shared parking matching method. The present invention improves the utilization rate of parking spaces, makes full use of idle parking resources, realizes efficient and convenient parking, shortens parking cruising time, and makes travel more convenient; the utilization efficiency of parking spaces is improved, the total demand for parking resources will decrease, and at the planning level, the construction volume of basic parking facilities is reduced, saving land resources and construction funds.

Description

Technical Field

[0001] The present invention relates to the technical field of urban parking operation and optimization management, and in particular to a residential area private shared parking matching method and system taking user characteristics into consideration. Background Art

[0002] As the number of cars increases year by year, the demand for parking has surged, while parking space planning is insufficient and the level of parking facilities is not high. The difficulty of parking caused by the gap and contradiction between parking supply and demand is one of the long-term problems in the development of cities in various countries. In view of the problem of parking difficulties, it is not realistic to simply build more parking infrastructure. Improving the utilization efficiency of existing parking resources is an important breakthrough to alleviate the contradiction of urban parking. Therefore, the concept and application of "shared parking" have received attention. Shared parking is defined as the use of shared parking spaces during different peak parking periods of the day in a specific area. The shared parking model can not only improve the utilization rate of idle parking spaces and bring certain benefits to parking space sharers, but also reduce the time for parking demand to find parking spaces, thereby further alleviating traffic congestion. With the development and application of shared parking theory, many researchers have explored the shared parking model and its application in urban parking. In the implementation of shared parking of private parking spaces in residential areas, a major obstacle is that private parking space users consider potential cost risks and benefits, and are not willing to share. Therefore, for urban planning and parking management, it is very important to consider the return characteristics and benefit risk protection of private parking space suppliers when conducting matching mechanism research to promote the actual application of shared parking.

[0003] Existing shared parking research focuses on three aspects: demand analysis, pricing, and matching. The research focus on shared parking matching has shifted from the early public parking sharing to private parking sharing. At present, the distribution characteristics of the return of supply users and the arrival of requesting users have not been taken seriously in matching; as the basis and premise of matching research, accurate analysis and prediction of the return of supply users and the arrival of requesting users play a key role in the design of matching mechanisms and the efficient completion of the matching process. In addition, the benefit guarantee of supply users has not been clearly reflected in matching; in the implementation of external sharing of private parking spaces in existing residential areas, the low willingness of supply users is one of the difficulties. The existing related matching research has failed to focus on the cost-effectiveness of supply users to improve and guarantee sharing willingness, which affects the application value of shared parking matching research. Summary of the invention

[0004] The object of the present invention is to provide a method and system for matching private shared parking in residential areas taking into account user characteristics, so as to solve at least one technical problem existing in the above-mentioned background technology.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In one aspect, the present invention provides a residential area private shared parking matching method considering user characteristics, comprising:

[0007] Collect parking supply information and parking request information, the parking supply information includes the start and end time of the shared parking space, and the parking request information includes the requested arrival time and parking duration;

[0008] According to the parking supply information and the parking request information, a parking supply matrix and a parking request matrix are defined respectively;

[0009] Based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, the return needs of the supply users are segmented and guaranteed.

[0010] Based on the parking supply matrix and the parking request matrix, considering the supply-demand matching constraints, time window constraints and user request acceptance constraints, and taking the maximization of parking space utilization as the goal, a shared parking matching model based on binary integer programming is constructed.

[0011] Solve the shared parking matching model, construct a dual-objective optimization function of the platform's pure profit and the supply user benefit with respect to the price parameter, and adjust the price parameters in the sharing to obtain the optimal price parameter combination;

[0012] Based on the optimal price parameter combination and the distribution of the objective optimization function in the two-dimensional space of supply and request, a reasonable supply-demand ratio is obtained, and finally a shared parking matching solution is obtained.

[0013] Preferably, the dividing point is determined based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, and the entire sharing is divided into two stages, sharing stage one and sharing stage two; the berths provided by the supply users are shared throughout the sharing stage one, the arrival of the requesting users only occurs in stage one, and the return of the supply users occurs within the two stages. When the return of the supply user occurs within the sharing stage one, it can be divided into two types: if the supply user returns at noon or before, it is considered to be a short-stay return type, and sharing resumes after the user leaves, and it is considered that sharing will continue until the last sharing period; if the supply user returns after noon, it is considered to be a regular return type.

[0014] Preferably, classification and guarantee processing are performed according to the return requirements and supply information of the supply user, including:

[0015] If the supply user plans to return within the first sharing phase, the short-term return parking situation of the supply user will be regarded as a requesting user, and a short-term parking space will be allocated to him first, with a lower rent, and a 100% acceptance rate for his request. It is assumed that the supply user who returns after a short stay only shares in the first sharing phase;

[0016] If the user plans to return within the first sharing phase, for the regular return of the user, if the user requests parking when returning to the parking space, the platform will give the user corresponding compensation, and the platform will use a certain cost to move the car, otherwise it will return directly to the parking space;

[0017] If the supply user plans to return during the second sharing phase, the first phase is fully shared and the second phase is partially shared, and the user returns directly to the berth;

[0018] If the supply user plans to return after the end of the sharing phase 2, the entire phase 1 and phase 2 will be shared and the user will return to the berth directly.

[0019] Preferably, according to the parking supply information and the parking request information, a parking supply matrix and a parking request matrix are defined respectively, including:

[0020] Obtain a parking supply matrix and a parking request matrix according to the reservation information;

[0021] Define the price parameters in sharing and build a tripartite relationship among the supply user, the request user and the parking management platform;

[0022] Define the objective function and constraints; the constraints include: supply-demand matching constraint, which limits each request to one parking space at most; supply matching constraint, which means that each parking space can accommodate at most one car in each sharing period; time window constraint, which ensures that the accepted request time occurs within the sharing period to avoid timeouts outside the sharing period; supply user request acceptance constraint, which ensures that the acceptance rate of requests converted from short-term stays within the supply user sharing period is 100%; decision variable constraint, the decision variables involved in the model are all binary variables, that is, their values ​​can only be 1 or 0.

[0023] Preferably, the evaluation index system of the matching model includes: parking space utilization rate as the first evaluation index, parking request acceptance rate as the second evaluation index, platform net profit as the third evaluation index, and user benefit as the fourth evaluation index.

[0024] Preferably, the parking space utilization rate is used as the first evaluation indicator, which is defined as the total occupation time of parking requests and the total supply time of parking spaces; the parking request acceptance rate is used as the second evaluation indicator, which is defined as the ratio of the total number of accepted requests to the total number of requests; the platform net profit is used as the third evaluation indicator, which is defined as the sum of the profits obtained from renting and selling parking spaces to requesting users and the profits obtained from renting and selling parking spaces to supply users who return after a short stay, minus the total costs of renting and purchasing parking spaces from supply users, the total compensation to supply users who return regularly during the sharing period, and the total costs required for moving vehicles after supply users who return regularly during the sharing period return; the supply user benefit is used as the fourth evaluation indicator, which is defined as the sum of the rent obtained from renting and selling parking spaces and the compensation obtained when the parking space exists for shared parking during the regular return during the sharing period, minus the total rent of renting a temporary parking space for a short stop and the total time cost incurred when the parking space exists for shared parking during the regular return during the sharing period.

[0025] In a second aspect, the present invention provides a residential area private shared parking matching system taking into account user characteristics, comprising:

[0026] A collection module, used to collect parking supply information and parking request information, the parking supply information includes the start and end time of the shared parking space, and the parking request information includes the requested arrival time and parking duration;

[0027] A definition module, used for defining a parking supply matrix and a parking request matrix respectively according to the parking supply information and the parking request information;

[0028] A segmentation module, used to segment the return requirements of supply users and perform guarantee processing based on the return distribution characteristics of supply users and the arrival distribution characteristics of requesting users;

[0029] A construction module is used to construct a shared parking matching model based on binary integer programming based on a parking supply matrix and a parking request matrix, taking into account supply and demand matching constraints, time window constraints, and supply user request acceptance constraints, with the goal of maximizing parking space utilization;

[0030] The solution module is used to solve the shared parking matching model, construct a dual-objective optimization function of the platform's pure profit and the supply user benefit with respect to the price parameter, and adjust the price parameters in the sharing to obtain the optimal price parameter combination;

[0031] The matching module is used to obtain a reasonable supply-demand ratio based on the optimal price parameter combination and the distribution of the target optimization function in the two-dimensional space of supply and request, and finally obtain a shared parking matching solution.

[0032] In a third aspect, the present invention provides a non-transitory computer-readable storage medium, which is used to store computer instructions. When the computer instructions are executed by a processor, the residential area private shared parking matching method considering user characteristics as described above is implemented.

[0033] In a fourth aspect, the present invention provides a computer program product, comprising a computer program, which, when executed on one or more processors, is used to implement the residential area private shared parking matching method taking into account user characteristics as described above.

[0034] In a fifth aspect, the present invention provides an electronic device comprising: a processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory so that the electronic device executes instructions for implementing the residential area private shared parking matching method considering user characteristics as described above.

[0035] Beneficial effects of the present invention:

[0036] 1) From the perspective of urban transportation, shared parking has revitalized existing parking resources, improved the utilization rate of parking spaces, and alleviated the problem of parking difficulties. Relying on the development of the Internet, the electronic parking platform is used to realize shared reservations and supply and demand matching. Considering the distribution characteristics of supply users returning and request users arriving, as well as the benefits of supply users, without affecting regular use, idle parking resources are fully utilized, and parking spaces are allocated to public parking requests, alleviating the problem of parking difficulties, reducing traffic pressure and environmental pollution;

[0037] 2) From the perspective of economic benefits, shared parking can generate considerable economic benefits for vacant parking spaces, and all parties involved can benefit. Parking space providers can obtain additional income through shared parking spaces, and shared parking platform operators can obtain price difference profits by charging service management fees. Parking requesters can reserve parking spaces through the shared platform, and parking can be efficiently and conveniently parked during travel, shortening parking cruising time and making travel more convenient;

[0038] 3) From the perspective of traffic planning, shared parking provides a new solution to the parking problem in the city center. Under the shared parking model, the utilization efficiency of parking spaces in residential areas is improved, and the total demand for parking resources will decrease. At the planning level, shared parking can reduce the construction of basic parking facilities and save precious land resources and construction funds.

[0039] Additional advantages of the present invention will be more clearly given in the following description or learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0041] Figure 1 This is a flow chart of a design scheme for a residential area private shared parking matching method taking user characteristics into consideration according to an embodiment of the present invention.

[0042] Figure 2 This is a flowchart of the provision of user segmentation and guarantee processing according to an embodiment of the present invention.

[0043] Figure 3 A flowchart for constructing a private shared parking matching model taking user characteristics into consideration according to an embodiment of the present invention.

[0044] Figure 4 This is a graph showing changes in the platform's net profit and user benefit under different supply and demand relationships described in an embodiment of the present invention.

[0045] Figure 5 This is a graph showing changes in berth utilization and parking request acceptance rate under different supply and demand relationships described in an embodiment of the present invention.

[0046] Figure 6 This is a flow chart of the NSGA-II algorithm for solving dual-objective optimization according to an embodiment of the present invention.

[0047] Figure 7 This is a distribution diagram of the optimal price parameter combination for dual-objective optimization of platform pure profit and supply user benefit under different supply and demand relationships described in the embodiments of the present invention.

[0048] Figure 8 It is a contour map of berth utilization in a two-dimensional space of supply and request according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below by the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0050] It should be understood by those skilled in the art that unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this invention belongs.

[0051] It should also be understood that terms, such as those defined in commonly used dictionaries, should be understood to have a meaning consistent with that in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless as defined herein.

[0052] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements and / or groups thereof.

[0053] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0054] To facilitate understanding of the present invention, the present invention is further explained below with reference to specific embodiments in conjunction with the accompanying drawings, and the specific embodiments do not constitute a limitation on the embodiments of the present invention.

[0055] Those skilled in the art should understand that the drawings are merely schematic diagrams of embodiments, and the components in the drawings are not necessarily necessary for implementing the present invention.

[0056] Example 1

[0057] This embodiment 1 provides a residential area private shared parking matching system taking into account user characteristics, including:

[0058] A collection module, used to collect parking supply information and parking request information, the parking supply information includes the start and end time of the shared parking space, and the parking request information includes the requested arrival time and parking duration;

[0059] A definition module, used for defining a parking supply matrix and a parking request matrix respectively according to the parking supply information and the parking request information;

[0060] A segmentation module, used to segment the return requirements of supply users and perform guarantee processing based on the return distribution characteristics of supply users and the arrival distribution characteristics of requesting users;

[0061] A construction module is used to construct a shared parking matching model based on binary integer programming based on a parking supply matrix and a parking request matrix, taking into account supply and demand matching constraints, time window constraints, and supply user request acceptance constraints, with the goal of maximizing parking space utilization;

[0062] The solution module is used to solve the shared parking matching model, construct a dual-objective optimization function of the platform's pure profit and the supply user benefit with respect to the price parameter, and adjust the price parameters in the sharing to obtain the optimal price parameter combination;

[0063] The matching module is used to obtain a reasonable supply-demand ratio based on the optimal price parameter combination and the distribution of the target optimization function in the two-dimensional space of supply and request, and finally obtain a shared parking matching solution.

[0064] In this embodiment 1, the above system is used to implement a residential area private shared parking matching method that takes user characteristics into consideration, including:

[0065] Collect parking supply information and parking request information, the parking supply information includes the start and end time of the shared parking space, and the parking request information includes the requested arrival time and parking duration;

[0066] According to the parking supply information and the parking request information, a parking supply matrix and a parking request matrix are defined respectively;

[0067] Based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, the return needs of the supply users are segmented and guaranteed.

[0068] Based on the parking supply matrix and the parking request matrix, considering the supply-demand matching constraints, time window constraints and user request acceptance constraints, and taking the maximization of parking space utilization as the goal, a shared parking matching model based on binary integer programming is constructed.

[0069] Solve the shared parking matching model, construct a dual-objective optimization function of the platform's pure profit and the supply user benefit with respect to the price parameter, and adjust the price parameters in the sharing to obtain the optimal price parameter combination;

[0070] Based on the optimal price parameter combination and the distribution of the objective optimization function in the two-dimensional space of supply and request, a reasonable supply-demand ratio is obtained, and finally a shared parking matching solution is obtained.

[0071] Specifically, the dividing point is determined based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, and the entire sharing is divided into two stages, sharing stage one and sharing stage two; the berths provided by the supply users are shared throughout the sharing stage one, the arrival of the requesting users only occurs in stage one, and the return of the supply users occurs in both stages. When the return of the supply user occurs in sharing stage one, it can be divided into two types: if the supply user returns at noon or before, it is considered to be a short-stay return type, and sharing resumes after the user leaves, and it is considered that sharing will continue until the last sharing period; if the supply user returns after noon, it is considered to be a regular return type.

[0072] Among them, classification and guarantee processing are carried out according to the return requirements and supply information of the supply users, including:

[0073] If the supply user plans to return within the first sharing phase, the short-term return parking situation of the supply user will be regarded as a requesting user, and a short-term parking space will be allocated to him first, with a lower rent, and a 100% acceptance rate for his request. It is assumed that the supply user who returns after a short stay only shares in the first sharing phase;

[0074] If the user plans to return within the first sharing phase, for the regular return of the user, if the user requests parking when returning to the parking space, the platform will give the user corresponding compensation, and the platform will use a certain cost to move the car, otherwise it will return directly to the parking space;

[0075] If the supply user plans to return during the second sharing phase, the first phase is fully shared and the second phase is partially shared, and the user returns directly to the berth;

[0076] If the supply user plans to return after the end of the sharing phase 2, the entire phase 1 and phase 2 will be shared and the user will return to the berth directly.

[0077] According to the parking supply information and the parking request information, a parking supply matrix and a parking request matrix are defined respectively, including:

[0078] Obtain a parking supply matrix and a parking request matrix according to the reservation information;

[0079] Define the price parameters in sharing and build a tripartite relationship among the supply user, the request user and the parking management platform;

[0080] Define the objective function and constraints; the constraints include: supply-demand matching constraint, which limits each request to one parking space at most; supply matching constraint, which means that each parking space can accommodate at most one car in each sharing period; time window constraint, which ensures that the accepted request time occurs within the sharing period to avoid timeouts outside the sharing period; supply user request acceptance constraint, which ensures that the acceptance rate of requests converted from short-term stays within the supply user sharing period is 100%; decision variable constraint, the decision variables involved in the model are all binary variables, that is, their values ​​can only be 1 or 0.

[0081] Among them, the evaluation index system of the matching model includes: parking space utilization rate as the first evaluation index, parking request acceptance rate as the second evaluation index, platform net profit as the third evaluation index, and user benefit as the fourth evaluation index.

[0082] Specifically, the parking space utilization rate is taken as the first evaluation indicator, which is defined as the total occupation time of parking requests and the total supply time of parking spaces; the parking request acceptance rate is taken as the second evaluation indicator, which is defined as the ratio of the total number of accepted requests to the total number of requests; the platform net profit is taken as the third evaluation indicator, which is defined as the sum of the profits obtained from renting and selling parking spaces to requesting users and the profits obtained from renting and selling parking spaces to supply users who return after a short stay, minus the total costs of renting and purchasing parking spaces from supply users, the total compensation to supply users who return regularly during the sharing period, and the total costs required for moving parking spaces after supply users who return regularly during the sharing period return; the supply user benefit is taken as the fourth evaluation indicator, which is defined as the sum of the rent obtained from renting and selling parking spaces and the compensation obtained when the parking spaces exist for shared parking during the regular return during the sharing period, minus the total rent for renting temporary parking spaces for short-term stopovers and the total time cost incurred when the parking spaces exist for shared parking during the regular return during the sharing period.

[0083] Example 2

[0084] This embodiment 2 proposes a residential private shared parking matching scheme that takes into account user characteristics. On a certain working day, the users who provide parking spaces have a tidal characteristic of "leaving early and returning late", and the users who request parking spaces all arrive during the day. Considering the distribution characteristics of the return of supply users and the arrival of request users and the benefits of supply users, a shared parking matching model based on binary integer programming is constructed. The changes in indicators such as parking utilization rate, parking request acceptance rate, and supply user benefits under different supply and demand relationships are further analyzed, and the optimal price parameter combination and reasonable supply and demand ratio are explored based on the matching results.

[0085] like Figure 1 As shown, the residential area shared parking matching solution considering user characteristics provided in this embodiment 2 specifically includes the following steps:

[0086] Step 100, the parking platform based on mobile Internet collects parking supply and request information in advance. The supply information includes the start and end time of the shared parking space, and the request information includes the requested arrival time and parking duration;

[0087] Step 101, define parking supply and request matrices according to the sharing time period. Divide the entire sharing into several time periods (for example, each time period is 30 minutes apart), and define parking supply and request matrices according to the status of supply or request in each sharing time period;

[0088] Step 102, based on user characteristics, the return requirements of the supplying users are subdivided and guaranteed. According to the user characteristics, i.e., the return distribution characteristics of the supplying users and the arrival distribution characteristics of the requesting users, the entire sharing is divided into two stages, including sharing stage 1 and sharing stage 2, and the return requirements of the supplying users are further subdivided and guaranteed;

[0089] Step 103, constructing a shared parking matching model based on binary integer programming. According to the supply and request matrix obtained in step 101, considering the supply and demand matching constraints, time window constraints and supply user request acceptance constraints, with the goal of maximizing the parking space utilization, construct a shared parking matching model based on binary integer programming;

[0090] Step 104, solve the shared parking matching model and adjust the price parameters in the sharing. Solve the matching results, construct a dual-objective optimization of the platform's pure profit and the supply user benefit with respect to the price parameters, and obtain the optimal price parameter combination;

[0091] Step 105, find a reasonable supply-demand ratio and obtain a shared parking matching solution. Based on the matching results, according to the distribution of the objective function in the two-dimensional space of supply and request, a reasonable supply-demand ratio is obtained, and finally a shared parking matching solution is obtained.

[0092] Specifically, Figure 2 As shown, step 102 specifically includes: based on user characteristics, the return needs of the supply users are subdivided and guaranteed, based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, the demarcation point is determined, and the entire sharing is divided into two stages, the sharing stage one and the sharing stage two; the berth provided by the supply user is shared throughout the sharing stage one, the arrival of the requesting user only occurs in the stage one, and the return of the supply user occurs in the two stages. When the return of the supply user occurs in the sharing stage one, it can be divided into two types: if the supply user returns at noon or before, it is considered to be a short-term return type, assuming that the average stay time is 1 hour, and the sharing resumes after the user leaves, and it is considered that the sharing will continue until the last sharing period; if the supply user returns after noon, it is considered to be a regular return type;

[0093] According to the return requirements and supply information of the supply users, classification and guarantee processing are carried out:

[0094] (1) If the supply user plans to return within the first sharing phase, the short-term return parking situation of the supply user is regarded as a requesting user, and a short-term parking space is allocated to him first, with a lower rent, and a 100% acceptance rate for his request. It is assumed that the supply user who returns after a short stay only shares in the first sharing phase;

[0095] (2) If the user plans to return within the first sharing phase, for the regular return of the user, if the user requests parking when returning to the parking space, the platform will give the user corresponding compensation, and the platform will use a certain cost to move the car, otherwise the user will return directly to the parking space;

[0096] (3) If the supply user plans to return during the second sharing phase, the supply user will return to the berth directly if the first phase is fully shared and the second phase is partially shared;

[0097] (4) If the supply user plans to return after the end of sharing phase 2, the entire phase 1 and phase 2 will be shared and the user will return directly to the berth.

[0098] like Figure 3 As shown, step 103 specifically includes:

[0099] Step 300, obtaining parking supply and parking request matrix according to reservation information:

[0100] Assume that the shared period is divided into K intervals, the first K c The interval is stage 1, and then KK c The interval is stage 2. For the supply side, a binary variable is introduced When berth n is available in time period k, Otherwise it is 0. Get the parking request matrix,

[0101] Next, three binary variables are introduced to distinguish the returns provided to users:

[0102] (1) Introducing binary variable b n Determine whether the supply user returns in the sharing phase 1. If so, b n =1, otherwise, b n =0;

[0103] (2) Introducing binary variable c n Determine whether the user's return is a short-term return. If so, c n =1, otherwise, c n =0;

[0104] (3) Introducing binary variable w nDetermine whether there is a shared parking space when the user returns normally. If so, w n =1, otherwise, w n =0.

[0105] For the requester, assume that M is the total number of public parking requests arriving during the entire sharing period, and are the time periods when request m arrives and leaves, respectively. The duration of the request is Consider providing users with short-term stays and returning, as the requester to match berths, and are the arrival and departure time periods of the short-term requests generated by the supply users corresponding to berth n, and are also the return and departure time periods of the supply users. Introduce a binary variable When the duration of request m contains period k, Otherwise it is 0. Get the parking request matrix, m=1, 2,...M+N, k=1, 2,...K.

[0106] Each berth can be occupied by different requests during the sharing process. In this case, a binary decision variable x is introduced. nm If request m is accepted by berth n, it is considered a successful match, x nm =1, otherwise 0. Then, there is a matching result matrix X N×(M+N) =[x nm ], n = 1, 2, ... N, m = 1, 2, ... M + N. According to the parking request matrix D M ×K and matching result matrix X N × M , define the parking space occupancy matrix The specific element relationships are as follows:

[0107]

[0108] Step 301, define the price parameters in sharing, and build a tripartite relationship among the supply user, the request user and the parking management platform: let p so and p sp They represent the unit sales price of renting and selling cars to short-term supply users and general public request users, respectively, b represents the unit rental price (the rental price of the berth for the shared period provided to the user unit), p p The unit compensation price for parking in the parking space after the user returns, p m represents the unit cost of moving the car after the user returns to the parking space, p t It means that after the user returns to the parking space, there is a time cost for parking and waiting for the car to be moved.

[0109] Step 302, define the objective function and constraints:

[0110] Goal: Maximize berth utilization

[0111]

[0112] In the formula, Indicates the total time taken by parking requests, Indicates the total berth supply time.

[0113] Constraint 1: Supply and demand matching constraint, limiting each request to at most one parking space.

[0114]

[0115] Constraint 2: Supply matching constraint, each parking space can accommodate at most one car during each sharing period.

[0116]

[0117] Constraint 3: Time window constraint, which ensures that all accepted requests occur within the shared time period to avoid timeouts outside the shared time period.

[0118] q nm ·x nm =0, n=1, 2, 3,...N, m=1, 2, 3..., M

[0119] Among them, the binary variable q nm , in the arrival period of request m, if the parking duration of request m is within the entire sharing period, q nm =0, otherwise 1.

[0120] Constraint 4: The supply user request acceptance constraint ensures that the request acceptance rate for short-term stay return conversion by the supply user within the shared time period is 100%.

[0121]

[0122] Constraint 5: Decision variable constraint. All decision variables involved in the model are binary variables, that is, their values ​​can only be 1 or 0.

[0123] x nm ∈{0, 1}, n=1, 2, 3,...N, m=1, 2, 3..., M

[0124] Regarding step 104, the evaluation index system of the matching model is as follows:

[0125] The berth utilization rate is used as the first evaluation indicator, which is defined as the total parking request occupancy time and the total berth supply time. The specific mathematical expression is as follows:

[0126]

[0127] The parking request acceptance rate is the second evaluation indicator, which is defined as the ratio of the total number of accepted requests to the total number of requests. The specific mathematical expression is as follows:

[0128]

[0129] The third evaluation indicator is the net profit of the platform, which is defined as the sum of the profits from renting and selling parking spaces to requesting users and the profits from renting and selling parking spaces to supply users who return after a short stay, minus the total cost of renting and purchasing parking spaces from supply users, the total compensation to supply users who return regularly during the sharing period, and the total cost of moving the parking spaces after the supply users who return regularly during the sharing period return. The specific mathematical expression is as follows:

[0130]

[0131] The fourth evaluation indicator is the user benefit, which is defined as the sum of the rent for renting and selling parking spaces and the compensation for shared parking spaces during the regular return period, minus the total rent for renting temporary parking spaces for short-term stopovers and the total time cost incurred when shared parking spaces are available during the regular return period. The specific mathematical expression is as follows:

[0132]

[0133] Example 3

[0134] In this embodiment 3, a numerical experiment is taken as an example to further illustrate the residential area private shared parking matching scheme considering user characteristics:

[0135] Assume that sharing occurs between 9:30AM and 9:30PM on a certain weekday, lasting for 12 hours with an interval of 0.5 hours. The total number of sharing periods K = 24. Assume that the peak of supply users' return is around 5:30PM and the peak of request users' arrival is before 5:30PM, so 5:30PM is taken as the dividing point between the two sharing stages. Assume that the total number of parking spaces rented or purchased by the operating platform from suppliers is N = 100, and all parking spaces are fully shared in stage one. The return of supply users occurs in two stages. For sensitivity analysis, the number of parking requests M varies continuously from 0 to 1000, and the arrival of request users only occurs in stage one. Assume that the return of supply users and the arrival of request users both follow a Gaussian mixture distribution, and the requested parking time follows a negative exponential distribution, with an average parking time of 3 hours. Assume

[0136] The sales price of a parking space per unit time period is p so =5 and p sp=8, rental price per unit time period p b =4, unit vehicle compensation price p p =10, the unit vehicle cost of the moving operation p m =4, the time cost per unit of the return vehicle p t =6, penalty coefficient μ=0.

[0137] In order to explore the changes of various evaluation indicators under different supply and demand relationships, a cross-comparison analysis of the evaluation indicators with the increase of parking requests under fixed supply was conducted, and the following plots were made: Figure 4 and Figure 5 shown.

[0138] In order to explore the optimal price parameter combination under different supply and demand relationships in the matching scheme of the present invention, a dual-objective optimization of platform pure profit and supply user benefit is constructed, and the genetic algorithm with fast non-dominated sorting elite strategy (NSGA-II) is used to solve it. The algorithm flow chart and solution results are shown in the figure. Figure 6 and Figure 7 shown.

[0139] In order to explore the reasonable supply-demand ratio in the matching scheme of the present invention, the berth utilization rate contour map in the two-dimensional space of supply and request is drawn, as shown in Figure 8 shown. Figure 8 Two supply and demand ratio lines are marked:

[0140] 1) Optimal request line under certain supply: Given a given number of berths, the berth utilization rate increases with the number of parking requests. To determine the reasonable ratio of supply to requests, the optimal request line under a certain supply is marked in the figure. The slope of the line is the supply-demand ratio N / M. This supply-demand ratio shows the number of parking requests that the operation management platform should accept to achieve efficient matching and maximize berth utilization and platform net profit when the number of shared berths available for rent in a certain area is fixed.

[0141] 2) Optimal supply line under certain requests: Under a given number of parking requests, the parking space utilization rate decreases as the number of parking space supply increases. In order to determine a reasonable request and supply ratio, the optimal supply line under a certain request is marked in the figure. The inverse of the slope of the line is the supply-demand ratio N / M. This ratio line shows the number of parking spaces that the platform operator should rent to ensure efficient matching, maximize parking space utilization and maximize platform net profit under a given or predicted number of parking requests.

[0142] Example 4

[0143] Embodiment 4 of the present invention provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, a residential area private shared parking matching method considering user characteristics is implemented. The method includes:

[0144] Collect parking supply information and parking request information; the parking supply information includes the start and end time of the shared parking space, and the parking request information includes the requested arrival time and parking duration;

[0145] According to the parking supply information and the parking request information, a parking supply matrix and a parking request matrix are defined respectively;

[0146] Based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, the return needs of the supply users are segmented and guaranteed.

[0147] Based on the parking supply matrix and the parking request matrix, considering the supply-demand matching constraints, time window constraints and user request acceptance constraints, and taking the maximization of parking space utilization as the goal, a shared parking matching model based on binary integer programming is constructed.

[0148] Solve the shared parking matching model, construct a dual-objective optimization function of the platform's pure profit and the supply user benefit with respect to the price parameter, and adjust the price parameters in the sharing to obtain the optimal price parameter combination;

[0149] Based on the optimal price parameter combination and the distribution of the objective optimization function in the two-dimensional space of supply and request, a reasonable supply-demand ratio is obtained, and finally a shared parking matching solution is obtained.

[0150] Example 5

[0151] Embodiment 5 of the present invention provides a computer program (product), including a computer program, wherein when the computer program is executed on one or more processors, the computer program is used to implement a residential area private shared parking matching method considering user characteristics, the method comprising:

[0152] Collect parking supply information and parking request information, the parking supply information includes the start and end time of the shared parking space, and the parking request information includes the requested arrival time and parking duration;

[0153] According to the parking supply information and the parking request information, a parking supply matrix and a parking request matrix are defined respectively;

[0154] Based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, the return needs of the supply users are segmented and guaranteed.

[0155] Based on the parking supply matrix and the parking request matrix, considering the supply-demand matching constraints, time window constraints and user request acceptance constraints, and taking the maximization of parking space utilization as the goal, a shared parking matching model based on binary integer programming is constructed.

[0156] Solve the shared parking matching model, construct a dual-objective optimization function of the platform's pure profit and the supply user benefit with respect to the price parameter, and adjust the price parameters in the sharing to obtain the optimal price parameter combination;

[0157] Based on the optimal price parameter combination and the distribution of the objective optimization function in the two-dimensional space of supply and request, a reasonable supply-demand ratio is obtained, and finally a shared parking matching solution is obtained.

[0158] Example 6

[0159] Embodiment 6 of the present invention provides an electronic device, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to execute instructions for implementing a residential area private shared parking matching method considering user characteristics, the method comprising:

[0160] Collect parking supply information and parking request information; the parking supply information includes the start and end time of the shared parking space, and the parking request information includes the requested arrival time and parking duration;

[0161] According to the parking supply information and the parking request information, a parking supply matrix and a parking request matrix are defined respectively;

[0162] Based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, the return needs of the supply users are segmented and guaranteed.

[0163] Based on the parking supply matrix and the parking request matrix, considering the supply-demand matching constraints, time window constraints and user request acceptance constraints, and taking the maximization of parking space utilization as the goal, a shared parking matching model based on binary integer programming is constructed.

[0164] Solve the shared parking matching model, construct a dual-objective optimization function of the platform's pure profit and the supply user benefit with respect to the price parameter, and adjust the price parameters in the sharing to obtain the optimal price parameter combination;

[0165] Based on the optimal price parameter combination and the distribution of the objective optimization function in the two-dimensional space of supply and request, a reasonable supply-demand ratio is obtained, and finally a shared parking matching solution is obtained.

[0166] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0167] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0168] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0169] These computer program instructions can also be loaded onto a computer or other programmable data processing device, and a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0170] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative work on the basis of the technical solution disclosed in the present invention should be included in the scope of protection of the present invention.

Claims

1. A residential area private shared parking matching method considering user characteristics, characterized in that: include: Collect parking supply information and parking request information, the parking supply information includes the start and end time of the shared parking space, and the parking request information includes the requested arrival time and parking duration; According to the parking supply information and the parking request information, a parking supply matrix and a parking request matrix are defined respectively; Based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, the return needs of the supply users are subdivided and guaranteed processing is performed; wherein, based on the return distribution characteristics of the supply users and the arrival distribution characteristics of the requesting users, the demarcation point is determined, and the entire sharing is divided into two stages, sharing stage one and sharing stage two; the berths provided by the supply users are shared throughout the sharing stage one, the arrival of the requesting users only occurs in stage one, and the return of the supply users occurs in two stages. When the return of the supply users occurs in the sharing stage one, it can be divided into two types: if the supply users return at noon or before, it is considered to be a short-stay return type, and sharing will resume after the user leaves, and it is considered that sharing will continue until the last sharing period; if the supply users return after noon, it is considered to be a regular return type; classification and guarantee processing are performed according to the return needs of the supply users and the supply information, including: If the supply user plans to return within the first sharing phase, the short-term return parking situation of the supply user will be regarded as a requesting user, and a short-term parking space will be allocated to him first, with a lower rent, and a 100% acceptance rate for his request. It is assumed that the supply user who returns after a short stay only shares in the first sharing phase; If the user plans to return within the first sharing phase, for the regular return of the user, if the user requests parking when returning to the parking space, the platform will give the user corresponding compensation, and the platform will use a certain cost to move the car, otherwise it will return directly to the parking space; If the supply user plans to return during the second sharing phase, the first phase is fully shared and the second phase is partially shared, and the user returns directly to the berth; If the supply user plans to return after the end of the sharing phase 2, the entire phase 1 and phase 2 will be shared and the user will return to the berth directly; Based on the parking supply matrix and the parking request matrix, considering the supply-demand matching constraints, time window constraints and user request acceptance constraints, and taking the maximization of parking space utilization as the goal, a shared parking matching model based on binary integer programming is constructed. Solve the shared parking matching model, construct a dual-objective optimization function of the platform's pure profit and the supply user benefit with respect to the price parameter, and adjust the price parameters in the sharing to obtain the optimal price parameter combination; Based on the optimal price parameter combination, according to the distribution of the target optimization function in the two-dimensional space of supply and request, a reasonable supply-demand ratio is obtained, and finally a shared parking matching solution is obtained; Among them, the parking space utilization rate is the first evaluation indicator, which is defined as the total occupation time of parking requests and the total supply time of parking spaces; the parking request acceptance rate is the second evaluation indicator, which is defined as the ratio of the total number of accepted requests to the total number of requests; the platform net profit is the third evaluation indicator, which is defined as the sum of the profits obtained from renting and selling parking spaces to requesting users and the profits obtained from renting and selling parking spaces to supply users who return after a short stay, minus the total cost of renting and purchasing parking spaces from supply users, the total compensation to supply users who return regularly during the sharing period, and the total cost of moving the parking spaces after supply users who return regularly during the sharing period return; the supply user benefit is the fourth evaluation indicator, which is defined as the sum of the rent obtained from renting and selling parking spaces and the compensation obtained when the parking spaces exist for shared parking during regular returns during the sharing period, minus the total rent for renting temporary parking spaces for short-term stops and the total time cost incurred when the parking spaces exist for shared parking during regular returns during the sharing period.

2. The residential area private shared parking matching method considering user characteristics according to claim 1 is characterized in that: According to the parking supply information and the parking request information, a parking supply matrix and a parking request matrix are defined respectively, including: Obtain a parking supply matrix and a parking request matrix according to the reservation information; Define the price parameters in sharing and build a tripartite relationship among the supply user, the request user and the parking management platform; Define the objective function and constraints; the constraints include: supply-demand matching constraint, which limits each request to one parking space at most; supply matching constraint, which means that each parking space can accommodate at most one car in each sharing period; time window constraint, which ensures that the accepted request time occurs within the sharing period to avoid timeouts outside the sharing period; supply user request acceptance constraint, which ensures that the acceptance rate of requests converted from short-term stays within the supply user sharing period is 100%; decision variable constraint, the decision variables involved in the model are all binary variables, that is, their values ​​can only be 1 or 0.

3. The residential area private shared parking matching method considering user characteristics according to claim 2 is characterized in that: The evaluation index system of the matching model includes: parking space utilization rate as the first evaluation index, parking request acceptance rate as the second evaluation index, platform net profit as the third evaluation index, and user benefit as the fourth evaluation index.

4. A residential area private shared parking matching system considering user characteristics, characterized in that: include: A collection module, used for collecting parking supply information and parking request information; The parking supply information includes the start and end time of the shared parking space, and the parking request information includes the requested arrival time and parking duration; A definition module, used for defining a parking supply matrix and a parking request matrix respectively according to the parking supply information and the parking request information; The segmentation module is used to segment the return demand of the supply user and perform guarantee processing based on the return distribution characteristics of the supply user and the arrival distribution characteristics of the requesting user; wherein, the demarcation point is determined based on the return distribution characteristics of the supply user and the arrival distribution characteristics of the requesting user, and the entire sharing is divided into two stages, sharing stage one and sharing stage two; the berth provided by the supply user is shared throughout the sharing stage one, the arrival of the requesting user only occurs in stage one, and the return of the supply user occurs in two stages. When the return of the supply user occurs in the sharing stage one, it can be divided into two types: if the supply user returns at noon or before, it is considered to be a short-stay return type, and sharing will resume after the user leaves, and it is considered that sharing will continue until the last sharing period; if the supply user returns after noon, it is considered to be a regular return type; classification and guarantee processing are performed according to the return demand of the supply user and the supply information, including: If the supply user plans to return within the first sharing phase, the short-term return parking situation of the supply user will be regarded as a requesting user, and a short-term parking space will be allocated to him first, with a lower rent, and a 100% acceptance rate for his request. It is assumed that the supply user who returns after a short stay only shares in the first sharing phase; If the user plans to return within the first sharing phase, for the regular return of the user, if the user requests parking when returning to the parking space, the platform will give the user corresponding compensation, and the platform will use a certain cost to move the car, otherwise it will return directly to the parking space; If the supply user plans to return during the second sharing phase, the first phase is fully shared and the second phase is partially shared, and the user returns directly to the berth; If the supply user plans to return after the end of the sharing phase 2, the entire phase 1 and phase 2 will be shared and the user will return to the berth directly; A construction module is used to construct a shared parking matching model based on binary integer programming based on a parking supply matrix and a parking request matrix, taking into account supply and demand matching constraints, time window constraints, and supply user request acceptance constraints, with the goal of maximizing parking space utilization; The solution module is used to solve the shared parking matching model, construct a dual-objective optimization function of the platform's pure profit and the supply user benefit with respect to the price parameter, and adjust the price parameters in the sharing to obtain the optimal price parameter combination; The matching module is used to obtain a reasonable supply-demand ratio based on the optimal price parameter combination and the distribution of the target optimization function in the two-dimensional space of supply and request, and finally obtain a shared parking matching solution; Among them, the parking space utilization rate is the first evaluation indicator, which is defined as the total occupation time of parking requests and the total supply time of parking spaces; the parking request acceptance rate is the second evaluation indicator, which is defined as the ratio of the total number of accepted requests to the total number of requests; the platform net profit is the third evaluation indicator, which is defined as the sum of the profits obtained from renting and selling parking spaces to requesting users and the profits obtained from renting and selling parking spaces to supply users who return after a short stay, minus the total cost of renting and purchasing parking spaces from supply users, the total compensation to supply users who return regularly during the sharing period, and the total cost of moving the parking spaces after supply users who return regularly during the sharing period return; the supply user benefit is the fourth evaluation indicator, which is defined as the sum of the rent obtained from renting and selling parking spaces and the compensation obtained when the parking spaces exist for shared parking during regular returns during the sharing period, minus the total rent for renting temporary parking spaces for short-term stops and the total time cost incurred when the parking spaces exist for shared parking during regular returns during the sharing period.

5. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the residential area private shared parking matching method considering user characteristics as described in any one of claims 1-3 is implemented.

6. A computer program product, characterized in that It comprises a computer program, which, when running on one or more processors, is used to implement the residential area private shared parking matching method considering user characteristics as described in any one of claims 1-3.

7. An electronic device, characterized in that: include: A processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to execute instructions for implementing the residential area private shared parking matching method considering user characteristics as described in any one of claims 1-3.

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