A priority-driven hybrid shared parking and charging resource optimization method

Abstract

The application discloses a priority-driven mixed shared parking and charging resource optimization method, aiming at solving the problems of unreasonable resource allocation of existing shared parking lot, imbalance between supply and demand of parking spaces and low utilization rate of charging parking spaces. First, a priority matching mechanism of multiple types of parking spaces and parking demand is constructed, and the priority is set according to the parking demand type and the parking space attribute, so that the matching of mixed demand and charging parking spaces is preferentially met. Secondly, the parking lot and demand data are collected, and an optimization model with the target of maximizing the operation profit is constructed, and the target function includes the income, the cost and the penalty cost. By introducing the time window constraint of the parking demand and the shared parking space supply, the timeliness and rationality of the supply and demand matching are ensured. The constraint relationship between the demand and the supply is established, and the resource allocation efficiency is optimized. The application can significantly improve the utilization efficiency of parking and charging resources, improve the user experience, relieve the parking problem and help the promotion of the shared parking policy.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of traffic engineering and traffic information and control system, and relates to the technical field of intelligent transportation system, and more particularly to a priority-driven mixed shared parking and charging resource optimization method. BACKGROUND

[0002] With the acceleration of urbanization and the continuous growth of the number of motor vehicles, the problem of parking difficulty is increasingly prominent, especially in high-demand areas such as business centers, residential areas and colleges, the contradiction between supply and demand of parking resources is intensified. The introduction of the sharing economy model provides a new solution to the parking problem, and the optimal allocation of shared parking resources has gradually become a research hotspot in academia and industry. Through effective management and allocation of parking resources, congestion can be reduced, parking efficiency can be improved, parking utilization can be optimized, and resource waste can be reduced.

[0003] In existing research, most scholars focus on the allocation of single-function parking lot resources, such as shared parking allocation in residential areas, commercial areas and college parking lots. Chen Jun and Xie Kai proposed a double-layer dynamic shared allocation model based on the parking demand of colleges and universities, taking into account the balance between vehicle demand and social demand (Chen J, Xie K. Dynamic allocation model and effect evaluation of central city college parking lot sharing [J]. China Journal of Highway, 2015, 28(11): 104-111.); Duan Manzhen proposed a double-constrained shared parking allocation model for residential areas, taking walking distance and idle parking index as optimization objectives (Duan M Z, Yang Z S, Zhang L, et al. Shared parking allocation model in residential areas under individualized guidance [J]. Journal of Northeast University (Natural Science Edition), 2017, 38(02): 174-179.). Weighted vertex graph model based on ant colony algorithm, particle swarm search algorithm and chance-constrained optimization are also used to solve the parking supply and demand matching problem, and good resource utilization results have been achieved. However, these studies are mostly limited to the optimization of single parking demand type, and fail to cover the diversity and complexity of parking and charging demand in mixed parking lots.

[0004] In recent years, with the popularity of electric vehicles, the layout of charging piles and the management of charging parking spaces have become new challenges for parking resource allocation. Some scholars have conducted research on mixed parking and charging scenarios, such as Xie et al. optimizing parking demand and supply matching through dynamic adjustment mechanism (Xie M, Lin S, Wu Z, et al. Optimal allocation and adjustment mechanism of shared parking slots considering combined parking resources [J]. Transportation Letters, 2023, 15(7): 730-741.); Zhang et al. constructed a bilateral preference multi-objective optimization model to improve user satisfaction and parking space utilization (Zhang Y, Wen H, Zhao M, et al. How does bilateral preference affect shared parking in sharing economy? [J]. Mathematical Problems in Engineering, 2020, 2020.). However, current researches mostly take parking resources or charging resources as separate objects, lacking a unified optimization method for mixed parking and charging scenarios. In addition, most existing methods optimize resources from the user's perspective, ignoring how the background manager can achieve optimal allocation of resources through overall planning and decision-making.

[0005] In this context, how to construct a priority-driven resource allocation mode in mixed parking and charging parking lots, coordinate parking demand and charging demand through dynamic matching mechanism, and improve the utilization efficiency of parking resources and charging facilities has become a key technical problem to be solved. The invention proposes a priority-driven mixed shared parking and charging resource optimization method to meet diversified parking demand, realize efficient allocation of resources, and comprehensively improve user experience. SUMMARY

[0006] Technical problem: In view of the problems that existing parking resource allocation methods ignore the characteristics of mixed parking and charging demand, the supply and demand matching mechanism is insufficient, and the parking efficiency and user experience cannot be considered, the purpose of the invention is to provide a priority-driven mixed shared parking and charging resource optimization method, by introducing a dynamic matching mechanism based on priority, combining collected data, time window constraints and multi-objective optimization model, coordinating the resource allocation of multiple types of parking spaces and parking and charging demand, to improve resource utilization efficiency and user satisfaction, and promote the intelligentization and efficient management of shared parking lots.

[0007] Technical solution: To solve the above technical problems, a priority-driven mixed shared parking and charging resource optimization method of the application comprises the following steps:

[0008] Step 1: Establish a priority matching mechanism between multiple types of parking spaces and parking demand to realize reasonable allocation of resources and maximize benefits; wherein the matching priority of mixed demand and charging parking spaces is the highest, the platform obtains parking and charging benefits at the same time, priority is given to mixed demand, and potential high-value demand is avoided due to insufficient resources; the matching priority of ordinary parking demand and ordinary parking spaces is the second highest, which guarantees the satisfaction of ordinary parking demand and avoids ordinary demand occupying charging resources to ensure reasonable use of resources; the matching priority of ordinary parking demand and charging parking spaces is the lowest, which only satisfies parking demand and occupies charging parking resource, which may cause waste of charging resources, and is only considered when resources are abundant;

[0009] Step 2: Collect parking space information and parking demand information, and build a model with the maximum profit of the operation manager as the target, the target function including three parts of benefits, costs and penalty costs;

[0010] Step 3: Build time window constraints between different parking demands, time window constraints between parking demand and parking sharing supply time;

[0011] Step 4: Establish constraint relationship between variables according to demand and supply.

[0012] The target function construction in step 2 comprises the following steps:

[0013] Step 21: The target function is shown in formula (1):

[0014] maxf=E1+E2+E3-C a -C b -C p1 -C p2 (1)

[0015] In the formula:

[0016] f is the profit of the operation manager;

[0017] E1 and E3 respectively represent the benefits obtained by matching ordinary parking spaces and matching charging parking spaces for parking demand;

[0018] E2 represents the benefits obtained by mixed demand;

[0019] C a and C b respectively represent the cost of renting ordinary parking spaces and charging parking spaces by the platform;

[0020] C p1 represents the penalty cost caused by the platform refusing to rent parking spaces;

[0021] C p2 represents the penalty cost of sharing platform rejecting the demand;

[0022] Step 22: The income E1 of parking demand matching ordinary parking spaces is calculated by formula (2):

[0023]

[0024] In the formula:

[0025] P1 represents the parking fee paid by the parking demander for ordinary parking spaces, unit: yuan / hour;

[0026] I represents the demand set of parking demanders, parking demand i, i∈I;

[0027] N represents the set of ordinary parking spaces, ordinary parking space n, n∈N;

[0028] represents the length of the idle time window of ordinary parking space n;

[0029] x in is a 0-1 variable, x in =1 indicates that the parking demand i is assigned to the ordinary parking space n, otherwise 0, i∈I, n∈N;

[0030] The length of the idle time window of ordinary parking space n is calculated by formula (3):

[0031]

[0032] In the formula: and respectively represent the start time and end time of the idle time window of the ordinary parking space;

[0033] The income E2 of mixed demand is calculated by formula (4):

[0034]

[0035] In the formula:

[0036] H is the set of mixed demands of charging and parking, each mixed demand h, h∈H;

[0037] S represents the set of charging parking spaces, charging parking space s, s∈S;

[0038] P2 represents the charging fee paid by the mixed parking demander for charging parking spaces, unit: yuan / kWh;

[0039] Qh represents the charging demand of the mixed parking demander, unit: kilowatt;

[0040] xhs is a 0-1 variable, x hs = 1 if mixed parking demand h is assigned to charging parking space s, otherwise 0, h e H, s e S;

[0041] denotes the parking time window length of mixed parking demand h, which is calculated by formula (5):

[0042]

[0043] In the formula: and denote the start time and end time of mixed demanders, respectively;

[0044] The revenue E3 obtained by matching parking demand with charging parking space is calculated by formula (6):

[0045]

[0046] In the formula:

[0047] P3 denotes the parking fee paid by mixed parking demanders for charging parking spaces, unit: yuan / h; wherein: P3 > P1;

[0048] x is is a 0-1 variable, x is = 1 if parking demand i is assigned to charging parking space s, otherwise 0, i e I, s e S;

[0049] denotes the parking time window length of parking demand i, which is calculated by formula (7):

[0050]

[0051] In the formula: and denote the start time and end time of ordinary parking demanders, respectively;

[0052] The cost C a of platform renting ordinary parking spaces is calculated by formula (8):

[0053]

[0054] In the formula:

[0055] C1 denotes the cost of shared platform renting ordinary parking spaces, unit: yuan / h;

[0056] y n is a 0-1 variable, y n = 1 if shared platform rents ordinary parking space n, otherwise 0, n e N;

[0057] The cost C of platform renting a charging parking space b The cost C of platform renting a charging parking space is calculated by formula (9):

[0058]

[0059] In the formula:

[0060] C2 represents the cost of sharing platform renting a charging parking space, unit: yuan / h; wherein: C2 > C1;

[0061] y s is a 0-1 variable, y s = 1 indicates that the sharing platform rents a charging parking space s, otherwise 0, s ∈ S;

[0062] The length of the idle time window of the charging parking space s The length of the idle time window of the charging parking space s is calculated by formula (10):

[0063]

[0064] In the formula: and respectively represent the start time and the end time when the charging parking space is idle;

[0065] The penalty cost C of the sharing platform refusing to rent a parking space p1 The penalty cost C of the sharing platform refusing to rent a parking space is calculated by formula (11):

[0066]

[0067] In the formula:

[0068] θ1 represents the compensation cost paid by the sharing platform to the parking space provider for not renting a normal parking space, unit: yuan / h;

[0069] θ2 represents the compensation cost paid by the sharing platform to the parking space provider for not renting a charging parking space, unit: yuan / h;

[0070] The penalty cost C of the sharing platform refusing demand p2 The penalty cost C of the sharing platform refusing demand is calculated by formula (12):

[0071]

[0072] In the formula:

[0073] τ represents the compensation cost paid by the sharing platform to the normal parking demander, unit: yuan / h;

[0074] γ represents the compensation cost paid by the sharing platform to the mixed parking demander, unit: yuan / h.

[0075] The time window constraints between different parking demands, the time window constraints between the parking demands and the parking sharing supply time in step 3 are constructed by the following steps:

[0076] Step 31: Time window constraints between different parking demands;

[0077] When different parking demands conflict in the parking period, they cannot be allocated to the same parking space; the reservation periods of parking demands i and j allocated to the ordinary parking space should not conflict, where i, j ∈ I, i ≠ j; the reservation periods of parking demands i and e allocated to the charging parking space should not conflict, where i, e ∈ I, i ≠ e; and the reservation periods of mixed parking demands h and f allocated to the charging parking space should not conflict, where h, f ∈ S, h ≠ f; as shown in equations (13)-(15);

[0078]

[0079] In the formula:

[0080] I represents the demand set of parking demanders, parking demand i, i ∈ I;

[0081] S represents the set of charging parking spaces, charging parking space s, s ∈ S;

[0082] And represents the time window length of mixed parking demands h and f;

[0083] represents the parking time window length of parking demands i, j, and e, respectively;

[0084] a ij , a ie , and a hf are 0-1 variables, respectively representing the conflicts between parking demands i, j, e, h, and f; a ij = 1 indicates that the reservation periods of parking demands i and j allocated to the ordinary parking space conflict, otherwise 0, i, j ∈ I, i ≠ j; a ie = 1 indicates that the reservation periods of parking demands i and e allocated to the charging parking space conflict, otherwise 0, i, e ∈ I, i ≠ e; a hf = 1 indicates that the reservation periods of mixed parking demands h and f allocated to the charging parking space conflict, otherwise 0, h, f ∈ S, h ≠ f;

[0085] Step 32: Time window constraints between parking demands and parking sharing supply time;

[0086] The parking space supply user provides part of the idle time of its parking space, and the allocation to the demand of the shared parking lot must comply with the shared time of the parking space supply. The parking time period of the parking demand i should not exceed the shared time period of the ordinary parking space n, the parking time period of the parking demand i should not exceed the shared time period of the charging parking space s, and the parking time period of the mixed parking demand h should not exceed the shared time period of the charging parking space s. The constraints are shown in formulas (16)-(18);

[0087]

[0088] In the formula:

[0089] N represents a set of ordinary parking spaces, ordinary parking space n, n∈N;

[0090] S represents a set of charging parking spaces, charging parking space s, s∈S;

[0091] I represents a set of demand of parking demanders, parking demand i, i∈I;

[0092] H is a set of mixed demands of charging and parking, each mixed demand h, h∈H;

[0093] g in , k is and l hs respectively represent the time window from the relationship of the parking demand and the ordinary parking space, the parking demand and the charging parking space, and the mixed parking demand and the charging parking space;

[0094] represents the time window length of the parking demand i;

[0095] represents the idle time window length of the ordinary parking space n;

[0096] represents the idle time window length of the charging parking space s;

[0097] represents the parking time window length of the mixed parking demand h.

[0098] In step 4, the constraints between variables are established according to the demand and supply, including the following steps:

[0099] Step 41: In the resource matching, the parking demand put forward by the parking demander only has two possible results: acceptance or rejection; once the demand is accepted, a parking space is allocated to it; the parking demand i is allocated to at most one ordinary parking space; the constraint is shown in formula (19);

[0100]

[0101] In the formula:

[0102] N denotes the set of normal parking spaces, normal parking space n, n e N;

[0103] S denotes the set of charging parking spaces, charging parking space s, s e S;

[0104] x in is a 0-1 variable, x in = 1 if parking demand i is assigned to normal parking space n, otherwise 0, i e I, n e N;

[0105] x is is a 0-1 variable, x is = 1 if parking demand i is assigned to charging parking space s, otherwise 0, i e I, s e S;

[0106] Charging demand h is assigned to at most one charging parking space; constraint as shown in equation (20);

[0107]

[0108] In the equation:

[0109] H is the set of mixed demands of charging and parking, each mixed demand h, h e H;

[0110] x hs is a 0-1 variable, x hs = 1 if mixed parking demand h is assigned to charging parking space s, otherwise 0, h e H, s e S;

[0111] Parking time of parking demanders are mutually constrained; if parking demanders are assigned to the same parking space, time conflicts in time are avoided, constraints as shown in equations (21)-(23);

[0112] x in + a ij · x jn ≤ 1, i, j e I; i≠j; n e N (21)

[0113] x is + a ie · x es ≤ 1, i, e e I; i≠e; s e S (22)

[0114] x hs + a hf · x fs ≤ 1, h, f e H; h≠f; s e S (23)

[0115] In the equation:

[0116] x jn is a 0-1 variable, x jn= 1 if parking demand j is assigned to normal parking space n, otherwise 0, j e I, n e N;

[0117] x es is a 0-1 variable, x es = 1 if parking demand e is assigned to charging parking space s, otherwise 0, e e I, s e S;

[0118] x fs is a 0-1 variable, x fs = 1 if hybrid parking demand f is assigned to charging parking space s, otherwise 0, f e H, s e S;

[0119] a ij , a ie and a hf are 0-1 variables, respectively representing the conflict between parking demands i, j, e, h, f;

[0120] The parking time of parking demanders is subject to the shared supply time of parking space providers; once the demanders successfully obtain parking space assignment, their parking time must strictly follow the time window constraints of the parking space, as shown in equations (24)-(26);

[0121] x in · g in = 0, i e I; n e N (24)

[0122] x is · k is = 0, i e I; s e S (25)

[0123] x hs · l hs = 0, h e H; s e S (26)

[0124] In the formula:

[0125] g in , k is and l hs represent the time window dependency relationship between parking demand and normal parking space, between parking demand and charging parking space, and between hybrid parking demand and charging parking space, respectively;

[0126] The occupancy time of all demands assigned to the same parking space should not exceed the total shared duration of the parking space, as shown in constraints (27)-(29);

[0127]

[0128] In the formula:

[0129] represents the time window duration of parking demand i;

[0130] represents the length of the idle time window of the common parking space n;

[0131] represents the length of the idle time window of the charging parking space s;

[0132] represents the length of the parking time window of the mixed parking demand h;

[0133] y s is a 0-1 variable, y s = 1 indicates that the sharing platform rents the charging parking space s, otherwise 0, s ∈ S;

[0134] y n is a 0-1 variable, y n = 1 indicates that the sharing platform rents the common parking space n, otherwise 0, n ∈ N;

[0135] P T-pow represents the total power within the parking lot; h,e-pow represents the charging power occupied by the hth mixed demander, and the constraint is shown in equation (30);

[0136]

[0137] ensures that the power provided by the charging parking space can meet the minimum demand Qh of the mixed demander, and the constraint is shown in equation (31);

[0138]

[0139] P s,T-pow represents the charging power of the sth charging parking space.

[0140] Advantages: Compared with the prior art, the present application has the following advantages

[0141] By constructing a priority matching mechanism based on demand type and parking space attributes, the conflict between parking and charging demand is effectively solved, the resources are reasonably allocated, the mixed demand is preferentially met, and the resource utilization rate in the parking and charging integrated scene is improved. By introducing real-time data acquisition and dynamic allocation model, combined with time window constraint and multi-objective optimization method, the allocation scheme can be dynamically adjusted, and the matching efficiency and system adaptability are significantly improved. At the same time, a target function with the core of maximizing the profit of the operation manager is constructed, which takes into account user experience, resource utilization efficiency and social benefits, and balances the interests and demands of multiple parties. In view of the complexity of the parking and charging mixed scene, the present application provides an optimization method for overall planning of parking and charging resources, which makes up for the defects of insufficient attention to mixed demand and resource matching in existing research, and is suitable for multifunctional parking lot. This method not only relieves the parking problem, but also promotes the efficient use of electric vehicle charging facilities, and has wide popularization and application potential. BRIEF DESCRIPTION OF DRAWINGS

[0142] Figure 1 Flow chart of the method of the present application;

[0143] Figure 2 Schematic diagram of the research object of the method of the present application;

[0144] Figure 3 Result chart. DETAILED DESCRIPTION

[0145] The technical solutions of the present application are described in detail below in combination with the drawings and examples:

[0146] Step 1: Establish a priority matching mechanism between multiple types of parking spaces and parking demand to achieve rational allocation of resources and maximize benefits; among them, the matching priority of mixed demand and charging parking spaces is the highest, the platform obtains parking and charging benefits at the same time, and the mixed demand is satisfied first to avoid potential high-value demand from being unable to be satisfied due to insufficient resources; the matching priority of ordinary parking demand and ordinary parking spaces is the second highest, which guarantees the satisfaction of ordinary parking demand and avoids ordinary demand occupying charging resources to ensure rational use of resources; the matching priority of ordinary parking demand and charging parking spaces is the lowest, which only satisfies parking demand and occupies charging parking space resources, which may cause waste of charging resources, and is only considered when resources are abundant;

[0147] Step 2: Collect parking space information and parking demand information, and the shared platform has 8 parking space information for rent, including 2 charging parking spaces and 6 ordinary parking spaces.

[0148] 18 pieces of parking demand information, including 15 ordinary parking demands and 3 mixed demands of parking and charging. The time table of different parking space rental information is shown in Table 1. The time table of different parking demand information is shown in Table 2.

[0149] Table 1 Time table of different parking space rental information

[0150]

[0151] Table 2 Time table of different parking demand information

[0152]

[0153]

[0154] The operating time of the shared parking platform is 0:00-24:00, the parking unit price of the ordinary parking space is P1=10 yuan / hour, the parking unit price of the charging parking space is P3=15 yuan / hour, the charging unit price of the charging parking space is P2=0.8 yuan / kWh. The cost of renting an ordinary parking space is C1=5 yuan / hour, the cost of renting a charging parking space is C2=8 yuan / hour. If refused, the penalty cost is θ1=0.4 yuan / hour, θ2=0.5 yuan / hour, τ=0.5 yuan / hour, and γ=0.6 yuan / hour. The charging demands of the three charging users are 30 degrees, 30 degrees and 50 degrees respectively.

[0155] For 18 different parking demands, the income, the cost of renting a parking space and the penalty cost of refusing a demand obtained by the shared platform are as shown in Table 3.

[0156] Table 3 Platform income and cost

[0157]

[0158] For 18 different parking demands, in order to meet the demands with high priority, demands 6 and 8 are refused, and demand 10 is refused because there is no shared parking space to meet demand 10, and the profit is 332.15 yuan. Demands 16, 17 and 18 are all met, which makes the charging parking space resources be reasonably used, and prevents the charging resources from being occupied by the shared platform for more benefits.

[0159] The present application is not limited to this single example; any changes, modifications, substitutions, combinations, simplifications made for deviating from the spirit and principles of the present application are equivalent replacement methods, and are all included in the protection scope of the present application.

Claims

1. A priority-driven method for optimizing hybrid shared parking and charging resources, characterized in that, The method includes the following steps: Step 1: Establish a priority matching mechanism between different types of parking spaces and parking demands: the highest priority is given to matching mixed demands with charging parking spaces, the second highest priority is given to matching ordinary parking demands with ordinary parking spaces, and the lowest priority is given to matching ordinary parking demands with charging parking spaces. Step 2: Collect parking space information and parking demand information, and build a model with the goal of maximizing the profit of the operation manager. The objective function includes three parts: revenue, cost and penalty cost. Step 3: Construct time window constraints between different parking demands, and time window constraints between parking demand and parking supply time; Step 4: Establish constraints between variables based on demand and supply; The objective function formula is as follows: maxf=E1+E2+E3-C a -C b -C p1 -C p2 (1) In equation (1), f represents the profit of the operations manager; E1 and E3 represent the revenue obtained from matching parking demand with ordinary parking spaces and charging parking spaces, respectively; E2 represents the revenue obtained from mixed demand; C a and C b These represent the costs of renting regular parking spaces and charging parking spaces on the platform, respectively; C p1 This refers to the penalty costs incurred by the sharing platform for refusing to rent a parking space; C p2 This indicates the penalty costs incurred by sharing platforms for refusing requests; In equation (2), P1 represents the parking fee paid by ordinary parking demanders for ordinary parking spaces, in yuan / hour; I represents the demand set of ordinary parking demanders, i, i∈I; N represents the set of ordinary parking spaces, n, n∈N; x represents the duration of the parking time window for typical parking demand i; in x is a 0-1 variable. in =1 indicates that the ordinary parking demand i is allocated to an ordinary parking space n, otherwise it is 0, i∈I,n∈N; In equation (3), H is the set of mixed demand for charging and parking, with each mixed demand h, h∈H; S represents the set of charging spaces, with charging spaces s, s∈S; P2 represents the charging fee paid by mixed parking demanders for charging spaces, in yuan / kWh; Q h This indicates the charging demand of mixed-use parking users, in kilowatts. x hs x is a 0-1 variable. hs =1 indicates that the mixed parking demand h is allocated to the charging parking space s, otherwise it is 0, h∈H, s∈S; This represents the duration of the parking time window for mixed parking demand (h). In formula (4), P3 represents the parking fee paid by mixed parking demanders for charging parking spaces, in yuan / hour; Where: P3 > P1; x is x is a 0-1 variable. is =1 indicates that parking demand i is allocated to charging parking space s, otherwise it is 0, i∈I, s∈S; In equation (5), C1 represents the cost of renting a regular parking space by the sharing platform, in yuan / hour; y n y is a 0-1 variable. n =1 indicates that the shared platform rents n ordinary parking spaces; otherwise, it is 0, where n∈N; This represents the idle time window duration for a regular parking space n; In equation (6), C2 represents the cost of renting charging spaces by the shared platform, in yuan / hour; where: C2 > C1; y s y is a 0-1 variable. s =1 indicates that the shared platform rents charging spaces s, otherwise it is 0, s∈S; This indicates the duration of the idle time window for charging parking space s; In equation (7), θ1 represents the compensation cost paid by the sharing platform to the parking space provider for not renting ordinary parking spaces, in yuan / hour; θ2 represents the compensation cost paid by the sharing platform to the parking space provider for not renting charging parking spaces, in yuan / hour. In equation (8), τ represents the compensation cost paid by the sharing platform to ordinary parking users, in yuan / hour; γ represents the compensation cost paid by the sharing platform to mixed parking users, in yuan / hour. In equation (9), and These represent the start and end times when a regular parking space becomes available; In equation (10), and These represent the start and end times of mixed demanders; In equation (11), and These represent the start and end times of parking for regular parking users, respectively. In equation (12), and These represent the start and end times when a charging parking space is vacant.

2. The priority-driven method for optimizing hybrid shared parking and charging resources according to claim 1, characterized in that, Step 3 includes the following steps: Step 31: Time window constraints between different parking demands; When different parking needs conflict during parking time periods, they cannot be assigned to the same parking space; When parking demands i and j are allocated to ordinary parking spaces, the reservation time slots should not conflict, where i,j∈I,i≠j; when parking demands i and e are allocated to charging parking spaces, the reservation time slots should not conflict, where i,e∈I,i≠e; and when mixed parking demands h and f are allocated to charging parking spaces, the reservation time slots should not conflict, where h,f∈S,h≠f; as shown in equations (13)-(15); In the formula, and Indicates the duration of the time window for mixed parking demand (h and f); Let i, j, and e represent the duration of the parking time window for ordinary parking demands, respectively. a ij a ie and a hf All are 0-1 variables, representing the conflicts between parking demands i, j, e, h, and f, respectively; a ij =1 indicates that there is a conflict in the reservation time slot when regular parking requests i and j are allocated to regular parking spaces; otherwise, it is 0, where i,j∈I, i≠j; a ie =1 indicates a conflict between the reservation time slots when parking demand i and e are allocated to charging spaces; otherwise, it is 0, where i, e ∈ I, i ≠ e; a hf =1 indicates that the reservation time slots conflict when the mixed parking demand h and f are allocated to charging parking spaces; otherwise, it is 0, h,f∈S, h≠f; Step 32: Time window constraints for parking demand and parking sharing supply; The parking space supply user provides a portion of the free time of their parking space. The demand allocated to the shared parking lot must comply with the shared time provided by the parking space. The parking time of parking demand i should not exceed the shared time of ordinary parking space n. The parking time of parking demand i should not exceed the shared time of charging parking space s. The parking time of mixed parking demand h should not exceed the shared time of charging parking space s. The constraints are shown in equations (16)-(18). In the formula, g in k is and l hs These represent the time window relationships between general parking demand and general parking spaces, general parking demand and charging spaces, and mixed parking demand and charging spaces, respectively.

3. The priority-driven method for optimizing hybrid shared parking and charging resources according to claim 1, characterized in that, Step 4 includes the following steps: Step 41: In resource matching, the parking space request made by the parking user has only two possible outcomes: acceptance or rejection; once the request is accepted, a parking space is allocated to the user. Parking demand i can be allocated to at most one regular parking space; the constraint is shown in equation (19); The charging demand h can be allocated to at most one charging space; the constraint is shown in equation (20); The parking times of parking users are mutually constrained; if parking users are assigned to the same parking space, in order to avoid time conflicts, the constraints are as shown in equations (21)-(23). x in +a ij ·x jn ≤1,i,j∈I;i≠j;n∈N (21) x is +a ie ·x es ≤1,i,e∈I;i≠e;s∈S (22) x hs +a hf ·x fs ≤1,h,f∈H;h≠f;s∈S (23) In the formula, x jn x is a 0-1 variable. jn =1 indicates that the ordinary parking demand j is allocated to an ordinary parking space n, otherwise it is 0, j∈I, n∈N; x es x is a 0-1 variable. es =1 indicates that parking demand e is allocated to charging space s, otherwise it is 0, e∈I, s∈S; x fs x is a 0-1 variable. fs =1 indicates that the mixed parking demand f is allocated to the charging parking space s, otherwise it is 0, f∈H, s∈S; a ij a ie and a hf All are 0-1 variables, representing the conflicts between parking demands i, j, e, h, and f, respectively; The parking time of parking demanders and the shared supply time of parking space providers are mutually constrained; once a demander successfully obtains a parking space allocation, their parking time must strictly follow the time window constraint of that parking space, as shown in equations (24)-(26). x in ·g in =0,i∈I;n∈N (24) x is ·k is =0,i∈I;s∈S (25) x hs ·l hs =0,h∈H;s∈S (26) In the formula, g in k is and l hs These represent the time window relationships between general parking demand and general parking spaces, general parking demand and charging spaces, and mixed parking demand and charging spaces, respectively. The total time that all requests allocated to the same parking space are occupied should not exceed the total shared time of that parking space, as shown in equations (27)-(29); The charging power is less than the total power P in the parking lot. T-pow ;P h,e-pow Let represent the charging power used by the h-th mixed demander, with constraints as shown in equation (30); Ensure that the charging space provides enough power to meet the minimum needs of mixed-use users. h The constraints are shown in equation (31); In the formula, P s,T-pow This represents the charging power of the s-th charging parking space.

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