A method and system for remote check-in and boarding optimization based on space-time resource reconstruction

Abstract

The application discloses a far machine position boarding cooperative optimization method and system based on space-time resource reconstruction, relates to the technical field of far machine position boarding cooperative optimization, and comprises the following steps: through an established boarding bridge configuration model based on peak-hour flight data, the configuration number of a multiplex boarding bridge is calculated, the multiplex boarding bridge is a vertical traffic system using a fixed end of a near machine position boarding bridge, and a mixed flow line of a near machine position waiting room and a far machine position boarding room is formed; a plurality of index parameters affecting the selection of each multiplex boarding bridge are acquired, and each index parameter is standardized; based on each index parameter after the standardization processing, the comprehensive scores of the multiplex boarding bridges are calculated through an entropy weight method, and the multiplex boarding bridge with the highest comprehensive score is determined as the optimal boarding bridge; and the problems that the overall experience of passengers is poor due to long walking distance, low waiting room space design standard and long time consumption of a shuttle in a far machine position hall are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of remote machine position boarding cooperation optimization, more particularly to a remote machine position boarding cooperation optimization method and system based on space-time resource reconstruction. BACKGROUND

[0002] The terminal building remote machine position waiting hall is the core service facility of the remote machine position flight, which provides basic functions such as waiting, verification, and shuttle car riding, and forms a complement to the near machine position waiting hall. When the near machine position is saturated, the remote machine position can divert passenger flow to ensure the orderly operation of the flight, which is a key supplement to improve the overall operation efficiency of the airport. In the passenger flow process system, there are significant differences between the near machine position and the remote machine position. The passengers at the near machine position can walk to the boarding after checking-in and security check. However, the passengers at the remote machine position need to go down to the first floor to wait, take a shuttle to the station, and then walk, which is a long distance, the waiting space design standard is low, and the shuttle takes a long time. Therefore, the overall experience of the passengers at the remote machine position is not good. At the same time, when the remote machine position hall is used as a passenger flow supplement: the overnight machine position demand of the hub airport is large, which leads to the saturation of the near and remote machine positions. 40%-50% of the flights in the morning peak need to start from the remote machine position. However, there is a shortage of boarding gates and corresponding shuttle positions in the remote machine position hall, and some passengers miss the flight due to the long transfer time. When the number of flights parked at the remote machine position in the morning peak exceeds the number of boarding gates at the remote machine position, the near machine position corridor bridge machine position side ladder boarding is temporarily adjusted, which causes inconvenience in management.

[0003] Therefore, the present application is proposed. SUMMARY

[0004] The present application aims to provide a remote machine position boarding cooperation optimization method and system based on space-time resource reconstruction to solve the problems in the background.

[0005] The above technical purpose of the present application is achieved by the following technical scheme:

[0006] In a first aspect, the present application provides a remote machine position boarding cooperation optimization method based on space-time resource reconstruction, which includes the following specific steps:

[0007] The configuration number of the multiplex boarding bridge is calculated by the established boarding bridge configuration model based on the morning peak flight data. The multiplex boarding bridge is a vertical transportation system using the fixed end of the near machine position boarding bridge, and a mixed flow line of the near machine position waiting and the remote machine position boarding is formed.

[0008] A plurality of index parameters affecting the selection of each multiplex boarding bridge are obtained, and each index parameter is standardized.

[0009] Based on each index parameter after the standardization, the comprehensive score of each multiplex boarding bridge is calculated by the entropy weight method, and the multiplex boarding bridge with the highest comprehensive score is determined as the optimal boarding bridge.

[0010] On the basis of the above technical solutions, the application can be further improved as follows.

[0011] Further, the above boarding bridge configuration model is specifically:

[0012] ;

[0013] In the formula, is the configuration number of the multiplex boarding bridge, and when there is a decimal, it needs to be rounded up to an integer; represents the total number of flights during the morning peak, represents the reasonable number of flights running in the near-stand terminal, represents the reasonable number of flights running in the far-stand terminal, represents the single seat service time of the multiplex boarding bridge.

[0014] Further, the index parameters obtained by affecting the selection of each multiplex boarding bridge include at least the boarding bridge occupation interval during the morning peak, the walking distance after passenger security, the far-stand scheduling and shuttle distance, and the total amount of seat resources.

[0015] Further, the above standardization processing of each index parameter is specifically:

[0016] , ;

[0017] , ;

[0018] In the formula, is the standardized processing of the boarding bridge occupation interval during the morning peak, is the boarding bridge occupation interval during the morning peak, and respectively represent the minimum value and the maximum value of the boarding bridge occupation interval during the morning peak, is the standardized processing of the walking distance after passenger security, represents the walking distance after passenger security, and respectively represent the minimum value and the maximum value of the walking distance after passenger security, is the standardized processing of the far-stand scheduling and shuttle distance, is the far-stand scheduling and shuttle distance, and respectively represent the minimum value and the maximum value of the far-stand scheduling and shuttle distance, is the total amount of seat resources, represents the total amount of seat resources, and the total amount of seat resources is equal to the existing seats plus the expandable seats, and respectively represent the minimum value and the maximum value of the total amount of seat resources.

[0019] Further, the comprehensive scores of the respective multiplexing boarding bridges calculated by the entropy weight method are specifically as follows:

[0020] The proportion of each multiplexing boarding bridge to each index parameter is calculated.

[0021] The information entropy of each index parameter is calculated based on the proportion of each multiplexing boarding bridge.

[0022] The difference coefficient of each index parameter is calculated based on the information entropy of each index parameter.

[0023] The weight of each index parameter is calculated based on the difference coefficient of each index parameter.

[0024] The comprehensive score of each multiplexing boarding bridge is calculated based on the weight of each index parameter.

[0025] Further, the proportion of each multiplexing boarding bridge is specifically as follows: ; wherein, represents the proportion of the i th index parameter and the j th multiplexing boarding bridge, is the value of the i th index parameter of the j th multiplexing boarding bridge, represents the number of multiplexing boarding bridges;

[0026] The information entropy of each index parameter is specifically as follows: ; wherein, is the information entropy of the i th index parameter; The difference coefficient of each index parameter is specifically as follows:

[0027] ; wherein, is the difference coefficient of the i th index parameter;

[0028] The weight of each index parameter is specifically as follows: ; wherein, is the weight of the i th index parameter, is the number of index parameters;

[0029] The comprehensive score of each multiplexing boarding bridge is specifically as follows: ; wherein, is the comprehensive score of the i th multiplexing boarding bridge.

[0030] ​​​​​​​​Further, the method further comprises:

[0031] When the comprehensive scores of the two or more multiplex boarding bridges are the same, the multiplex boarding bridge corresponding to the maximum value of the normalized early peak boarding bridge occupation interval is determined as the optimal boarding bridge.

[0032] In a second aspect, the application provides a remote boarding coordination optimization system based on space-time resource reconstruction, which is applied to the remote boarding coordination optimization method based on space-time resource reconstruction in any one of the first aspect, and comprises:

[0033] The configuration quantity calculation module is configured to calculate the configuration quantity of the multiplex boarding bridge by using the boarding bridge configuration model based on the early peak flight data, and the multiplex boarding bridge is a mixed flow line formed by using the vertical traffic system of the fixed end of the near-stand boarding bridge.

[0034] The index parameter acquisition module is configured to acquire a plurality of index parameters affecting the selection of each multiplex boarding bridge, and perform standardization processing on each index parameter.

[0035] The comprehensive score calculation module is configured to calculate the comprehensive score of each multiplex boarding bridge based on each index parameter after standardization processing by using the entropy weight method, and determine the multiplex boarding bridge with the highest comprehensive score as the optimal boarding bridge.

[0036] In a third aspect, the application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method of any one of the first aspect when executing the computer program.

[0037] In a fourth aspect, the application provides a non-transitory computer readable storage medium, which stores computer instructions, and the computer instructions make the computer execute the method of any one of the first aspect.

[0038] Compared with the prior art, the application has at least the following beneficial effects:

[0039] Space service level is improved: the early peak remote stand passenger terminal restores the comfort level of per capita area, runs smoothly, and reduces the difficulty of scheduling; passenger experience is optimized: the walking distance of remote stand passengers is shortened, the walking time is more ideal, the ferry time is shorter, the waiting space is more comfortable, the hardware facility condition is better, and the complaint rate of remote stand passengers is reduced; equipment utilization is optimized: the utilization rate of near-stand boarding space, boarding gate and boarding bridge resources is improved; the transformation cost is reduced: through resource reuse, the construction area of the transformed remote stand passenger terminal is reduced, and the influence on other functions of the first floor building is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0040] The accompanying drawings, which are included to provide a further understanding of the embodiments of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings:

[0041] Figure 1 A method flow chart of the optimization method in the embodiments of the application;

[0042] Figure 2 A connection schematic diagram of the optimization system in the embodiments of the application;

[0043] Figure 3 A connection schematic diagram of the electronic device in the embodiments of the application. DETAILED DESCRIPTION

[0044] In order to make the objects, technical solutions and advantages of the embodiments of the application clearer, the technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are some but not all of the embodiments of the application. The components of the embodiments of the application described and shown in the drawings can be arranged and designed in various different configurations.

[0045] Therefore, the following detailed description of the embodiments of the application provided in the drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the application.

[0046] It should be noted that: similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0047] In the description of the embodiments of the application, "a plurality of" represents at least 2.

[0048] Embodiment 1: In order to solve the problems that the overall experience of passengers at the remote stand is poor due to long walking distance, low design standard of waiting space, long time consumption of shuttle, and the like, the embodiment provides a remote stand boarding collaborative optimization method based on space-time resource reconstruction, as shown in Figure 1 The method comprises the following specific steps:

[0049] S1, the configuration number of the multiplex boarding bridge is calculated by the established boarding bridge configuration model based on the early peak flight data. The multiplex boarding bridge is a vertical transportation system using the fixed end of the near stand boarding bridge, and a mixed flow line of near stand waiting and remote stand boarding is formed.

[0050] Wherein, the vertical traffic system (stairs or elevator) of the fixed end of the near-gate boarding bridge can be used to build a mixed flow line of "near-gate waiting - far-gate boarding"; since the fixed end of the original boarding bridge is usually a fire standard and located semi-outdoor, the design standard of the near-gate boarding bridge fixed end can be optimized in this embodiment to make the passenger travel experience more comfortable; configuration: stair slope ≤ 30°, step width 300-310mm, width ≥ 1.2m, elevator load ≥ 3T (accommodate more than 40 people), add the enclosure system to set the stairs indoors to improve the comfort of the body, and set the double parking space shuttle bus stop area near the first floor exit.

[0051] Optionally, the boarding bridge configuration model described above is specifically:

[0052] ;

[0053] In the formula, is the configuration number of the multiplex boarding bridge, and when there is a decimal, it needs to be rounded up to an integer; represents the total number of flights in the morning peak, represents the reasonable number of flights running in the near-gate waiting hall, represents the reasonable number of flights running in the far-gate waiting hall, represents the single seat service time of the multiplex boarding bridge, unit: hour, for example, 0.45-0.5 hours are needed to serve 1 flight.

[0054] S2, obtain a plurality of index parameters affecting the selection of each multiplex boarding bridge, and standardize each index parameter.

[0055] Wherein, the index parameters affecting the selection of each multiplex boarding bridge obtained above include at least boarding bridge occupation interval in the morning peak, passenger security post-walking distance, far-gate dispatching and shuttle distance, and total seat resource; the boarding bridge occupation interval in the morning peak is in minutes, which can be recorded as T, the larger the interval, the lower the dispatching conflict risk; the passenger security post-walking distance is in meters, which can be recorded as D1; the passenger security post-walking distance is in meters, which can be recorded as D1; the unit of the total seat resource is pieces, C total = existing seats + expandable potential.

[0056] For the early morning peak boarding bridge occupation interval, the larger the interval, the lower the risk of scheduling conflict, the better the performance; for the passenger security walking distance, the shorter the distance, the better the passenger experience, the better the performance; for the far stand scheduling and transfer distance, the shorter the distance, the higher the efficiency of the alternative solution, the better the performance; for the total amount of seat resources, the larger the total amount, the higher the passenger comfort, the better the performance; for the passenger security walking distance and the far stand scheduling and transfer distance, when standardized, the two index parameters are converted from "the smaller the better" to "the larger the better" positive index based on the consistency of the other two index parameters; then the above standardization of each index parameter is performed, specifically:

[0057] , ;

[0058] , ;

[0059] In the formula, is the standardized early morning peak boarding bridge occupation interval, is the early morning peak boarding bridge occupation interval, and respectively represent the minimum and maximum values of the early morning peak boarding bridge occupation interval, is the standardized passenger security walking distance, represents the passenger security walking distance, and respectively represent the minimum and maximum values of the passenger security walking distance, is the standardized far stand scheduling and transfer distance, is the far stand scheduling and transfer distance, and respectively represent the minimum and maximum values of the far stand scheduling and transfer distance, is the total amount of seat resources, represents the total amount of seat resources, which is equal to the existing seats plus the expandable seats, and respectively represent the minimum and maximum values of the total amount of seat resources.

[0060] S3, based on the standardized index parameters, the comprehensive scores of each multiplex boarding bridge are calculated by entropy weight method, and the multiplex boarding bridge with the highest comprehensive score is determined as the optimal boarding bridge.

[0061] The preferred process of multiplexing the boarding bridge prioritizes the resource scheduling flexibility during the morning peak period, while considering passenger experience and facility capacity, and selects the optimal multiplexing boarding bridge. The entropy weight method is used to determine the index weight of the multiplexing boarding bridge, which is objective and data-driven. It calculates the weight based on the objective volatility of the index data, avoids subjective bias, and can automatically highlight the indicators with large differences (such as the early morning peak interval T), which meets the demand of prioritizing scheduling flexibility. At the same time, it can balance multi-dimensional indicators and adapt to dynamic changes in the airport scene. When the data distribution changes, the weight is automatically updated without manual adjustment, enhancing the scientificity and adaptability of decision-making.

[0062] Optionally, the comprehensive score of each multiplexing boarding bridge calculated by the entropy weight method is as follows:

[0063] The proportion of each multiplexing boarding bridge for each index parameter is calculated, wherein the proportion of each multiplexing boarding bridge is specifically: ; in the formula, represents the proportion of the th index parameter and the th multiplexing boarding bridge, is the value of the th index parameter of the th multiplexing boarding bridge, represents the number of configurations of the multiplexing boarding bridge.

[0064] Further, the information entropy of each index parameter is calculated based on the proportion of each multiplexing boarding bridge, wherein the information entropy of each index parameter is specifically: ; in the formula, is the information entropy of the th index parameter.

[0065] Further, the difference coefficient of each index parameter is calculated based on the information entropy of each index parameter, wherein the difference coefficient of each index parameter is specifically: ; in the formula, is the difference coefficient of the th index parameter.

[0066] Further, the weight of each index parameter is calculated by the difference coefficient of each index parameter, wherein the weight of each index parameter is specifically: ; in the formula, is the weight of the th index parameter, is the number of index parameters.

[0067] Further, the comprehensive score of each multiplexing boarding bridge is calculated based on the weight of each index parameter, wherein the comprehensive score of each multiplexing boarding bridge is specifically: ; in the formula, the comprehensive score of the first multiplex boarding bridge.

[0068] Optionally, the method can further include:

[0069] S4, when the comprehensive scores of two or more multiplex boarding bridges are the same, determining the multiplex boarding bridge corresponding to the maximum value of the early peak boarding bridge occupation interval after standardization as the optimal boarding bridge.

[0070] Specifically, in the specific implementation, first, import the flight data, calculate the number of multiplex boarding bridges required and allocate the near-gate boarding bridge resources, and the passenger comfort can be improved according to the 'near-gate boarding bridge multiplexing module'; second, guide the early peak passengers to the near-gate waiting hall, and inform them in advance that they need to take the shuttle bus to start, and after the boarding of the flight, the passengers pass through the near-gate boarding gate, enter the elevator and stairs through the boarding bridge, and take the shuttle bus; finally, the double-car position circular operation is performed to the far-gate, and the running strategy needs to be dynamically adjusted while continuously paying attention to the early peak far-gate waiting area operation and the near-gate boarding bridge occupation state.

[0071] Among them, through the implementation scheme in this embodiment, 1. Space service level is improved: the early peak far-gate waiting hall recovers the comfortable level of per capita area, runs smoothly, and reduces the difficulty of scheduling; 2. Passenger experience optimization: the walking distance of far-gate passengers is shortened, the walking time is more ideal, the shuttle time is shorter, the waiting space is more comfortable, the hardware facility condition is better, and the far-gate passenger complaint rate is reduced; 3. Optimization of equipment utilization rate: improve the utilization rate of near-gate waiting space, boarding gate and boarding bridge resources; 4. Reduce the cost of transformation: through resource reuse, the construction area of the far-gate waiting hall can be reduced, and the influence on other functions of the first floor building can be reduced.

[0072] Embodiment 2: The application provides a far-gate boarding coordination optimization system based on space-time resource reconstruction, which is applied to the far-gate boarding coordination optimization method based on space-time resource reconstruction in embodiment 1, as shown in Figure 2 , can include:

[0073] The configuration quantity calculation module is configured to calculate the configuration quantity of the multiplex boarding bridge by establishing the boarding bridge configuration model based on the early peak flight data, and the multiplex boarding bridge is a near-gate boarding bridge fixed end vertical transportation system, and a mixed flow line of near-gate waiting-far-gate boarding is formed;

[0074] The index parameter acquisition module is configured to acquire a plurality of index parameters affecting the selection of each multiplex boarding bridge, and to standardize each index parameter;

[0075] The comprehensive score calculation module is configured to calculate a comprehensive score of each multiplexing boarding bridge based on the standardized index parameters by using an entropy weight method, and determine the multiplexing boarding bridge with the highest comprehensive score as the optimal boarding bridge.

[0076] Embodiment 3: The embodiment of the application provides an electronic device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method of embodiment 1 when executing the computer program. Figure 3 As shown in the figure, the electronic device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method of embodiment 1 when executing the computer program.

[0077] Embodiment 4: The embodiment of the application provides a non-transitory computer readable storage medium, which stores computer instructions, and the computer instructions make a computer execute the method of embodiment 1.

[0078] Those skilled in the art should understand that the embodiments of the application can be provided as a method, a system, or a computer program product. Therefore, the application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the application can adopt a computer program product in the form of being 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 codes.

[0079] The application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks. Figure 1 The devices that implement the functions specified in one or more flows and / or blocks.

[0080] These computer program instructions can also be stored in a computer readable storage medium that can guide the computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer readable storage medium produce a manufactured product including instruction devices that implement the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks. Figure 1 The devices that implement the functions specified in one or more flows and / or blocks.

[0081] These computer program instructions can also be loaded into a computer or other programmable data processing device, so that a series of operational steps are performed on the computer or other programmable data processing device to generate a computer implemented process, so that the instructions executed on the computer or other programmable data processing device provide a process for implementing the functions specified in the flowchart Figure 1 one flow or multiple flows and / or the functions specified in the block Figure 1 one block or multiple blocks.

[0082] Those of ordinary skill in the art can understand that all or part of the steps of the above-mentioned facts and methods can be completed by programs instructing relevant hardware, and the programs involved or the programs mentioned can be stored in a computer-readable storage medium. When the program is executed, the following steps are included: at this time, the corresponding method steps are derived, and the storage medium can be ROM / RAM, a magnetic disc, an optical disc, etc.

[0083] The above specific embodiments further illustrate the purposes, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the protection scope of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A collaborative optimization method for remote gate boarding based on spatiotemporal resource reconstruction, characterized in that, The specific steps include the following: By establishing a boarding bridge configuration model based on morning peak flight data, the number of reusable boarding bridges is calculated. The reusable boarding bridge is a hybrid flow line formed by utilizing the vertical transportation system at the fixed end of the near-gate boarding bridge to form a near-gate waiting-remote-gate boarding flow. Multiple indicator parameters affecting the selection of each of the reusable boarding bridges are obtained, and each of the indicator parameters is standardized. Among them, the multiple indicator parameters affecting the selection of each of the reusable boarding bridges include at least the boarding bridge occupancy interval during the morning peak, the walking distance after passenger security check, the remote gate scheduling and shuttle distance, and the total number of seat resources. Based on the standardized index parameters, the comprehensive score of each reused boarding bridge is calculated by the entropy weight method, and the reused boarding bridge with the highest comprehensive score is determined as the optimal boarding bridge. The boarding bridge configuration model is as follows: ； In the formula, To ensure the number of reusable boarding bridges is configured, any decimals must be rounded up to the nearest integer. This indicates the total number of flights during the morning rush hour. This indicates the reasonable number of flights operating in the near-gate waiting area. This indicates the number of flights that can be reasonably operated from the remote gate waiting area. This indicates the service time per seat for a reused boarding bridge.

2. The remote gate boarding collaborative optimization method based on spatiotemporal resource reconstruction according to claim 1, characterized in that, The standardization process for each of the aforementioned index parameters specifically involves: ， ； , ； In the formula, Standardized morning rush hour boarding bridge occupancy intervals. The boarding bridge is occupied during the morning rush hour. and These represent the minimum and maximum intervals between boarding bridge occupancy during the morning rush hour, respectively. This refers to the standardized walking distance for passengers after security checks. This indicates the walking distance for passengers after security check. and These represent the minimum and maximum walking distances for passengers after security checks, respectively. This refers to the standardized remote gate scheduling and shuttle distance. For remote parking position scheduling and shuttle distance, and These represent the minimum and maximum values ​​for remote gate scheduling and shuttle distance, respectively. For the total number of seats, This represents the total number of seating resources, which equals the sum of existing seats and expandable seats. and These represent the minimum and maximum values ​​of the total number of seats, respectively.

3. The remote gate boarding collaborative optimization method based on spatiotemporal resource reconstruction according to claim 1, characterized in that, The comprehensive score of each reused boarding bridge is calculated using the entropy weight method, specifically as follows: Calculate the proportion of each reused boarding bridge for each indicator parameter; Based on the proportion of each reused boarding bridge, the information entropy of each indicator parameter is calculated; Based on the information entropy of each indicator parameter, calculate the difference coefficient of each indicator parameter; The weight of each indicator parameter is calculated by using the difference coefficient of each indicator parameter. Based on the weights of each indicator parameter, the overall score of each reused boarding bridge is calculated.

4. The remote gate boarding collaborative optimization method based on spatiotemporal resource reconstruction according to claim 3, characterized in that, The specific proportions of each reusable boarding bridge are as follows: In the formula, Indicates the first The first indicator parameter, the first The proportion of reusable boarding bridges, For the first The first reusable boarding bridge The value of each indicator parameter, Indicates the number of reused boarding bridges configured; The information entropy of each indicator parameter is specifically as follows: In the formula, For the first Information entropy of each indicator parameter; The difference coefficients of each indicator parameter are as follows: In the formula, For the first The coefficient of difference of each indicator parameter; The weights of each indicator parameter are as follows: In the formula, For the first The weights of each indicator parameter, The number of indicator parameters; The overall score for each reused boarding bridge is as follows: In the formula, For the first The overall score for each reusable boarding bridge.

5. The remote gate boarding collaborative optimization method based on spatiotemporal resource reconstruction according to claim 1, characterized in that, The method further includes: When two or more shared boarding bridges have the same overall score, the shared boarding bridge corresponding to the maximum value of the morning peak boarding bridge occupancy interval after standardization is determined as the optimal boarding bridge.

6. A remote gate boarding collaborative optimization system based on spatiotemporal resource reconstruction, characterized in that, include: The configuration quantity calculation module is used to calculate the configuration quantity of reused boarding bridges based on the established boarding bridge configuration model based on morning peak flight data. The reused boarding bridges are a hybrid flow line formed by utilizing the vertical transportation system at the fixed end of the near-gate boarding bridge, creating a near-gate waiting area and a remote-gate boarding area. The boarding bridge configuration model is specifically as follows: ； In the formula, To ensure the number of reusable boarding bridges is configured, any decimals must be rounded up to the nearest integer. This indicates the total number of flights during the morning rush hour. This indicates the reasonable number of flights operating in the near-gate waiting area. This indicates the number of flights that can be reasonably operated from the remote gate waiting area. This indicates the service time per seat for a reused boarding bridge; The indicator parameter acquisition module is used to acquire multiple indicator parameters that affect the selection of each of the reusable boarding bridges, and to standardize each of the indicator parameters; the multiple indicator parameters that affect the selection of each of the reusable boarding bridges include at least the boarding bridge occupancy interval during the morning peak, the walking distance after passenger security check, the remote gate scheduling and shuttle distance, and the total number of seat resources. The comprehensive score calculation module is used to calculate the comprehensive score of each reused boarding bridge based on the standardized index parameters using the entropy weight method, and to determine the reused boarding bridge with the highest comprehensive score as the optimal boarding bridge.

7. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method of any one of claims 1-5.

8. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions that cause the computer to perform the method of any one of claims 1-5.

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