Site selection method, computing device and readable storage medium

Abstract

The invention discloses a site selection method, a computing device and a computer readable storage medium, and the method comprises the steps: obtaining first site selection data submitted by a user, the first site selection data comprising a site selection position of at least one energy site in a preset region; evaluating the first site selection data based on a preset evaluation factor, wherein the preset evaluation factor comprises at least one of submission frequency, trajectory popularity, power supply, traffic flow and land cost; and determining the site selection position of the energy site according to the evaluation result of the first site selection data. Therefore, according to the technical scheme of the invention, multi-dimensional factor evaluation is performed on the site selection data submitted by the user, so that the user demand and the actual use condition can be more comprehensively known, and a more scientific and accurate site selection decision can be made.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a site selection method, a computing device, and a computer-readable storage medium. Background Art

[0002] With the rapid development of the electric vehicle industry, the demand for battery swap stations, as key infrastructure for electric vehicle energy replenishment, is growing. However, the traditional method of selecting battery swap stations mainly relies on offline surveys, which is not only time-consuming and costly, but also difficult to fully and accurately reflect market demand and drivers' actual preferences. Summary of the invention

[0003] The purpose of this application is to provide a site selection method, a computing device and a computer-readable storage medium, which can more comprehensively understand user needs and actual usage by performing a multi-dimensional factor evaluation on the site selection data submitted by the user, thereby making more scientific and accurate site selection decisions.

[0004] To achieve the above objectives:

[0005] The embodiment of the present application provides a site selection method, comprising: obtaining first site selection data submitted by a user, wherein the first site selection data comprises a site selection location of at least one energy site in a preset area;

[0006] Evaluate the first site selection data based on preset evaluation factors, wherein the preset evaluation factors include at least one of submission frequency, trajectory heat, power supply, traffic flow, and land cost;

[0007] The site selection location of the energy site is determined according to the evaluation result of the first site selection data.

[0008] In one embodiment, after obtaining the first site selection data submitted by the user, the method includes:

[0009] Performing point aggregation analysis on the first site selection data to obtain a point aggregation area;

[0010] Obtaining a trajectory heat map according to the user's historical travel routes;

[0011] The first site selection data is filtered based on the point aggregation area and / or the trajectory heat map.

[0012] In one embodiment, the quantitative evaluation of the first site selection data based on a preset evaluation factor includes at least one of the following:

[0013] Obtaining a first evaluation result of the first site selection data according to the submission frequency of the first site selection data;

[0014] Obtaining a second evaluation result of the first location selection data according to the number of times the user traveled and the length of stay in the historical travel route;

[0015] Obtaining a third evaluation result of the first site selection data according to the distance between the first site selection data and the power supply facility, and / or the residual load ratio of the power grid of the power supply facility;

[0016] Obtaining a fourth evaluation result of the first site selection data according to the distance between the first site selection data and the main road, and / or the statistical flow of the main road;

[0017] A fifth evaluation result of the first site selection data is obtained based on the land cost and / or land suitability level of the area where the first site selection data is located.

[0018] In one embodiment, the method further comprises:

[0019] Perform a weighted average on at least two of the first to fifth evaluation results to obtain an evaluation result of the first site selection data.

[0020] In one embodiment, before obtaining the first site selection data submitted by the user, the method includes:

[0021] A site selection map is generated, where the site selection map is used to create, modify or delete the first site selection data.

[0022] In one embodiment, the method further comprises:

[0023] A user community is created, the user community providing the users with communication, voting and / or feedback functions for energy site siting.

[0024] In one embodiment, before obtaining the first site selection data submitted by the user, the method further includes:

[0025] Generate second site selection data according to the frequently visited places of the user, and push the second site selection data to the user.

[0026] In one embodiment, after determining the site selection location of the energy site according to the evaluation result of the first site selection data, the method further includes:

[0027] An evaluation report is generated, wherein the evaluation report includes at least one of a score of each candidate position, an analysis of strengths and weaknesses, and a reason for recommendation.

[0028] An embodiment of the present application also provides a computing device, including: a processor and a memory storing a computer program, and when the processor runs the computer program, the steps of the site selection method described in any one of the above items are implemented.

[0029] An embodiment of the present application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of the site selection method described in any one of the above items are implemented.

[0030] The site selection method, computing device and computer-readable storage medium provided in the embodiment of the present application include: obtaining the first site selection data submitted by the user, the first site selection data includes the site selection location of at least one energy site in a preset area; evaluating the first site selection data based on preset evaluation factors, the preset evaluation factors include submission frequency, trajectory heat, power supply, traffic flow, land cost, environmental impact and sustainable energy at least one; determining the site selection location of the energy site according to the evaluation result of the first site selection data. In this way, the technical solution of the present application can more comprehensively understand the user's needs and actual usage by conducting a multi-dimensional factor evaluation on the site selection data submitted by the user, so as to make a more scientific and accurate site selection decision. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 A flowchart of a site selection method provided in an embodiment of the present application.

[0033] Figure 2 The overall workflow diagram of the site selection method for this application example.

[0034] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0035] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0036] It should be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0037] It should be understood that, although the terms first, second, third, etc. may be used to describe various information in this article, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this article, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "at the time of..." or "when..." or "in response to determination". Furthermore, as used in this article, the singular forms "one", "one" and "the" are intended to also include plural forms, unless there is an opposite indication in the context. It should be further understood that the terms "comprising", "including" indicate that there are described features, steps, operations, elements, components, projects, kinds, and / or groups, but do not exclude the existence, occurrence or addition of one or more other features, steps, operations, elements, components, projects, kinds, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Thus, “A, B, or C” or “A, B and / or C” means “any of the following: A; B; C; A and B; A and C; B and C; A, B, and C.” An exception to this definition will occur only when a combination of elements, functions, steps, or operations are inherently mutually exclusive in some manner.

[0038] It should be understood that, although the various steps in the flowchart in the embodiment of the present application are displayed in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and it can be performed in other orders. Moreover, at least a portion of the steps in the figure may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and their execution order is not necessarily performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0039] It should be noted that in this article, step codes such as S1 and S2 are used for the purpose of expressing the corresponding content more clearly and concisely, and do not constitute a substantial limitation on the order. When implementing the step, those skilled in the art may execute S2 first and then S1, etc., but these should all be within the scope of protection of this application.

[0040] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0041] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0042] Traditional site selection methods rely on offline surveys and traffic flow analysis, which are not only time-consuming and labor-intensive, but also complex in data collection and processing, making it difficult to quickly and accurately determine the best location for a battery swap station. In addition, traditional site selection methods ignore the voices and needs of drivers as the direct beneficiaries of battery swap services.

[0043] In order to solve the problems of the prior art, an embodiment of the present application provides a site selection method. The site selection method provided in the embodiment of the present application can be executed by a computing device provided in the embodiment of the present application, and the computing device can be implemented in software and / or hardware. The computer device can be any one of a terminal device, an independent physical server, a server cluster, a cloud, a distributed system, an Internet of Things, or an Internet of Vehicles, and technicians in this field can set it according to actual needs.

[0044] See also Figure 1 , a site selection method provided in this embodiment includes the following steps S1 to S3:

[0045] Step S1: Acquire first site selection data submitted by a user, where the first site selection data includes the site selection location of at least one energy site in a preset area.

[0046] In one embodiment, the user may submit the first site selection data through an application or an online form. The first site selection data is data related to the construction of energy sites, including the site selection location of at least one energy site in a preset area. The preset area may be a city, district, county, or other specific area. The user provides one or more suggested locations of energy sites within the preset area. Energy sites may refer to facilities such as battery swap stations, gas stations, charging stations, and gas stations. In this way, by collecting the site selection data of energy sites online and introducing users (such as drivers) to directly participate in site selection, the interactivity between users and site selection decisions is enhanced, and the user's satisfaction and acceptability of the site selection results are improved.

[0047] In one embodiment, before obtaining the first site selection data submitted by the user, the site selection method includes:

[0048] A site selection map is generated, where the site selection map is used to create, modify or delete the first site selection data.

[0049] In one embodiment, the user can submit the first site selection data through the site selection map. Specifically, the user's real-time location is displayed on the site selection map, and the user can drag, search and submit the geographical location information of the energy site to be built on the site selection map to form the first site selection data. In this way, the process of submitting the site selection data can be visualized.

[0050] The site selection method of the embodiment of the present application can quickly collect a large amount of user demand data at different times and locations through the online submission function of real-time positioning and site selection data, greatly shortening the offline research cycle. Real-time positioning and site selection data directly reflect the actual needs and usage scenarios of drivers. Combined with map services and real-time road conditions, it can identify the best candidate points for energy sites and ensure that the construction location is closer to market demand.

[0051] In one embodiment, the site selection method further includes:

[0052] Create a user community that provides users with communication, voting and / or feedback capabilities regarding energy site selection.

[0053] In one embodiment, a dedicated online forum or community can be established, or a community can be created using existing social media platforms (such as WeChat, QQ groups, Facebook groups), or a mobile application or web application can be developed to integrate communication, voting and feedback functions.

[0054] In one embodiment, the user community can provide a discussion platform for users to discuss within the community and share opinions, ideas and suggestions on energy site selection. Users can also obtain the latest information about the site selection process, such as project progress, important notices, etc. through the community.

[0055] In one embodiment, users can express their support for different site selection options by voting. The voting results can be used as a reference for site selection decisions, helping planners understand public preferences, and the public voting process increases the transparency of the site selection process. Users can also submit specific feedback on the site selection options, including reasons for support, reasons for opposition, or suggestions for improvement.

[0056] In one embodiment, the user community may allow users to share or partially share their first site selection data, so that different users can view and refer to each other's website building suggestions, thereby enhancing the interactivity and transparency of the site selection process.

[0057] In one embodiment, before obtaining the first site selection data submitted by the user, the site selection method further includes:

[0058] Generate second site selection data based on the user's frequently visited locations, and push the second site selection data to the user.

[0059] In one embodiment, the second site selection data is a recommended point for an energy site automatically generated based on the user's frequently visited locations. The recommended points for energy sites can be combined with places that drivers frequently visit (such as gas stations, repair shops, restaurants, etc.) to optimize the site selection of energy sites. At the same time, based on the driver's historical behavior data, their driving preferences (such as preference for highways or ordinary roads, and preference for busy or quiet areas) are analyzed to recommend personalized site selection plans for different groups.

[0060] In one embodiment, the location data of the user is collected over a period of time. The collected location data is analyzed to identify the places frequently visited by the user. A clustering algorithm (such as K-means) or a density-based spatial clustering algorithm (such as DBSCAN) can be used for identification. Based on the user's frequently visited places, some potential energy site locations are selected. These locations can be close to the user's frequently visited places in order to provide convenient services. In addition, other site selection factors (such as transportation convenience, infrastructure, environmental impact, etc.) can be combined to comprehensively evaluate the potential sites and generate second site selection data.

[0061] The generated second site selection data is structured, including but not limited to site location, recommendation reasons, expected benefits, etc. These potential sites are marked on the map, and descriptions and scores are provided for users to refer to during the site selection process.

[0062] In one embodiment, users may be grouped according to their frequently visited locations and related attributes (such as occupation, driving habits, etc.) to determine the target user group for push notifications, and personalized second location selection data push content may be customized for each user group or each user.

[0063] In this way, the site selection data is combined with high-frequency use places to ensure that the energy site not only meets the power demand, but also facilitates users to park, rest, and repair. At the same time, by analyzing the user's historical behavior and preferences, a customized site selection plan can be generated to improve user experience and usage frequency, making site selection decisions more accurate, avoiding blind construction, and improving resource utilization.

[0064] In one embodiment, after obtaining the first site selection data submitted by the user, the site selection method includes:

[0065] Performing point aggregation analysis on the first site selection data to obtain a point aggregation area;

[0066] Get a trajectory heat map based on the user's historical travel routes;

[0067] The first site selection data is filtered based on the point aggregation area and / or trajectory heat map.

[0068] In one embodiment, the first site selection data is displayed on a map, and a point aggregation algorithm (such as DBSCAN, K-means, or HDBSCAN) is used to identify high-density areas, each of which represents a high-density site selection point group. The parameters of the algorithm, such as radius, minimum number of points, etc., can be adjusted according to actual conditions to obtain a reasonable aggregation result.

[0069] In one embodiment, the user's historical travel route data can be obtained from the user's mobile application or vehicle-mounted device, and the user's travel route data can be converted into trajectory segments. The trajectory data is processed using a heat map generation algorithm (such as kernel density estimation KDE) to generate a heat map. The heat map shows the user's travel frequency in different areas. The heat map can be displayed on a map, and the color depth indicates the high and low travel frequency.

[0070] In one embodiment, the first site selection data is screened based on the point aggregation area and / or the trajectory heat map. The site selection points located in the high-density point aggregation area can be selected, or the site selection points located in the high-frequency travel area (the area with darker color in the heat map) can be selected. Of course, the point aggregation area and the trajectory heat map can also be superimposed together for comprehensive analysis. For example, different weights are assigned to the point aggregation area and the trajectory heat map so that the relative importance of the two can be considered in the screening process.

[0071] In this way, geospatial analysis is performed on the site selection data submitted by users, and point aggregation technology is used to integrate dense site selection data into multiple hot spots. In addition, the heat map generated by the user's historical driving trajectory data can visualize the density of user activities in the area, thereby accurately identifying the geographical locations where energy site demand is most concentrated. The combination of point aggregation analysis and heat map not only speeds up the site selection process, but also enhances the accuracy of the site selection results.

[0072] Step S2: Evaluate the first site selection data based on preset evaluation factors, where the preset evaluation factors include at least one of submission frequency, trajectory heat, power supply, traffic flow and land cost.

[0073] In one embodiment, evaluating the first site selection data based on preset evaluation factors means that after determining the first site selection data, a series of pre-set standards or indicators are used to measure the suitability of these locations to ensure that the final selected location can not only meet the basic functional requirements, but also comprehensively consider various factors to achieve the optimal layout.

[0074] Specifically, submission frequency refers to the number of users' suggestions for specific locations in the first site selection data as potential sites. A high submission frequency indicates that there is a large demand for services in the area or that it is generally popular among users. Trajectory heat is the result of analyzing the user's historical driving trajectory data, which shows the density of vehicle activities in a certain area. Areas with high trajectory heat mean that there are more vehicles passing through, which may be ideal locations for setting up energy sites. Power supply is used to examine the power grid conditions and power supply stability near the candidate site to ensure that the energy site can obtain reliable power support. Traffic flow is used to analyze the total volume and distribution characteristics of traffic passing through a certain place in the road network. Higher traffic flow usually corresponds to a greater demand for energy supply. Land cost is used to analyze the difference in land prices in different locations. Choosing a more cost-effective location helps control the total investment of the project.

[0075] By comprehensively considering one or more of the above factors, we can more comprehensively evaluate the advantages and disadvantages of each candidate address and make more scientific and reasonable decisions.

[0076] In one embodiment, the first site selection data is quantitatively evaluated based on a preset evaluation factor, including at least one of the following:

[0077] Obtaining a first evaluation result of the first site selection data according to the submission frequency of the first site selection data;

[0078] Obtaining a second evaluation result of the first location selection data according to the number of times the user traveled and the length of stay in the user's historical travel route;

[0079] Obtaining a third evaluation result of the first site selection data according to the distance between the first site selection data and the power supply facility, and / or the residual load ratio of the power grid of the power supply facility;

[0080] Obtaining a fourth evaluation result of the first site selection data according to the distance between the first site selection data and the main road, and / or the statistical flow of the main road;

[0081] A fifth evaluation result of the first site selection data is obtained according to the land cost and / or land suitability level of the area where the first site selection data is located.

[0082] In one embodiment, the needs and behaviors of users are quantitatively analyzed to evaluate the demand heat of site selection data. The submission frequency of different users for specific site selection points can be included in the score according to a certain weight, and the submission heat score = submission frequency * weight 1 is obtained.

[0083] In one embodiment, based on the user's historical driving trajectory data, the frequency of the driving route and the duration of stay at certain locations are analyzed to determine the battery replacement demand in the area. By calculating the number of driving passes and the duration of stay, and assigning corresponding weights, the trajectory heat score = number of driving passes * duration of stay * weight 2 is obtained.

[0084] In one embodiment, the site selection point is evaluated based on the power supply situation, which includes but is not limited to the total power supply capacity and load situation of the power grid. Real-time power supply information is obtained by connecting to the power grid data interface. The closer to the power supply facility, the more stable the power supply and the lower the construction cost of the energy site. Therefore, the regional power supply situation can be divided into high, medium and low levels, and higher scores are given to areas with high power supply capacity in the scoring system. Specifically, the power supply facility distance score is calculated using the formula, power supply facility distance score = 1 / distance * weight 3.

[0085] In one embodiment, the grid load condition of the preset area for site selection is evaluated to avoid selecting areas with insufficient power supply. The grid load condition score can be calculated using the formula: load condition score = grid residual load ratio * weight 4.

[0086] In one embodiment, the site selection is evaluated based on traffic flow evaluation. The road condition data for a period of time is obtained. The distance of the energy site from the main traffic artery will affect the convenience of users. The closer the site is to the main road, the higher the score. Therefore, the main road distance score = 1 / distance*weight 5 can be obtained.

[0087] In one embodiment, through analysis of historical traffic flow data, areas with large and stable traffic flow are more advantageous and convenient for rapid access to energy sites, so it can be obtained that the traffic flow score = traffic statistics value * weight 6.

[0088] In one embodiment, the site selection is evaluated based on the land cost. The land price and use type data of the candidate area can be obtained by accessing a public land price database. Then, each candidate plot is scored to ensure the optimization of land cost. Land cost includes but is not limited to land market price, rental cost and use nature attribute of the plot. Among them, the use nature data of the plot refers to the commercial or industrial use of the land, which affects the difficulty of construction. The score is scored according to the purchase or rental cost of the land, and the lower the land cost, the higher the score. Therefore, it can be concluded that the land cost score = 1 / land cost * weight 7.

[0089] In one implementation, the commercial or industrial use of the land is considered to affect the ease of construction, and the use nature score = land suitability grade * weight 8 can be obtained.

[0090] In one embodiment, the site selection method further includes:

[0091] At least two of the first to fifth evaluation results are weighted averaged to obtain an evaluation result of the first site selection data.

[0092] In one embodiment, based on the evaluation results of the above factors, a weighted average is performed to obtain the total score of the site selection point:

[0093] Total score = (submission heat score × weight 1 + trajectory heat score × weight 2 + power supply score × weight 3 + traffic flow score × weight 4 + land cost score × weight 5 + usage nature score × weight 6) / total weight

[0094] In one embodiment, each weight is adjusted according to the actual situation to ensure that the optimal weight distribution meets the strategic needs of the enterprise. For example, some areas may pay more attention to traffic flow, while other areas may pay more attention to land cost.

[0095] Assuming that a company is selecting a site for a battery swap station in a specific area, the following factors and their weights are considered:

[0096] Submission heat score: weight 1 = 0.2

[0097] Track heat score: weight 2 = 0.2

[0098] Power supply score: weight 3 = 0.2

[0099] Traffic flow score: weight 4 = 0.2

[0100] Land cost score: weight 5 = 0.1

[0101] Usage rating: Weight 6 = 0.1

[0102] Assume that the scores are:

[0103] Submission heat score = 80

[0104] Track heat score = 70

[0105] Power supply score = 90

[0106] Traffic flow score = 85

[0107] Land cost score = 75

[0108] Usage rating = 80

[0109] The total score is calculated as follows:

[0110] Total score = (80×0.2+70×0.2+90×0.2+85×0.2+75×0.1+80×0.1) / 1 = 80.5

[0111] Through the above method, multiple factors can be systematically evaluated quantitatively and combined with weight allocation to generate a comprehensive score, thereby helping decision makers select the optimal location for battery swap stations. This not only improves the scientificity and accuracy of the site selection process, but also ensures that the site selection results meet the strategic needs of the enterprise.

[0112] Step S3: Determine the site selection location of the energy site according to the evaluation result of the first site selection data.

[0113] In one embodiment, a comprehensive score is calculated for each candidate location, reflecting its performance in each evaluation dimension, and the candidate locations with the highest scores are selected in order as the final site selection location of the energy site.

[0114] In one embodiment, an evaluation report is generated, which includes information such as the score of each candidate location, analysis of advantages and disadvantages, and reasons for recommendation. Based on the evaluation report, combined with the company's strategic goals, capital budget and other factors, the final site selection decision is made.

[0115] In one implementation, a field survey is conducted in demand hotspot areas to verify the accuracy of the data collected and analyzed in the previous stage.

[0116] The site selection method provided in this embodiment obtains the first site selection data submitted by the user, and the first site selection data includes the site selection location of at least one energy site in a preset area; the first site selection data is evaluated based on preset evaluation factors, and the preset evaluation factors include at least one of submission frequency, trajectory heat, power supply, traffic flow, land cost, environmental impact and sustainable energy; according to the evaluation result of the first site selection data, the site selection location of the energy site is determined. In this way, the technical solution of the present application can more comprehensively understand the user's needs and actual usage by conducting a multi-dimensional factor evaluation on the site selection data submitted by the user, so as to make a more scientific and accurate site selection decision.

[0117] See also Figure 2 Based on the same inventive concept as the above embodiments, a system for applying the site selection method is exemplified below to explain the above embodiments in detail through a specific application scenario:

[0118] This system mainly includes data acquisition module, data analysis module, data evaluation module and site selection decision. The data acquisition module is responsible for collecting vehicle positioning information, station construction information submitted by drivers, urban traffic flow data, power supply data, land cost and other data; the data analysis module processes and analyzes the collected data and outputs the big data model of the corresponding city; the data evaluation module generates an evaluation report based on the big data model; the site selection decision module makes decisions on the site selection of the battery swap station.

[0119] (1) The battery-swap vehicle will report the latitude and longitude information of the driving trajectory (including latitude and longitude, direction, altitude) and other information to the data analysis background in real time.

[0120] (2) The driver user enters the wish list page in the APP used to submit site selection data, drags the map or searches to determine the final location, generates a site selection wish list, and submits it to the management backend.

[0121] (3) Using big data analysis technology, we mine and analyze massive amounts of historical driving trajectory data to identify hot spots and driving patterns of drivers. Then, we aggregate and analyze the station building clue data provided by drivers in step (2) to further assist in site selection decisions. Finally, we conduct a comprehensive assessment based on factors such as urban traffic flow, power supply, and land costs to determine the location of the battery swap station.

[0122] (4) Conduct field visits to demand hotspots to verify the accuracy of the data, evaluate factors such as transportation convenience, power supply stability, and land costs for each candidate location, comprehensively consider all factors, and score them, and finally output a candidate location evaluation report.

[0123] (5) Make the final site selection decision based on the evaluation report and in combination with company strategy, financial budget and other factors.

[0124] In summary, this system realizes the full process management from real-time vehicle trajectory data collection to comprehensive site selection decision through four modules: data collection, analysis, evaluation and decision-making. The system uses big data technology to mine driver activity hotspots and driving patterns, and combines the wish list data submitted by drivers for aggregate analysis, supplemented by comprehensive evaluation of multi-dimensional factors such as urban traffic conditions, power supply, and land costs, and finally generates a detailed candidate location evaluation report to achieve reasonable battery swap station site selection decisions.

[0125] Based on the same inventive concept as the above embodiments, the present application embodiment provides a computing device, such as Figure 3 As shown, the device includes: a processor 310 and a memory 311 storing a computer program; wherein, Figure 3The processor 310 shown in the figure is not used to indicate that the number of the processor 310 is one, but is only used to indicate the positional relationship of the processor 310 relative to other devices. In actual applications, the number of the processor 310 may be one or more; similarly, Figure 3 The memory 311 shown in the figure has the same meaning, that is, it is only used to refer to the position relationship of the memory 311 relative to other devices. In practical applications, the number of memories 311 can be one or more. When the processor 310 runs the computer program, the address selection method applied to the above device is implemented, for example Figure 1 The step S1 shown is: performing three-dimensional rendering on the two-dimensional map data according to the first rendering rule to generate intermediate three-dimensional map data, and the intermediate three-dimensional map data is in an editable format; step S2: when the first quality inspection result corresponding to the intermediate three-dimensional map data indicates a rendering abnormality, performing editing control on the intermediate three-dimensional map data according to a preset repair strategy to update the intermediate three-dimensional map data; step S3: performing three-dimensional rendering on the updated intermediate three-dimensional map data according to the second rendering rule to obtain the target three-dimensional map data.

[0126] The device may also include: at least one network interface 312. The various components in the device are coupled together via a bus system 313. It is understood that the bus system 313 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 313 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 3 Various buses are labeled as bus system 313.

[0127] The memory 311 may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. The nonvolatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disk, or a compact disc read-only memory (CD-ROM); the magnetic surface memory may be a disk memory or a tape memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and direct RAM bus random access memory (DRRAM, Direct Rambus Random Access Memory).The memory 311 described in the embodiments of the present application is intended to include but is not limited to these and any other suitable types of memories.

[0128] The memory 311 in the embodiment of the present application is used to store various types of data to support the operation of the device. Examples of these data include: any computer program for operating on the device, such as an operating system and an application program, etc. Among them, the operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application program may include various applications, such as a media player (MediaPlayer), a browser (Browser), etc., for implementing various application services. Here, the program implementing the method of the embodiment of the present application may be included in the application program.

[0129] The computing device of this embodiment can compile and render the two-dimensional map data into editable intermediate three-dimensional map data, so that when the intermediate three-dimensional map data has a rendering anomaly, the editing control of the intermediate three-dimensional map data can be realized, and the abnormal link causing the rendering anomaly corresponding to the intermediate three-dimensional map data can be quickly located and repaired in a visual manner, so that the intermediate three-dimensional map data after the rendering anomaly is repaired can be obtained, and then three-dimensional rendering can be performed again based on the intermediate three-dimensional map data, so that the target three-dimensional map data for users with excellent quality can be obtained. Therefore, in the process of generating three-dimensional map data, the computing device of this embodiment can realize the rapid location and repair of the abnormal link causing the rendering anomaly, ensuring that the final three-dimensional map data has excellent quality.

[0130] Based on the same inventive concept as the above-mentioned embodiment, this embodiment further provides a computer-readable storage medium, in which a computer program is stored. The computer-readable storage medium may be a ferromagnetic random access memory (FRAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); it may also be various devices including one or any combination of the above memories, such as a mobile phone, a computer, a tablet device, a personal digital assistant, etc. When the computer program stored in the computer-readable storage medium is executed by the processor, the above method is implemented. For the specific steps implemented when the computer program is executed by the processor, please refer to Figure 1 The description of the illustrated embodiment will not be repeated here.

[0131] Based on the same inventive concept as the aforementioned embodiment, this embodiment further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the site selection method described above are implemented.

[0132] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0133] In this document, the terms "comprises," "comprising," or any other variations thereof, are intended to cover a non-exclusive inclusion of elements other than those listed and may also include additional elements not expressly listed.

[0134] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A site selection method, characterized in that: include: Acquire first site selection data submitted by a user, wherein the first site selection data includes a site selection location of at least one energy site in a preset area; Evaluate the first site selection data based on preset evaluation factors, wherein the preset evaluation factors include at least one of submission frequency, trajectory heat, power supply, traffic flow, and land cost; The site selection location of the energy site is determined according to the evaluation result of the first site selection data.

2. The site selection method according to claim 1, characterized in that: After obtaining the first site selection data submitted by the user, the method includes: Performing point aggregation analysis on the first site selection data to obtain a point aggregation area; Obtaining a trajectory heat map according to the user's historical travel routes; The first site selection data is filtered based on the point aggregation area and / or the trajectory heat map.

3. The method according to claim 1, characterized in that The quantitative evaluation of the first site selection data based on a preset evaluation factor includes at least one of the following: Obtaining a first evaluation result of the first site selection data according to the submission frequency of the first site selection data; Obtaining a second evaluation result of the first location selection data according to the number of times the user traveled and the length of stay in the historical travel route; Obtaining a third evaluation result of the first site selection data according to the distance between the first site selection data and the power supply facility, and / or the residual load ratio of the power grid of the power supply facility; Obtaining a fourth evaluation result of the first site selection data according to the distance between the first site selection data and the main road, and / or the statistical flow of the main road; A fifth evaluation result of the first site selection data is obtained based on the land cost and / or land suitability level of the area where the first site selection data is located.

4. The site selection method according to claim 3, characterized in that: The method further comprises: Perform a weighted average on at least two of the first to fifth evaluation results to obtain an evaluation result of the first site selection data.

5. The site selection method according to claim 1, characterized in that: Before obtaining the first site selection data submitted by the user, the method includes: A site selection map is generated, where the site selection map is used to create, modify or delete the first site selection data.

6. The site selection method according to claim 1, characterized in that: The method further comprises: A user community is created, the user community providing the users with communication, voting and / or feedback functions for energy site siting.

7. The site selection method according to claim 1, characterized in that: Before obtaining the first site selection data submitted by the user, the method further includes: Generate second site selection data according to the frequently visited places of the user, and push the second site selection data to the user.

8. The site selection method according to claim 1, characterized in that: After determining the site selection location of the energy site according to the evaluation result of the first site selection data, the method further includes: An evaluation report is generated, wherein the evaluation report includes at least one of a score of each candidate position, an analysis of strengths and weaknesses, and a reason for recommendation.

9. A computing device, characterized in that include: A processor and a memory storing a computer program, wherein when the processor runs the computer program, the steps of the site selection method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a processor, the steps of the site selection method according to any one of claims 1 to 8 are implemented.

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