Community life circle division method, device, computer equipment and medium

Abstract

The present invention discloses a method, device, equipment and medium for dividing community life circles, including: collecting various historical characteristic data of community life circles, and building a simulation environment based on the historical characteristic data; defining the activity range of the community life circle based on the home domain theory according to the simulation environment and historical characteristic data, and obtaining the activity definition range; dividing the internal structure of the life circle through time-space demand thermal simulation according to the simulation environment and historical characteristic data, and obtaining the target internal structure; performing data analysis based on the activity definition range and the target internal structure to obtain the life circle division result. The accuracy of the community life circle division is improved, which is conducive to improving the space utilization rate and better guiding the renewal, optimization and construction of urban community space.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method, device, computer equipment and medium for dividing a community living circle. Background Art

[0002] In recent years, many cities have built community life circles, but most of the construction methods are often based on spatial entity division for the sake of universal implementation. In essence, they are still a continuation of the implementation method of traditional residential facilities configuration, and pay insufficient attention to the actual needs and spatiotemporal behavior of residents in the circle. At the same time, some scholars have divided community life circles from the perspective of residents' spatiotemporal behavior, based on individual behavior survey GPS data, mobile phone signaling data to identify residents' activity space, and analyze their behavioral needs. This method can better meet the basic requirements of community life circles to "adapt to local conditions" and respond to residents' needs, but there are also problems such as high data acquisition cost and large division granularity. Therefore, it is urgent to find a new method that is convenient and popularizable for the division of community life circles. Summary of the invention

[0003] The embodiments of the present invention provide a method, apparatus, computer equipment and storage medium for dividing community life circles, so as to improve the accuracy of dividing community life circles.

[0004] In order to solve the above technical problems, the embodiment of the present application provides a method for dividing a community living circle, including:

[0005] Collect various historical characteristic data of the community life circle, and build a simulation environment based on the historical characteristic data;

[0006] According to the simulation environment and the historical characteristic data, the activity scope of the community life circle is defined based on the home domain theory to obtain the activity definition scope;

[0007] According to the simulation environment and the historical characteristic data, the internal structure of the living circle is divided through a time-space demand thermal simulation to obtain a target internal structure;

[0008] Data analysis is performed based on the activity definition scope and the target internal structure to obtain the life circle division result.

[0009] Optionally, the collecting of various historical characteristic data of the community life circle and building a simulation environment based on the historical characteristic data includes:

[0010] According to various historical characteristic data, the behavior subject parameters are configured, and the behavior subject parameters include the basic attribute parameters of the behavior subject, the walking speed and diameter parameters of the behavior subject, the facility selection parameters of the behavior subject, the travel chain composition parameters and the travel chain generation probability parameters;

[0011] Create a simulation environment;

[0012] Based on the subject parameter configuration and the simulation environment, the travel chain logic of the behavior subject is generated, wherein the travel chain logic of the behavior subject includes a simple travel chain logic flow, a complex travel chain logic flow and a comprehensive logic flow.

[0013] Optionally, the activity scope of the community life circle is defined based on the home domain theory according to the simulation environment and the historical feature data, and the activity definition scope includes:

[0014] In the process of simulating the travel behavior of each residential group based on various historical characteristic data, the cumulative value of the number of entities passing through the unit pixel shows the thermal value, and the thermal map of residents' activities is drawn;

[0015] Convert the bitmap raster data representing the heat map of residents' activities into vector data to obtain the heat range;

[0016] Based on the thermal range, the home range theory is used to define the activity range and obtain the activity definition range.

[0017] Optionally, dividing the internal structure of the living circle through time-space demand thermal simulation according to the simulation environment and the historical characteristic data to obtain the target internal structure includes:

[0018] Quantifying the thermal value based on the resident activity thermal map to obtain a target thermal value for each unit;

[0019] Calculate the grid mean of all target thermal values ​​covered by a single fishing net to obtain the thermal value of a single spatial unit as the corresponding community residents' travel activity demand characteristics, where the thermal value corresponding to each desire unit is the result of the summary of individual behavioral activities of a community resident;

[0020] Based on the travel activity demand characteristics of all community residents, the internal structure of the living circle is divided to obtain the target internal structure.

[0021] Optionally, after performing data analysis based on the activity definition range and the target internal structure to obtain a life circle division result, the method further includes:

[0022] Compare the internal structure division results of different community life circles to determine the structure of different levels of demand circles;

[0023] Determine the facilities that will be affected based on the structure of different levels of demand circles;

[0024] Optimize deployment according to the impact facilities.

[0025] In order to solve the above technical problems, the embodiment of the present application further provides a device for dividing a community life circle, including:

[0026] The environment building module is used to collect various historical characteristic data of the community life circle and build a simulation environment based on the historical characteristic data;

[0027] The scope definition module is used to define the activity scope of the community life circle based on the simulation environment and historical characteristic data based on the home domain theory to obtain the activity definition scope;

[0028] The structural division module is used to divide the internal structure of the living circle through the time-space demand thermal simulation according to the simulation environment and historical characteristic data to obtain the target internal structure;

[0029] The result determination module is used to perform data analysis based on the activity definition scope and the target internal structure to obtain the life circle division results.

[0030] Optionally, the environment building module includes:

[0031] The parameter configuration unit is used to configure the behavior subject parameters according to various historical characteristic data. The behavior subject parameters include the basic attribute parameters of the behavior subject, the walking speed and diameter parameters of the behavior subject, the facility selection parameters of the behavior subject, the travel chain composition parameters and the travel chain generation probability parameters;

[0032] An environmental simulation unit, used to create a simulated environment;

[0033] The logic generation unit is used to generate the travel chain logic of the behavioral subject based on the subject parameter configuration and simulation environment, wherein the travel chain logic of the behavioral subject includes a simple travel chain logic flow, a complex travel chain logic flow and a comprehensive logic flow.

[0034] Optionally, the scoping module comprises:

[0035] The heat map drawing unit is used to display the heat value of the accumulated value of the number of entities passing through the unit pixel in the process of simulating the travel behavior of each residential group according to various historical characteristic data, and draw the heat map of residents' activities;

[0036] A vectorization unit is used to convert the bitmap raster data representing the thermal map of residents' activities into vector data to obtain the thermal range;

[0037] The scope definition unit is used to define the activity scope based on the thermal range and adopt the home range theory to obtain the activity definition scope.

[0038] Optionally, the structure division module includes:

[0039] A thermal value calculation unit is used to quantify the thermal value based on the resident activity thermal map to obtain the target thermal value of each unit;

[0040] The individual demand evaluation unit is used to calculate the grid mean of all target thermal values ​​covered by a single fishing net, and obtain the thermal value of a single spatial unit as the corresponding community residents' travel activity demand characteristics, where the thermal value corresponding to each desire unit is the result of the summary of individual behavior activities of a community resident;

[0041] The structural division unit is used to divide the internal structure of the living circle based on the travel activity demand characteristics of all community residents to obtain the target internal structure.

[0042] Optionally, the community life circle division device further includes:

[0043] The comparison module is used to compare the internal structure division results of different community life circles and determine the structure of different levels of demand circles;

[0044] The facility determination module is used to determine the influencing facilities based on the structure of different levels of demand circles;

[0045] Deployment module for optimizing deployment based on influencing facilities.

[0046] In order to solve the above technical problems, an embodiment of the present application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for dividing community living circles when executing the computer program.

[0047] In order to solve the above technical problems, an embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the above-mentioned method for dividing community living circles.

[0048] The method, device, computer equipment and storage medium for dividing community life circles provided by the embodiments of the present invention collect various historical characteristic data of the community life circle, and build a simulation environment based on the historical characteristic data; define the activity range of the community life circle based on the home domain theory according to the simulation environment and historical characteristic data, and obtain the activity definition range; divide the internal structure of the life circle through time-space demand thermal simulation according to the simulation environment and historical characteristic data, and obtain the target internal structure; perform data analysis based on the activity definition range and the target internal structure to obtain the life circle division result. The accuracy of the community life circle division is improved, and the urban community space renewal optimization and construction are better guided, which is conducive to improving the space utilization rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0050] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0051] Figure 2 It is a flow chart of an embodiment of the method for dividing the community life circle of the present application;

[0052] Figure 3 This is a flow chart of simulation of travel behavior of residents in community life circle in one embodiment of the method for dividing community life circle of the present application;

[0053] Figure 4 It is a flowchart of a schematic diagram of a simulated environment range of an embodiment of a method for dividing a community living circle of the present application;

[0054] Figure 5 It is a flowchart of a simulation environment constructed by AnyLogic platform in one embodiment of the community life circle division method of the present application;

[0055] Figure 6 It is an embodiment of the community life circle division method of the present application, a residential group travel activity simulation heat map simulation map;

[0056] Figure 7 This is a schematic diagram of identifying activity points of residential groups in one embodiment of the method for dividing community life circles of the present application;

[0057] Figure 8 This is a schematic diagram of the distribution of heat values ​​of travel activities of residential groups in one embodiment of the method for dividing community life circles of the present application;

[0058] Fig. 9 This is a schematic diagram of the superposition result of the activity range of the community life circle of an embodiment of the method for dividing the community life circle of the present application;

[0059] Fig.10 This is a schematic diagram of the superposition result of the internal structure of the community life circle of an embodiment of the community life circle division method of the present application;

[0060] Fig.11 It is a structural schematic diagram of an embodiment of a device for dividing a community living circle according to the present application;

[0061] Fig.12 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0063] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] See also Figure 1 ,like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0066] Users can use terminal devices 101 , 102 , 103 to interact with server 105 via network 104 to receive or send messages, etc.

[0067] Terminal devices 101, 102, 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, desktop computers, etc.

[0068] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0069] It should be noted that the method for dividing the community life circle provided in the embodiment of the present application is executed by a server, and accordingly, the device for dividing the community life circle is set in the server.

[0070] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. The terminal devices 101, 102, 103 in the embodiment of the present application may specifically correspond to application systems in actual production.

[0071] See also Figure 2 , Figure 2 A method for dividing a community life circle provided by an embodiment of the present invention is shown. The method is applied in Figure 1 The server in is used as an example to illustrate the details as follows:

[0072] S201: Collect various historical characteristic data of the community life circle, and build a simulation environment based on the historical characteristic data.

[0073] Specifically, the simulation construction based on the subject modeling technology needs to configure the appropriate simulation platform, subject, process and basic assumptions according to the characteristics of the embodiment. This embodiment belongs to the low-density activity simulation in the micro-behavior simulation, so the basic construction of the simulation needs to take into account the complexity and specificity of the embodiment object.

[0074] Simulation platform. Currently, simulation platforms for micro-behaviors are gradually maturing. Considering the simulation complexity of this embodiment and the ease of use in the promotion process, this embodiment selects AnyLogic as the simulation platform. The platform uses a social force model that conforms to the logic of human individual activities. At the same time, the platform has a rich pedestrian database. During operation, it can modify individual walking characteristics to more accurately simulate the differentiated continuous micro-behaviors of community residents. The platform can output indicator data such as the number of people flow and heat in the simulation environment. Based on the data, visual data tables can also be synchronously exported for further analysis by the implementer.

[0075] The simulation subject and process, the simulation subject of this embodiment mainly includes two parts: the environment subject and the behavior subject. The environment subject refers to the built environment elements in the model construction, and in this embodiment, it mainly includes three parts: residence, travel path, and target facilities. The behavior subject refers to the intelligent agent that completes the configuration task, and in this embodiment, it represents the community residents within the scope of the embodiment. The specific simulation process is as follows Figure 3 shown.

[0076] Basic assumptions of simulation. This embodiment takes into account the complexity, diversity and contingency of community residents' travel. It is necessary to establish relevant assumptions to make the model universal. First, it is assumed that community residents are in good physical condition, conscious and self-care, and can reach the target location at a constant speed based on their own will, and there is no stagnation or reverse during the walking process; second, community residents are familiar with the distribution and paths of facilities around their residence, and can choose suitable target points and paths according to their own needs, without detours or getting lost; third, there are no obstacles in the existing pedestrian roads, community residents can move unimpeded, and there is no path congestion or oversaturation; finally, since the service quality of facilities of the same type and service level is difficult to quantify, residents have different evaluation criteria for facilities, and the service quality of facilities is not a decisive factor, it is assumed that the service quality between facilities of the same type and level has no effect on residents' choices, and community residents will choose the facilities closest to them for activities.

[0077] In a specific optional implementation, collecting various historical characteristic data of the community life circle, and building a simulation environment based on the historical characteristic data includes:

[0078] According to various historical characteristic data, the behavior subject parameters are configured. The behavior subject parameters include the basic attribute parameters of the behavior subject, the walking speed and diameter parameters of the behavior subject, the facility selection parameters of the behavior subject, the travel chain composition parameters and the travel chain generation probability parameters;

[0079] Create a simulation environment;

[0080] Based on the subject parameter configuration and simulation environment, the travel chain logic of the behavioral subject is generated, where the travel chain logic of the behavioral subject includes simple travel chain logic flow, complex travel chain logic flow and comprehensive logic flow.

[0081] In a specific case, the simulation object is Lianhua Street, which covers an area of ​​about 777.4 hectares, starting from Caitian Road in the east, Xiangmei Road in the west, Shennan Avenue in the south, and Beihuan Avenue in the north. The simulation environment takes into account the cross-street activities of community residents at the edge of the street, so the edge of Lianhua Street is extended outward by one block as the potential travel range boundary of community residents, such as Figure 4 shown.

[0082] Furthermore, based on the collected built environment data, the simulation environment can be easily drawn on the AnyLogic platform. The drawing content mainly includes the range of residential areas and their entrances and exits, travel routes, the range of target facilities and their entrances and exits, other buildings and obstacles, etc. The simulation environment is constructed based on the three types of spatial markers in the AnyLogic platform pedestrian library: polygon nodes (Node), target lines (TargetLine) and walls (Wall). The simulation environment built on the AnyLogic platform is as follows Figure 5 shown.

[0083] Furthermore, in the AnyLogic platform, the subject will be simulated based on the social force model. According to the relevant theories of the social force model, the travel behavior of community residents can be decomposed into five parts in chronological order: "Agent generation", "Agent generation of demand", "Demand-driven travel", "reaching the target facility" and "Agent return". Relying on the relevant modules in the AnyLogic platform pedestrian library and connecting them in series according to the actual travel logic, a complete simulation process of the subject's activities can be constructed.

[0084] Among them, according to the above travel logic, the simulation process of the simple travel chain will be connected using the following modules. In the "Agent Generation" stage, the pedSource control is used to generate the Agent according to the preset travel time, quantity and age structure; in the "Agent Generates Demand" stage, the pedSelectOutput control is used to output the input community resident Agent from different target ports according to the preset travel purpose ratio; in the "Demand Driven Travel" stage, the pedGoTo control is used to simulate the travel process of community residents according to the preset travel rules, so that the Agent reaches the target facility point; in the "Arrival at Target Facility" stage, the pedWait control is used to make the Agent stay in the target facility area for a preset time; in the "Agent Return" stage, the pedSink control is used to remove the Agent from the simulation environment. Linking the above controls can realize a complete simple travel chain simulation.

[0085] Among them, the complex travel chain simulation process needs to be built on the basis of the simple travel chain. When the simple travel chain completes the "arrival at the target facility stage", the pedSelectOutput control is used again to classify the input community resident Agents again. According to the preset ratio, the input Agents are divided into two categories: ending the trip and going to the next target facility point. The latter will link other target facility points and execute the three steps of "demand-driven travel", "arrival at the target facility" and "agent return" again, thus forming a complex travel chain simulation process.

[0086] In this embodiment, the comprehensive logic flow is based on two travel modes: simple and complex travel chains.

[0087] Based on the analysis and research on the travel behavior characteristics of community residents in the previous section, the relevant basic parameters of the computer model are configured.

[0088] (1) Basic attributes of the subject. To simulate the subject's activities based on the AnyLogic platform, the Pedsource control in the pedestrian library needs to be used to generate the simulated subject. In the process, three parameters, namely quantity, gender, and age, need to be introduced. First, the number of subjects generated in each community is calculated based on the building area of ​​each community at 27 m2 / person, and then the number of subjects in each age group is calculated based on the seventh census data; secondly, the gender parameter refers to the gender composition data of Futian Street in the seventh census, and the gender ratio is set to 107.86% (female = 100%); the age parameter refers to the survey data and is set to a triangular distribution, that is, triangular (min, max, mode), with teenagers triangular (4, 18, 8), adults triangular (19, 58, 29), and the elderly triangular (60, 84, 63).

[0089] (2) Walking speed and diameter of the subject: Considering the differences in walking ability among different age groups, the walking speeds of teenagers (uniform (0.6, 1.2) m / s), adults (0.6, 1.38) m / s, and the elderly (0.4, 0.98) m / s were used. Since adult males are generally taller than females, the walking speeds of teenagers, male adults, and female adults were set to triangular (30, 60, 45), triangular (40, 70, 60), and triangular (35, 60, 50) according to the triangular distribution.

[0090] (3) Travel chain. Combined with the above-mentioned concepts of community life circle, this study only considers the community travel behavior of each community resident around the residence, so commuting, visiting relatives and friends, etc. are not considered. In addition, since the activity venues of dining behavior are evenly distributed and dense, this type of behavior has little impact on the simulated division of the community life circle, so it is not considered. Combined with the above-mentioned summary of community residents' travel characteristics, the main behaviors simulated in this study include six types of travel, including going to school, leisure activities, shopping, escorting family members, seeing a doctor, and doing business. According to the analysis results of the travel chain characteristics of community residents, the probability of each travel chain is shown in Table 1.

[0091] Table 1 Probability of main travel chains in different age groups

[0092]

[0093]

[0094] Among them, h represents residence, S represents educational facilities, L represents leisure facilities, P represents shopping facilities, H represents medical facilities, and O represents administrative facilities.

[0095] (4) Facility selection by the subject. Considering that the service level of facilities will affect residents’ choice of target facilities, in the process of subject parameter configuration, leisure facilities are divided into two levels: community parks and urban parks, and medical facilities are divided into community health centers and general hospitals. In terms of selection logic, it is set that when there are two levels of leisure and medical facilities within a 15-minute reach of the subject, the subject can randomly choose to go to any facility to complete the travel needs.

[0096] S202: According to the simulation environment and historical characteristic data, the activity scope of the community life circle is defined based on the home domain theory to obtain the activity definition scope.

[0097] Specifically, based on the AnyLogic platform and the analysis of the travel characteristics of community residents in the previous chapter, the travel behavior of each residential group in Lianhua Street is simulated. The platform can display the thermal value based on the cumulative value of the number of entities passing through the unit pixel. Since in the simulation logic, the behavior subject will only go to the facility point represented by the target line to carry out activities, ignoring the potential possibility of the behavior subject's activities around the facility point, the thermal contour only represents the preliminary outline of the community residents' activity range, such as Figure 6 shown.

[0098] Since the AnyLogic platform cannot directly export thermal range data, it is necessary to use the ArcGIS platform to convert the bitmap raster data into vector data. The specific steps are as follows: First, georeference the imported thermal raster data and attach geographic coordinates to the bitmap data; second, use the raster calculator tool to filter the vector ranges of different density zones according to the values ​​of the three RGB bands in the bitmap data; finally, refer to the actual resident population of the residential group, use the Create Random Point tool to generate community resident activity points in different density zones according to the heat map density index, such as Figure 7 shown.

[0099] Furthermore, the Home Range Tool plug-in developed on the ArcGIS platform based on the "home range" theory can identify the potential activity range of residents according to the activity points, thereby defining the community life circle boundary of the residential group. In the "home range" theory, there are two methods for identifying the spatial range of individual activity: the minimum convex polygon method and the kernel density estimation method. This study chose to use the KDE method in the HRT plug-in, which is more in line with the activity rules of community residents. This method can calculate the potential activity range based on the spatial distribution probability density of residents' travel activity points. In the process of generating the potential activity range of residents through the HRT plug-in, it is necessary to focus on the setting of the Isopleths (isoline) parameter. The isoline refers to the proportion of activity points contained in the line to the total points, that is, the 98 isoline represents 98% of all points contained in the circle. Considering the occasional outliers in residents' travel activities, this study chooses the 95 isoline to represent the potential activity range of residents.

[0100] In a specific optional implementation, according to the simulation environment and historical feature data, the activity scope of the community life circle is defined based on the home domain theory, and the activity definition scope includes:

[0101] In the process of simulating the travel behavior of each residential group based on various historical characteristic data, the cumulative value of the number of entities passing through the unit pixel shows the thermal value, and the thermal map of residents' activities is drawn;

[0102] Convert the bitmap raster data representing the heat map of residents' activities into vector data to obtain the heat range;

[0103] Based on the thermal range, the home range theory was used to define the activity range and obtain the activity definition range.

[0104] S203: According to the simulation environment and historical characteristic data, the internal structure of the living circle is divided through time-space demand thermal simulation to obtain the target internal structure.

[0105] In a specific optional implementation, according to the simulation environment and historical characteristic data, the internal structure of the living circle is divided through the time-space demand thermal simulation, and the target internal structure includes:

[0106] Quantify the thermal value based on the residents' activity heat map to obtain the target thermal value of each unit;

[0107] Calculate the grid mean of all target thermal values ​​covered by a single fishing net to obtain the thermal value of a single spatial unit as the corresponding community residents' travel activity demand characteristics, where the thermal value corresponding to each desire unit is the result of the summary of individual behavioral activities of a community resident;

[0108] Based on the travel activity demand characteristics of all community residents, the internal structure of the living circle is divided to obtain the target internal structure.

[0109] Based on the simulation, the heat map of residents' activities was obtained. Since the AnyLogic platform cannot export vector data with thermal values, it is impossible to quantify the division of community life circles on the ArcGIS platform. Therefore, it is necessary to use the raster calculator tool to substitute the values ​​of the three RGB bands in the thermal bitmap data into the RGB function equation to calculate the color value of each grid (see Formula 1). The higher the color value, the closer it is to red and the higher the thermal value, and the lower the color value, the closer it is to blue and the lower the thermal value.

[0110] L=R×255×255+G×255+B (1)

[0111] Where L——RGB (red, green, blue) color value;

[0112] R——The value range is from 0 to 255. The value of Band1 in the bitmap represents the red component;

[0113] G——The value range is from 0 to 255. The value of Band2 in the bitmap represents the green component;

[0114] B——The value range is from 0 to 255. The value of Band3 in the bitmap represents the blue component;

[0115] The color value of each pixel unit can be obtained by calculation. According to the parameter description of the heat map display control in the official document of the AnyLogic platform, the red color represents 3.5 people passing through per square meter. From this, the corresponding relationship between each color value in the bitmap and the heat value can be deduced. After conversion, the heat value distribution of the community is as follows Figure 8 As shown, a quantifiable heat map is obtained.

[0116] Furthermore, based on the simulated thermal value data and spatial continuity effects, and drawing on Loebach's method of converting activity thermal data into fishing net data when studying children's community activity space, a 20m×20m fishing net covering the activity range of all residents was created on the ArcGIS platform. The thermal value of a single spatial unit was obtained by calculating the mean of all thermal value grids covered by a single fishing net, thereby quantitatively describing the travel activity demand characteristics of community residents in the fishing net, and thus better positioning the space when predicting the efficiency of future planning and construction.

[0117] The unit thermal value data summarized based on the fishing net can be used as an important basis for dividing the internal structure of the community life circle. Each fishing net unit is the result of the summary of each resident's individual behavior activities, which can reflect the most microscopic structural characteristics of the community life circle. This study divides the internal structure of the community life circle into three layers, including the high demand layer for travel activities, the low demand layer, and the potential activity layer. The high and low demand layers for travel activities are divided by the 75th percentile method of the thermal value of the fishing net unit. The potential activity layer is all spaces within the range of residents' travel activities, except for the high and low demand layers, based on the analysis of the home domain theory.

[0118] S204: Perform data analysis based on the activity definition scope and the target internal structure to obtain the life circle division results.

[0119] In a specific optional implementation, after performing data analysis based on the activity definition scope and the target internal structure to obtain the life circle division result, the method further includes:

[0120] Compare the internal structure division results of different community life circles to determine the structure of different levels of demand circles;

[0121] Determine the facilities that will be affected based on the structure of different levels of demand circles;

[0122] Deploy community living circles based on the affected facilities.

[0123] The boundary of the community life circle defined based on the "home domain" theory reflects the potential range of activities that residents will go to under the constraints of the built environment. From the definition results, the boundary of the community life circle is an irregular and internally connected polygon, and it shows the characteristics of expansion along the road. From the perspective of spatial relationship, since most of the residents' travel activities are carried out in the block, most of the area in the community life circle is in the block where the residential unit is located. However, there are also cases where the community life circle crosses the block due to the lack of certain facilities in the block or the residents' tendency to go to facilities with higher service levels. From the perspective of spatial form, due to the influence of the built environment, the residents of each residential unit have differences in the form of the community life circle. For example, under the restriction of the Xinzhou Expressway on the east side of Jinghua Community, the boundary of the community life circle of the residential unit on the east side of the community shows a trend of extending along the expressway and growing toward the inside of Jinghua Community (such as Jingli Garden and Fulin Garden, etc.); while the boundary of the community life circle in the west of Zijing Community with a better walking environment is closer to a circle (such as Ruida Garden and Zijing Garden, etc.).

[0124] Based on the boundaries of the community life circle, the internal structure of the life circle is divided using simulation thermal data. By comparing the results of the internal structure division of different community life circles, it can be found that the high and low demand circles are mainly in a network or tree structure, which is mainly affected by the distribution of facilities around the residential units. From the distribution of high and low demand circles, the public space within the residential unit is a common hot spot activity area for residents of each residential area. Outside the residential area, there are a variety of thermal distribution forms, including a network form extending along the road (such as Yifeng Garden, Jinghua Garden, etc.), a single hot spot center form extending outward around the residential area (Jingli Garden, Juhao Garden, etc.), and a multi-hot spot center form around the residential area and target facilities (Xiangmi Village 3, Yiyou Garden, etc.), which also represents the way residents of each residential area use facilities. In addition to high- and low-demand circles, potential activity circles are areas that should be focused on in the future community life circle planning process. This circle represents areas within the reach of residents where no activities occur. This also means that the area may lack facilities needed for daily life for residents and have a restrictive walking environment. Measures such as increasing service facilities and optimizing the walking environment can be taken to improve residents' efficiency in using potential activity circles.

[0125] Furthermore, according to the results of the community life circle division, it can be found that the same space will be overlapped by multiple life circles. This superposition phenomenon refers to the overlapping of adjacent residential units due to the use of the same community service facilities, that is, the intersection of community life circles. The following will analyze the spatial superposition characteristics from two aspects: the overlap of community life circle activity range and the overlap of internal structure.

[0126] First, the activity ranges of the 16 residential units are overlapped, which reflects the number of residential units that residents can reach within the potential activity range. The more residential areas with potential activities in a certain spatial location, the more accessible the location is to residents of different residential areas, which means that regional service facilities with strong radiation capabilities should be set up in the area. For the three communities of Jinghua, Zijing and Fuxin currently studied, the high potential activity area is basically located at the junction of the three communities, but it is also affected by the fact that the surrounding residential units have not yet been divided into community life circles. In general, the matching relationship between the high potential activity area and the regional service center is relatively balanced. On the one hand, the high potential activity area contains an entrance to a city-level park and a number of complex facility clusters, which is conducive to the efficient use of space. But on the other hand, there are many campuses and residential land in the high potential activity area, as well as inaccessible construction areas, which seriously affect the regional radiation capacity of the space, such as Fig. 9 shown.

[0127] Analyzing the matching of overlapping potential activities in different areas and shared use by surrounding residents can provide guidance for optimizing the community life circle. The matching relationship between high potential activity areas and high-density shared activity areas in the residential units currently analyzed in Lianhua Street needs to be optimized. The matching relationship is best in Zijing Community, and the two are basically consistent; the high-density shared activity area in Jinghua Community has not been shared by enough residential areas, which affects the efficiency of space use, but this situation may also be due to the failure to overlap the community life circles of the surrounding Jingtian and Shiling communities; Fuxin Community has a large residential area and is inaccessible due to access control, so residents of each residential area are restricted from moving around and have difficulty using roads in such areas. Therefore, a large number of daily activities are distributed on the main and secondary roads, and the areas with a high degree of sharing in the community center can only be combined with spaces with low potential activity possibilities, which affects the efficiency of space use. Based on the above problems, the future planning of community life circles should optimize the walking environment of such areas. At the same time, some facilities with higher service levels can be placed in such spaces to attract residents of surrounding residential areas to use them and improve the efficiency of space use, such as Fig.10 shown.

[0128] In this embodiment, various historical characteristic data of the community life circle are collected, and a simulation environment is built based on the historical characteristic data; based on the simulation environment and historical characteristic data, the activity range of the community life circle is defined based on the home domain theory to obtain the activity definition range; based on the simulation environment and historical characteristic data, the internal structure of the life circle is divided through time and space demand thermal simulation to obtain the target internal structure; data analysis is performed based on the activity definition range and the target internal structure to obtain the life circle division result. This improves the accuracy of the community life circle division and is conducive to improving space utilization.

[0129] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0130] Fig.11 The principle block diagram of the community life circle division device corresponding to the community life circle division method of the above embodiment is shown. Fig.11 As shown, the community life circle division device includes an environment building module 31, a scope definition module 32, a structure division module 33 and a result determination module 34. The detailed description of each functional module is as follows:

[0131] The environment building module 31 is used to collect various historical characteristic data of the community life circle and build a simulation environment based on the historical characteristic data;

[0132] A scope definition module 32 is used to define the activity scope of the community life circle based on the home domain theory according to the simulation environment and historical characteristic data to obtain the activity definition scope;

[0133] The structure division module 33 is used to divide the internal structure of the living circle through the time-space demand thermal simulation according to the simulation environment and historical characteristic data to obtain the target internal structure;

[0134] The result determination module 34 is used to perform data analysis based on the activity definition scope and the target internal structure to obtain the life circle division result.

[0135] Optionally, the environment building module 31 includes:

[0136] The parameter configuration unit is used to configure the behavior subject parameters according to various historical characteristic data. The behavior subject parameters include the basic attribute parameters of the behavior subject, the walking speed and diameter parameters of the behavior subject, the facility selection parameters of the behavior subject, the travel chain composition parameters and the travel chain generation probability parameters;

[0137] An environmental simulation unit, used to create a simulated environment;

[0138] The logic generation unit is used to generate the travel chain logic of the behavioral subject based on the subject parameter configuration and simulation environment, wherein the travel chain logic of the behavioral subject includes a simple travel chain logic flow, a complex travel chain logic flow and a comprehensive logic flow.

[0139] Optionally, the scoping module 32 includes:

[0140] The heat map drawing unit is used to draw the heat map of residents' activities by displaying the heat value of the cumulative value of the number of entities passing through the unit pixel during the travel behavior simulation of each residential group according to various historical characteristic data;

[0141] A vectorization unit is used to convert the bitmap raster data representing the thermal map of residents' activities into vector data to obtain the thermal range;

[0142] The scope definition unit is used to define the activity scope based on the thermal range and adopt the home range theory to obtain the activity definition scope.

[0143] Optionally, the structure division module 33 includes:

[0144] A thermal value calculation unit is used to quantify the thermal value based on the resident activity thermal map to obtain the target thermal value of each unit;

[0145] The individual demand evaluation unit is used to calculate the grid mean of all target thermal values ​​covered by a single fishing net, and obtain the thermal value of a single spatial unit as the corresponding community residents' travel activity demand characteristics, where the thermal value corresponding to each desire unit is the result of the summary of individual behavior activities of a community resident;

[0146] The structural division unit is used to divide the internal structure of the living circle based on the travel activity demand characteristics of all community residents to obtain the target internal structure.

[0147] Optionally, the community life circle division device also includes:

[0148] The comparison module is used to compare the internal structure division results of different community life circles and determine the structure of different levels of demand circles;

[0149] The facility determination module is used to determine the influencing facilities based on the structure of different levels of demand circles;

[0150] Deployment module, used to deploy community living circles according to influencing facilities.

[0151] For the specific definition of the community life circle division device, please refer to the definition of the community life circle division method above, which will not be repeated here. Each module in the above-mentioned community life circle division device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0152] To solve the above technical problems, the present application also provides a computer device. Fig.12 , Fig.12 This is a basic structural block diagram of the computer device in this embodiment.

[0153] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 4 with components connected to the memory 41, the processor 42, and the network interface 43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0154] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0155] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or D interface display memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as the program code of the method for dividing the community life circle, etc. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0156] The processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run the program code stored in the memory 41 or process data, such as running the program code of the community life circle division method.

[0157] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0158] The present application also provides another implementation, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores an interface display program, and the interface display program can be executed by at least one processor so that the at least one processor performs the steps of the method for dividing the community living circle as described above.

[0159] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0160] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A method for dividing a community life circle, characterized in that: include: Collect various historical characteristic data of the community life circle, and build a simulation environment based on the historical characteristic data, the historical characteristic data includes basic attribute parameters of the behavior subject, walking speed and diameter parameters of the behavior subject, facility selection parameters of the behavior subject, travel chain composition parameters and travel chain generation probability parameters; According to the simulation environment and the historical characteristic data, the activity range of the community life circle is defined based on the home domain theory to obtain the activity definition range, wherein the home domain theory includes determining the potential activity range using the resident activity heat map; According to the simulation environment and the historical characteristic data, the internal structure of the living circle is divided by time-space demand thermal simulation to obtain a target internal structure, wherein the time-space demand thermal simulation includes quantifying thermal values ​​and calculating the thermal value of each space unit; Performing data analysis based on the activity definition scope and the target internal structure to obtain the life circle division results, wherein the data analysis includes comparing the internal structure division results of different community life circles to determine the structure of different levels of demand circles; Wherein, the activity scope of the community life circle is defined based on the simulation environment and the historical feature data based on the home domain theory, and the activity definition scope includes: In the process of simulating the travel behavior of each residential group based on various historical characteristic data, the cumulative value of the number of entities passing through the unit pixel shows the thermal value, and the thermal map of residents' activities is drawn; Convert the bitmap raster data representing the heat map of residents' activities into vector data to obtain the heat range; Based on the thermal range, the home range theory is used to define the activity range and obtain the activity definition range; Wherein, the internal structure of the living circle is divided according to the simulation environment and the historical characteristic data through time-space demand thermal simulation to obtain the target internal structure, including: Quantifying the thermal value based on the resident activity thermal map to obtain a target thermal value for each unit; Calculate the grid mean of all target thermal values ​​covered by a single fishing net to obtain the thermal value of a single spatial unit as the corresponding community residents' travel activity demand characteristics, where the thermal value corresponding to each desire unit is the result of the summary of individual behavioral activities of a community resident; Based on the travel activity demand characteristics of all community residents, the internal structure of the living circle is divided to obtain the target internal structure.

2. The method for dividing community living circles according to claim 1, characterized in that: The collecting of various historical characteristic data of the community life circle and the building of a simulation environment based on the historical characteristic data include: According to various historical characteristic data, the behavior subject parameters are configured, and the behavior subject parameters include the basic attribute parameters of the behavior subject, the walking speed and diameter parameters of the behavior subject, the facility selection parameters of the behavior subject, the travel chain composition parameters and the travel chain generation probability parameters; Create a simulation environment; Based on the subject parameter configuration and the simulation environment, the travel chain logic of the behavior subject is generated, wherein the travel chain logic of the behavior subject includes a simple travel chain logic flow, a complex travel chain logic flow and a comprehensive logic flow.

3. The method for dividing community living circles according to claim 1, characterized in that: After performing data analysis based on the activity definition scope and the target internal structure to obtain the life circle division result, the method further includes: Compare the internal structure division results of different community life circles to determine the structure of different levels of demand circles; Determine the facilities that will be affected based on the structure of different levels of demand circles; Optimize deployment according to the impact facilities.

4. A device for dividing a community life circle, characterized in that: The method for dividing a community living circle according to any one of claims 1 to 3 is adopted, wherein the device comprises: The environment building module is used to collect various historical characteristic data of the community life circle and build a simulation environment based on the historical characteristic data; A scope definition module is used to define the activity scope of the community life circle based on the home domain theory according to the simulated environment and historical characteristic data to obtain the activity definition scope. The home domain theory includes determining the potential activity scope using the resident activity heat map; A structure division module is used to divide the internal structure of the living circle through time-space demand thermal simulation according to the simulation environment and historical characteristic data to obtain the target internal structure. The time-space demand thermal simulation includes quantifying the thermal value and calculating the thermal value of each space unit; The result determination module is used to perform data analysis based on the activity definition scope and the target internal structure to obtain the life circle division results. The data analysis includes comparing the internal structure division results of different community life circles to determine the structure of different levels of demand circles.

5. The device for dividing community living circles according to claim 4, characterized in that: The environment building module includes: The parameter configuration unit is used to configure the behavior subject parameters according to various historical characteristic data. The behavior subject parameters include the basic attribute parameters of the behavior subject, the walking speed and diameter parameters of the behavior subject, the facility selection parameters of the behavior subject, the travel chain composition parameters and the travel chain generation probability parameters; An environmental simulation unit, used to create a simulated environment; The logic generation unit is used to generate the travel chain logic of the behavioral subject based on the subject parameter configuration and simulation environment, wherein the travel chain logic of the behavioral subject includes a simple travel chain logic flow, a complex travel chain logic flow and a comprehensive logic flow.

6. The device for dividing community living circles according to claim 4, characterized in that: The scoping module includes: The heat map drawing unit is used to display the heat value of the accumulated value of the number of entities passing through the unit pixel in the process of simulating the travel behavior of each residential group according to various historical characteristic data, and draw the heat map of residents' activities; A vectorization unit is used to convert the bitmap raster data representing the thermal map of residents' activities into vector data to obtain the thermal range; The scope definition unit is used to define the activity scope based on the thermal range and adopt the home range theory to obtain the activity definition scope.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for dividing the community living circle as described in any one of claims 1 to 3 is implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for dividing a community living circle as described in any one of claims 1 to 3 is implemented.

Images