A method for constructing a green bridge connected pedestrian network

Abstract

The present invention relates to the technical field of pedestrian network construction, and discloses a green bridge connection type pedestrian network construction method, comprising the following steps: step 1, collecting road network data, verifying road attributes, and constructing a traffic network; step 2, collecting greening data, verifying greening associations, and constructing an ecological network; step 3, setting a connection constraint function; the connection constraint function includes a target connection constraint function and a walking accessibility constraint function; based on the connection constraint function, the constraint conditions of the target connection constraint function of the initial route are screened to obtain the number of nodes of different regional types; the constraint conditions of the walking accessibility constraint function include the number of nodes that can be reached by walking, the length of the walking route, the greening degree along the route, and the walking difficulty; step 4, selecting the series nodes between the initial routes; and connecting the series nodes to construct a pedestrian network. The present invention can effectively improve the green space service radius and optimize the overall benefits of the existing green space by constructing a pedestrian network.

Description

Technical Field

[0001] The present invention relates to the technical field of pedestrian network construction, and in particular to a method for constructing a green bridge connection type pedestrian network. Background Art

[0002] With the continuous acceleration of urbanization, the utilization efficiency and quality of urban public space have become one of the important indicators to measure the livability of a city. In many cities, the original activity areas have gradually exposed their limitations because they failed to fully foresee the future population growth and changes in activity patterns during planning. For example, in some historic urban centers, the park green space is small in area and the facilities are outdated, which makes it difficult to adapt to the increasingly diverse life needs of modern urban residents, such as fitness, parent-child interaction, cultural leisure, etc. In response to this, although the green space area has been consciously increased in the current urban construction, the problems of uneven distribution of green space and poor accessibility are becoming increasingly prominent in the layout structure of many cities. The distance between some residential areas and green space is too far, and factors such as inconvenient transportation have greatly reduced people's opportunities to enjoy green space on a daily basis, affecting the social benefits of urban green space. Especially in some old urban areas, the narrow streets and dense buildings formed due to historical reasons have made green space construction face greater challenges.

[0003] How to optimize the layout of green space and increase the service radius of green space while ensuring the improvement of urban functions, so that more citizens can enjoy green benefits conveniently and quickly, has become a new issue that urban planners must face. At present, some patent documents have proposed different solutions from the perspective of optimizing the layout of green space. For example, the "Method for Automatic Layout of Urban Green Space Based on Artificial Intelligence" with the publication number CN116401736A proposes a solution for using artificial intelligence to generate green space planning that meets planning standards. Another example is the "Method, Device, Electronic Equipment and Storage Medium for Optimizing Urban Green Space Pattern" with the publication number CN113642773A, which proposes a solution for obtaining a green space pattern optimization strategy for the target area based on supply evaluation and service demand evaluation. These solutions can guide the optimization of green space layout to a certain extent, but they are all adjusted from the green space itself, and the applicable scenarios are relatively limited (only suitable for before the construction of new green space, and the effect of improving existing green space is very limited). In addition, few people have given construction plans from the perspective of improving the service radius of green space. Summary of the invention

[0004] The present invention aims to provide a method for constructing a green bridge-connected pedestrian network, which can effectively increase the green space service radius and optimize the overall benefits of existing green spaces by constructing a pedestrian network.

[0005] The basic scheme provided by the present invention is: a method for constructing a green bridge connected pedestrian network, comprising the following steps:

[0006] Step 1: Collect road network data, verify road attributes, and build a transportation network;

[0007] Step 2: Collect greening data, verify greening relationships, and build an ecological network;

[0008] Step 3, setting a connection constraint function; the connection constraint function includes a target connection constraint function and a walking accessibility constraint function; based on the connection constraint function, screening to obtain an initial route; the initial route includes a physical route and a virtual route;

[0009] The constraint conditions of the target link constraint function include the number of nodes of different area types; the area types include ecological areas, service areas and site areas; the constraint conditions of the walking accessibility constraint function include the number of nodes accessible by foot, the length of the walking route, the greening degree along the route, and the walking difficulty;

[0010] Step 4: Based on the initial routes, select the series nodes between the initial routes; and connect the series nodes to construct a walking network.

[0011] Furthermore, in step 1, the road attributes include road alignment, road topological attributes, road grade, road length, road width, road slope and road type; and the road type is determined based on the road function.

[0012] Furthermore, when constructing a transportation network, the target area is first rasterized, and then a topological graph consisting of nodes and lines is constructed based on the adjacency relationship between roads and nodes to form a transportation network.

[0013] Furthermore, in step 2, the greening data includes green space area and green space type; the greening association relationship includes ecological connectivity between green spaces; and the green space type includes ecological type, site type and service type.

[0014] Furthermore, when constructing an ecological network, the target area is first rasterized, and then based on the ecological connectivity relationship, the green spaces are connected to form green space routes; then, based on the adjacency relationship between the green space routes and the nodes, a topological map composed of nodes and lines is constructed to form an ecological network.

[0015] Furthermore, after step 1 and step 2, the constructed transportation network and ecological network are divided into three-dimensional grids to form transportation grid units and ecological grid units with elevation information, and superimposed into a target network according to elevation; and based on the target network, with walking accessibility as a benchmark, the transportation grid units and ecological grid units are connected in series to obtain multiple groups of basic walking routes.

[0016] Furthermore, in step 3, the physical route is a real route screened from multiple groups of basic walking routes based on a connection constraint function.

[0017] Furthermore, in step 3, the virtual line is an optimal line newly generated in the target network based on the connection constraint function.

[0018] Furthermore, when selecting the series nodes between the initial routes, the following steps are included: based on the traffic network, the connection possibility of each node between the initial routes is determined, and the nodes with a connection possibility greater than the corresponding threshold are selected as the first-level nodes; then based on the ecological network and the greenway series connection conditions, the nodes that meet the conditions in the first-level nodes are selected as the series connection nodes.

[0019] The working principle and advantages of the present invention are:

[0020] The present invention provides a green bridge connection type pedestrian network construction method, which provides a new green space construction optimization direction from the perspective of improving the green space service radius. For the urban area to be optimized, the scheme first constructs its traffic network based on the road network, and converts the existing green space into an ecological network; then constructs the associated path between the two, and selects the initial route as needed, and then conditionally connects the routes in series to construct a pedestrian network. Through the pedestrian network, the green space in the urban area can be efficiently connected in series, its walking accessibility can be optimized, and the green space service radius of multiple green spaces can be simultaneously improved, so that the green space can be fully utilized, and the effect of optimizing the overall benefit of the existing green space can be achieved. In particular, the initial route here contains a virtual route, and the comprehensively constructed pedestrian network can be used as a reference for the connection between green spaces and between ordinary grid units and green spaces, which can be used to guide the construction of overpasses or new trails, and the green space service radius can be improved through targeted road design. In addition, the types of green spaces targeted in this scheme include ecological, site and service types. The pedestrian network formed can achieve the series planning of different types of green spaces based on different connection constraint functions, which can meet different benefit optimization needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The present invention is a method flow chart of an embodiment of a method for constructing a green bridge connected pedestrian network. DETAILED DESCRIPTION

[0022] The following is a further detailed description through specific implementation methods:

[0023] The embodiment is basically as shown in the attached Figure 1 As shown: A method for constructing a green bridge connected walking network, comprising the following steps:

[0024] Step 1: Collect road network data, verify road attributes, and build a transportation network.

[0025] In this step, the road attributes include road position, road alignment, road topology, road grade, road length, road width, road slope and road type; the road type is determined based on the road function. Specifically, in this embodiment, the road types include: traffic roads and life roads. The traffic roads include expressways, traffic trunk roads, traffic secondary trunk roads, and traffic branch roads. The life roads include life trunk roads, life secondary trunk roads, and life branch roads; which include waterfront roads, pedestrian streets, bus pedestrian streets, bicycle lanes and urban "greenways".

[0026] When constructing a transportation network, the target area is first rasterized, and then a topological map consisting of nodes and lines is constructed based on the adjacency relationship between roads and nodes to form a transportation network.

[0027] Step 2: Collect greening data, verify greening relationships, and build an ecological network.

[0028] In this step, the greening data includes the location, area and type of green space; the greening association relationship includes the ecological connectivity relationship between green spaces; and the green space types include ecological type, site type and service type.

[0029] Specifically, in this embodiment, the definition of green space is broader and is not limited to "green space" itself. It is more in line with the current diverse urban construction scenarios and helps to achieve more complete spatial planning. Among them, ecological green spaces include large lawn areas, forest activity areas, wetland parks, forest parks and other areas where ecological factors account for a relatively high proportion. Site-type green spaces include green areas such as villas and scenic spots that are closely related to specific sites or buildings. Service-type green spaces include community parks, squares, community gardens and other areas that focus on providing leisure and entertainment services to urban residents.

[0030] When constructing an ecological network, the target area is first rasterized, and then based on the ecological connectivity relationship, the green spaces are connected to form green space routes (the routes formed here include both virtual routes and physical routes). Then, based on the adjacency relationship between the green space routes and the nodes, a topological map consisting of nodes and lines is constructed to form an ecological network.

[0031] Here, the ecological connectivity relationship includes the ecological connectivity relationship between each grid and the ecological connectivity relationship between grid groups. Among them, the grids corresponding to a complete and independent green space constitute a grid group (such as a park corresponds to a grid group). The ecological connectivity relationship between each grid is mostly geographical connectivity, that is, the green spaces in the two grids are geographically connected; the ecological connectivity relationship between grid groups is mostly ecological connectivity, that is, there is an ecological corridor between the two grid groups, or there is ecological communication between the two grid groups. When connecting green spaces, for geographical connectivity, the grids are connected to form a green space route; for ecological connectivity, the ecological corridors are connected to form a green space route.

[0032] After steps 1 and 2, the constructed transportation network and ecological network are divided into three-dimensional grids to form transportation grid units and ecological grid units with elevation information, and superimposed into a target network according to elevation; and based on the target network, with walking accessibility as the benchmark, the transportation grid units and ecological grid units are connected in series to obtain multiple groups of basic walking routes.

[0033] In this embodiment, when performing three-dimensional meshing, reference network data (road network data and greening data extracted again from the raster data) is extracted from the traffic network and ecological network obtained by rasterization processing, and converted into vector data. A three-dimensional coordinate system is established, the vector data is mapped to the three-dimensional coordinate system, and an elevation value is assigned to it to form a basic file. The basic file is imported into a mesh generation tool (such as Gmsh or ANSYS Meshing, etc.).

[0034] Define grid parameters - set parameters such as unit size and boundary conditions as needed; then run the grid generation algorithm to generate a three-dimensional grid, including traffic grid cells and ecological grid cells with elevation information; then overlay them into the target network according to elevation.

[0035] Here, in this scheme, based on the collected road network data and greening data, rasterization processing is first performed to obtain the corresponding traffic network and ecological network, and then the traffic network and ecological network are converted into three-dimensional grids. This setting of the processing order firstly, through the prior rasterization processing, the complex road network data and greening data can be simplified into grid units, thereby reducing the amount of data. Each grid unit represents an area of ​​a fixed size, and numerical calculations can be performed quickly to reduce the processing complexity; and through rasterization, road network data from different sources can be standardized, which is convenient for unified parallel processing and analysis of data; it can effectively reduce the data processing volume and difficulty of the subsequent three-dimensional grid division, and compared with the direct three-dimensional grid division based on road network, greening data, etc., the overall efficiency can be greatly improved. Secondly, through the prior rasterization processing, the data obtained is more convenient for spatial relationship analysis and overlay analysis, can more accurately define the boundaries of the road network, and facilitate accurate and unified height assignment, which helps to achieve higher three-dimensional grid division accuracy in the future. Compared with direct three-dimensional grid division based on road network, greening data, etc., there is also a significant improvement in grid construction accuracy.

[0036] Through the above processing, this solution can better adapt to the complex regional analysis environment that integrates transportation network and green area.

[0037] When measuring the walking accessibility, the ecological grid unit is used as the destination and the traffic grid unit is used as the serial path; the traffic grid unit and the ecological grid unit are serially connected; the accessibility index between the traffic grid unit and the ecological grid unit is calculated, and the route with an accessibility index higher than the threshold is retained as the basic walking route. The accessibility index is calculated using the existing accessibility index evaluation method. The threshold is set according to the actual construction requirements.

[0038] Step 3, setting a connection constraint function; the connection constraint function includes a target connection constraint function and a walking accessibility constraint function; based on the connection constraint function, screening to obtain an initial route; the initial route includes a physical route and a virtual route.

[0039] The constraint conditions of the target link constraint function include the number of nodes of different area types; the area types include ecological areas, service areas and site areas; the constraint conditions of the walking accessibility constraint function include the number of nodes accessible by foot, the length of the walking route, the greening degree along the route, and the walking difficulty.

[0040] In this embodiment, a regression model can be used to screen the initial routes based on the connection constraint function. It can perform analysis under multiple conditions (i.e., multiple constraints) and simultaneously handle the requirements of multiple features and multiple constraints, so as to comprehensively consider the impact of multiple factors on route selection and select the most matching route.

[0041] The walking difficulty of the basic walking route is calculated using a random forest model. Specifically, the random forest model is trained in advance using a walking difficulty training set. The walking difficulty training set includes walking feature data, which includes terrain data (slope, terrain type), road surface data (road surface type, road surface width, road surface condition), climate data (temperature, humidity, precipitation), and pedestrian data (pedestrian pace, pedestrian type). During training, the walking feature data is used as input, and the random forest model predicts the walking difficulty and outputs it.

[0042] When calculating the walking difficulty of the basic walking route, the random forest model predicts the walking difficulty and outputs the basic walking route information, climate benchmark data and pedestrian benchmark data, wherein the climate benchmark data and pedestrian benchmark data are the average climate data and average pedestrian data in the preset target area.

[0043] In this step, the physical route is a real route selected from multiple groups of basic walking routes based on the connection constraint function. The virtual route includes the optimal route newly generated in the target network based on the connection constraint function; the virtual route in this embodiment may also include a virtual route in the green space route.

[0044] Step 4: Based on the initial routes, select the series nodes between the initial routes; and connect the series nodes to construct a walking network.

[0045] When selecting the serial nodes between the initial routes, the following steps are included: based on the traffic network, the connection possibility of each node between the initial routes is determined, and nodes with a connection possibility greater than a corresponding threshold are selected as first-level nodes; then based on the ecological network and the greenway serial conditions, nodes that meet the conditions are selected as serial nodes in the first-level nodes. The greenway serial conditions refer to the goal of serially connecting green spaces.

[0046] Here, when judging the connection possibility of each node between the initial lines, the random forest model is also used for prediction. When selecting nodes, the regression model is also used for selection.

[0047] The random forest model is trained using a link feature set, which contains environmental data of road nodes and roads, including terrain data (slope, terrain type), road surface data (road surface type, road surface width, road surface condition), and the location of facilities along the road.

[0048] During training, the random forest model uses the connection features as input, predicts the connection possibility and outputs it. When calculating the connection possibility of each node between the initial lines, the random forest model uses the node data of the initial line and the connection environment data (i.e. the environment data of the road formed by the two nodes) as input, predicts the connection possibility and outputs it.

[0049] The present embodiment provides a method for constructing a green bridge-connected pedestrian network, which can effectively increase the green space service radius and optimize the overall benefits of existing green spaces by constructing a pedestrian network.

[0050] In particular, this plan covers the construction of pedestrian networks, including secondary planning of physical routes and generation of virtual routes, which can guide the optimization of road layout and increase the service radius of green space. Compared with the green space layout adjustment method in the existing green space optimization plan, this plan proposes a new path, which does not adjust the original green space layout, but connects multiple types of green spaces in series to expand the collective benefits of existing green spaces, and can equivalently optimize the green space layout from the connection planning between green spaces.

[0051] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field are aware of all the common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement the scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for the ordinary technicians in the relevant field to implement this application. It should be pointed out that for the technicians in this field, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A method for constructing a green bridge connected pedestrian network, characterized in that: The following steps are involved: Step 1: Collect road network data, verify road attributes, and build a transportation network; Step 2: Collect greening data, verify greening relationships, and build an ecological network; The greening data includes green space area and green space type; the greening association relationship includes the ecological connectivity relationship between green spaces; the green space types include ecological type, site type and service type; when constructing an ecological network, the target area is firstly rasterized, and then the green spaces are connected based on the ecological connectivity relationship to form a green space route; then, according to the adjacency relationship between the green space route and the node, a topological map composed of nodes and lines is constructed to form an ecological network; Step 3, setting a connection constraint function; the connection constraint function includes a target connection constraint function and a walking accessibility constraint function; Based on the connection constraint function, an initial line is screened and obtained; the initial line includes a physical line and a virtual line; The constraint conditions of the target link constraint function include the number of nodes of different area types; the area types include ecological areas, service areas and site areas; the constraint conditions of the walking accessibility constraint function include the number of nodes accessible by foot, the length of the walking route, the greening degree along the route, and the walking difficulty; Step 4, based on the initial routes, selecting series nodes between the initial routes; and connecting the series nodes to construct a walking network; When selecting the series nodes between the initial routes, the following steps are included: based on the traffic network, the connection possibility of each node between the initial routes is determined, and the nodes with a connection possibility greater than the corresponding threshold are selected as the first-level nodes; then based on the ecological network and the greenway series connection conditions, the nodes that meet the conditions in the first-level nodes are selected as the series connection nodes; the greenway series connection conditions refer to the goal of connecting green spaces in series.

2. A method for constructing a green bridge connected pedestrian network according to claim 1, characterized in that: In step 1, the road attributes include road alignment, road topological attributes, road grade, road length, road width, road slope and road type; the road type is determined based on the road function.

3. The method for constructing a green bridge connected pedestrian network according to claim 2, characterized in that: When constructing a transportation network, the target area is first rasterized, and then a topological map consisting of nodes and lines is constructed based on the adjacency relationship between roads and nodes to form a transportation network.

4. The method for constructing a green bridge connected pedestrian network according to claim 1, characterized in that: After steps 1 and 2, the constructed transportation network and ecological network are divided into three-dimensional grids to form transportation grid units and ecological grid units with elevation information, and superimposed into a target network according to elevation; and based on the target network, with walking accessibility as the benchmark, the transportation grid units and ecological grid units are connected in series to obtain multiple groups of basic walking routes.

5. The method for constructing a green bridge connected pedestrian network according to claim 4, characterized in that: In step 3, the physical route is a real route obtained by screening from multiple groups of basic walking routes based on a connection constraint function.

6. The method for constructing a green bridge connected pedestrian network according to claim 4, characterized in that: In step 3, the virtual line is an optimal line newly generated in the target network based on the connection constraint function.

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