Tower site group intelligent planning method and system based on temporary road sharing, storage medium and computing device

Abstract

The present application belongs to the technical field of power transmission line construction, and particularly relates to a tower site group intelligent planning method and system based on temporary road sharing, a storage medium and a computing device.S1, data acquisition and preprocessing;S2, modeling of the environmental map of the power transmission line corridor channel;S3, calculation of the theoretical reference path length between any two adjacent tower sites in the tower site grid set;S4, calculation of the theoretical reference path length from any tower site in the tower site grid set to the existing road grid set;S5, based on the calculation results of S3 and S4, the multi-tower group is divided, and the final fixed group result is output. In the case where specific temporary road lines have not been generated, according to the characteristics of the spatial distribution of tower sites, terrain accessibility, existing road network distribution and construction machinery traffic constraints, the tower sites along the line can be quickly and intelligently divided into several construction groups with high road sharing potential, providing clear range definition and basic input for subsequent fine path optimization.

Description

Technical Field

[0001] This invention belongs to the field of power transmission line construction technology, specifically relating to a method, system, storage medium, and computing device for intelligent planning of tower site clusters based on shared temporary access roads. Background Technology

[0002] In mechanized construction of power transmission lines, temporary access roads are typically built along the tower sites to meet the needs of transporting construction machinery and materials. Since there are numerous tower sites along the transmission line, distributed linearly or in strips across complex terrain, constructing access roads independently for each tower site would result in extensive duplication of construction and extremely high project costs. To reduce the total length of construction roads, in practical projects, it is desirable to group multiple tower sites that are geographically close, have good terrain connectivity, and can share one or more sections of temporary roads into the same construction group, thereby reducing the total excavation volume through shared access roads.

[0003] Traditional methods of tower site clustering rely heavily on manual experience and trial-and-error processes. Designers typically plan a temporary path for a particular tower site, then attempt to determine whether adjacent tower sites can be "connected" or "accessed" to that path. Through continuous adjustments and repeated trials, several tower groups that can share roads are formed. This approach has significant shortcomings: First, the result of tower site clustering is greatly influenced by the order of path planning. Once the first planned path is determined, it restricts the access method of subsequent tower sites, making it difficult to identify the optimal tower site clustering scheme from a global perspective. Second, as the number of tower sites increases, the number of possible tower site clustering schemes grows exponentially. Manual trial and error is time-consuming and prone to getting stuck in local optima, making it impossible to systematically find a tower site clustering scheme that theoretically maximizes shared roads. Third, this method essentially tightly couples "path planning" and "clustering." Even if the goal is only to obtain a reasonable clustering result, it is necessary to repeatedly generate and evaluate a large number of temporary paths, leading to low efficiency in early decision-making. Summary of the Invention

[0004] The technical problem this invention aims to solve is to provide a method, system, storage medium, and computing device for intelligent planning of tower site clusters based on temporary access road sharing. It can quickly and intelligently divide tower sites along the route into several construction clusters with high potential for shared roads, based on characteristics such as tower site spatial distribution, terrain accessibility, existing road network distribution, and construction machinery access constraints, even before specific temporary road alignments are generated. This provides clear scope definition and basic input for subsequent refined path optimization, thereby reducing the complexity of global optimization while ensuring the economy of the final construction road scheme.

[0005] The technical solution adopted by this invention to solve its technical problem is: a smart planning method for tower site clusters based on temporary access road sharing, including the following steps: S1. Data Acquisition and Preprocessing; Acquire geographic coordinates and terrain elevation data for all tower locations along the transmission line; acquire feature type data and existing road network data within the transmission line corridor, including data on buildings, water systems, roads, economic crop areas, sensitive areas, and other general areas; and road network data including road location and road grade data; define cost attributes, including the maximum allowable slope. Road width Areas containing obstacles, areas containing cash crops, other general areas, and road areas; S2, Environmental map modeling of power transmission line corridors; Define a raster map; rasterize geographic coordinate data and terrain elevation data, perform raster map data layer calibration, and obtain the raster set of tower locations on the transmission line. , Current road grid set ; S3, Calculate the tower location grid set One of the tower locations With another adjacent tower site Theoretical baseline path length ; S4. Calculate the tower location grid set any tower location To the existing road grid set Theoretical baseline path length ; S5. Based on the calculation results of S3 and S4, perform multi-tower clustering to obtain a multi-tower cluster set. With the set of theoretically unreachable tower positions Output the final fixed grouping result.

[0006] Furthermore, step S2 specifically includes the following steps: S201 defines a raster map, including elevation layers. Attribute layer and basic cost layer ; Elevation layer , Represents grid Elevation value; Attribute layer , ; in: Indicates the starting point, i.e., the tower location; Indicates the destination, i.e., the current road surface; This indicates an area with obstacles, including buildings, waterways, and sensitive areas; Indicates the region of cash crops; Indicates other ordinary areas; Basic cost layer : Represents grid Basic toll costs; in: ,when hour; ,when hour; The value is determined based on the specific project requirements, and the range is 3 to 10. ,when hour; ,when hour; S202, according to road width The geographic coordinate data and terrain elevation data in S1 are rasterized, and the raster map elevation layer, attribute layer, and basic cost layer are labeled; houses, water systems, and sensitive areas are labeled as... The economic crop area is marked as Other ordinary areas are designated as N, and existing roads are designated as... Mark the tower location as ; S203, Obtain the set of tower location grids on the transmission line. T (i.e., raster properties) ), and existing road grid sets (i.e., raster properties) ).

[0007] Furthermore, step S3 specifically includes the following steps: S301, Calculate the tower location grid set Two adjacent tower sites and Accessibility score between Determine whether the conditions are met. , This represents the accessibility score threshold, ranging from 0.5 to 0.8; if the threshold is not met, then the tower location grid set... One of the tower locations With another adjacent tower site Theoretical baseline path length between End; otherwise, proceed to S302; ; in, express The number of grid cells representing an obstacle region of a specified width along a straight path; express The straight path specifies the number of upper grid cells of width; The specified width can be 5 to 10 grid cells; ; ; S302, Calculate the tower location grid set One of the tower locations To another adjacent tower The terrain relief coefficient of a local raster map with a specified width along a straight path. ; ; in, Indicates one of the tower locations To another adjacent tower The standard deviation of elevation within a local raster map of a specified width along a straight path; S303, first calculate the detour parameters ; ; in, This indicates the number of grid cells representing the obstacle area in a local grid map; Indicates the number of grid cells in a local raster map; Then calculate the tower location grid set. One of the tower locations With another adjacent tower site Theoretical baseline path length between ; ; ; in, express and The theoretical distance; express and The difference in elevation.

[0008] Furthermore, step S4 specifically includes the following steps: S401, Initialize search; initialization , Group ; Take the tower location grid set any tower location ,by Using a circle as the center, obtain the set of existing road grid cells from all grid cells within a radius of 500m. (i.e., a raster value of 2) and a list of corresponding elevation values. List of elevation values After sorting, stratified sampling is performed to obtain a set of m existing road grid cells with equal elevation differences. ; S402, Accessibility Filtering; Calculate tower location A set of existing road grids with m equal elevation differences Reachability score for each element Remove middle The corresponding element, if If empty, then the tower position Add to the set of theoretically unreachable tower positions ; ; in, express The number of grid cells representing an obstacle region of a specified width along a straight path; express The straight path specifies the number of upper grid cells of width; The specified width can be 5 to 10 grid cells; S403, Calculate the average path length; Calculate the tower location using step S3 A set of existing road grids with up to m equal elevation differences The theoretical baseline path length for each element is then used to calculate the tower location. A set of existing road grids with up to m equal elevation differences The arithmetic mean of the theoretical baseline path length for each element is used as the tower position. Theoretical baseline path length to the existing road network .

[0009] Furthermore, step S5 specifically includes the following steps: S501, Initialization; , Group ; S502~S503, iterative grouping; S502, if Then the tower position Join a group ; S503, comparison , ,like Tower position Join a group ;like ,make Furthermore, the tower position Join a group ; S504, order until the entire set of tower positions is traversed. All elements in the set will be used to obtain the multi-tower cluster collection. and the set of theoretically unreachable tower positions Output the final fixed grouping result.

[0010] The intelligent planning system for tower site clusters based on temporary access road sharing adopts an intelligent planning method for tower site clusters based on temporary access road sharing, including a data acquisition and preprocessing module, a transmission line corridor environment map modeling module, a first calculation module, a second calculation module, and a multi-tower cluster division module. The data acquisition and preprocessing module is used to acquire the geographic coordinates and terrain elevation data of all tower locations of the transmission line; acquire the land feature type data and existing road network data within the transmission line corridor, including data on houses, water systems, roads, economic crop areas, sensitive areas, and other general areas; and the existing road network data including road location and road grade data. It also defines cost attributes, including the maximum allowable slope. Road width Areas containing obstacles, areas containing cash crops, other general areas, and road areas; The transmission line corridor environment map modeling module is used to define a raster map; rasterize geographic coordinate data and terrain elevation data; perform raster map data layer calibration; and obtain a raster set of tower locations on the transmission line. , Current road grid set ; The first calculation module is used to calculate the tower location grid set. One of the tower locations With another adjacent tower site Theoretical baseline path length ; The second calculation module is used to calculate the tower location grid set. any tower location To the existing road grid set Theoretical baseline path length ; The multi-tower clustering module is used to obtain a set of multi-tower clusters. With the set of theoretically unreachable tower positions Output the final fixed grouping result.

[0011] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of an intelligent planning method for tower site clustering based on temporary access road sharing.

[0012] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a smart planning method for tower site clustering based on temporary access road sharing.

[0013] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention provides an intelligent planning method, system, storage medium, and computing device for tower site clusters based on temporary access road sharing. It can quickly and intelligently divide tower sites along the route into several construction clusters with high potential for shared roads, based on characteristics such as tower site spatial distribution, terrain accessibility, existing road network distribution, and construction machinery access constraints, even before specific temporary road paths are generated. This provides clear scope definition and basic input for subsequent refined path optimization, thereby reducing the complexity of global optimization while ensuring the economy of the final construction road scheme. It has the following advantages: First, it significantly improves the efficiency and globality of cluster division. Without the need to pre-plan any temporary roads, it can directly divide the tower locations along the entire route into clusters based on the characteristics of the tower locations and the environment. This completely avoids the time consumption and local pitfalls caused by the path planning sequence and repeated trial and error in traditional methods. It can complete the global analysis of a massive number of tower locations in a short time and quickly output clustering schemes with high sharing potential.

[0014] Second, the subsequent path planning significantly reduces the search complexity. By first dividing the site into clusters, the large-scale path optimization problem across the entire route is decomposed into multiple independent path planning problems within each cluster. This reduces the path search space from "tower locations across the entire route" to "tower locations within each cluster," effectively reducing the variable scale and solution difficulty of subsequent precise path planning. At the same time, each cluster can be processed in parallel, further improving the overall design efficiency.

[0015] Third, this method maximizes the potential for road sharing and reduces construction costs. During the clustering phase, this approach identifies the most likely groups of tower sites to share roads from a global perspective, avoiding the omission of excellent sharing combinations due to later route planning limitations. This results in a final construction road scheme that allows for longer shared access road sections and less redundant construction, directly reducing construction road costs.

[0016] Fourth, it enhances the adaptability and flexibility of the scheme. Since the cluster division does not depend on a specific path orientation, the result can be flexibly adapted to various subsequent path planning strategies and algorithms. It can also provide a consistent basic cluster structure for road design under different construction machinery configurations and different access road standards, thus enhancing the robustness of early-stage project decisions. Attached Figure Description

[0017] Figure 1 This is a flowchart of the present invention; Figure 2 This is a schematic diagram of the tower grouping of the present invention; Figure 3 This is a diagram of a strip corridor according to an embodiment of the present invention; Figure 4 This is a rasterized map according to an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the calculation of the theoretical reference path lengths for tower positions T4 and T5 according to an embodiment of the present invention; Figure 6 This is a schematic diagram of T15 road grid layered sampling and access point evaluation according to an embodiment of the present invention; Figure 7 This is a diagram showing the results of tower site grouping in an embodiment of the present invention. Detailed Implementation

[0018] The following is in conjunction with the appendix Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 and Figure 7 The invention is further illustrated by the embodiments.

[0019] A smart planning method for tower site clusters based on shared temporary access roads includes the following steps: S1. Data Acquisition and Preprocessing; Acquire geographic coordinates and terrain elevation data for all tower locations along the transmission line; acquire feature type data and existing road network data within the transmission line corridor, including data on buildings, water systems, roads, economic crop areas, sensitive areas, and other general areas; and road network data including road location and road grade data; define cost attributes, including the maximum allowable slope. Road width Areas containing obstacles, areas containing cash crops, other general areas, and road areas.

[0020] S2, Environmental map modeling of power transmission line corridors; Define a raster map; rasterize geographic coordinate data and terrain elevation data, perform raster map data layer calibration, and obtain the raster set of tower locations on the transmission line. , Current road grid set .

[0021] Specifically, step S2 includes the following steps: S201 defines a raster map, including elevation layers. Attribute layer and basic cost layer ; Elevation layer , Represents grid Elevation value; Attribute layer , ; in: Indicates the starting point, i.e., the tower location; Indicates the destination, i.e., the current road surface; This indicates an area containing obstacles, including buildings, waterways, and sensitive areas. Indicates the region of cash crops; Indicates other ordinary areas; Basic cost layer : Represents grid Basic toll costs; in: ,when hour; ,when hour; The value is determined based on the specific project requirements, and the range is 3 to 10. ,when hour; ,when hour; S202, according to road width The geographic coordinate data and terrain elevation data in S1 are rasterized, and the raster map elevation layer, attribute layer, and basic cost layer are labeled; houses, water systems, and sensitive areas are labeled as... The economic crop area is marked as Other ordinary areas are designated as N, and existing roads are designated as... Mark the tower location as ; S203, Obtain the set of tower location grids on the transmission line. (i.e., raster properties) ), and existing road grid sets (i.e., raster properties) ).

[0022] S3, Calculate the tower location grid set One of the tower locations With another adjacent tower site Theoretical baseline path length .

[0023] Specifically, step S3 includes the following steps: S301, Calculate the tower location grid set Two adjacent tower sites and Accessibility score between Determine whether the conditions are met. , This represents the accessibility score threshold, typically between 0.5 and 0.8; if the threshold is not met, then the tower location grid set... One of the tower locations With another adjacent tower site Theoretical baseline path length between End; otherwise, proceed to S302; ; in, express The number of grid cells representing an obstacle region of a specified width along a straight path; express The straight path specifies the number of upper grid cells of width; The specified width can be 5 to 10 grid cells; ; ; S302, Calculate the tower location grid set One of the tower locations To another adjacent tower The terrain relief coefficient of a local raster map with a specified width along a straight path. ; ; in, Indicates one of the tower locations To another adjacent tower The standard deviation of elevation within a local raster map of a specified width along a straight path; S303, first calculate the detour parameters ; ; in, This indicates the number of grid cells representing the obstacle area in a local grid map; Indicates the number of grid cells in a local raster map; Then calculate the tower location grid set. One of the tower locations With another adjacent tower site Theoretical baseline path length between ; ; ; in, express and The theoretical distance; express and The difference in elevation.

[0024] S4. Calculate the tower location grid set any tower location To the existing road grid set Theoretical baseline path length .

[0025] Specifically, step S4 includes the following steps: S401, Initialize search; initialization , Group ; Take the tower location grid set any tower location ,by Using a circle as the center, obtain the set of existing road grid cells from all grid cells within a radius of 500m. (i.e., a raster value of 2) and a list of corresponding elevation values. List of elevation values After sorting, stratified sampling is performed to obtain a set of m existing road grid cells with equal elevation differences. ; The value of m ranges from 5 to 10 grid cells; S402, Accessibility Filtering; Calculate tower location A set of existing road grids with m equal elevation differences Reachability score for each element Remove middle The corresponding element, if If empty, then the tower position Add to the set of theoretically unreachable tower positions ; ; in, express The number of grid cells representing an obstacle region of a specified width along a straight path; express The straight path specifies the number of upper grid cells of width; The specified width can be 5 to 10 grid cells; S403, Calculate the average path length; Calculate the tower location using step S3 A set of existing road grids with up to m equal elevation differences The theoretical baseline path length for each element is then used to calculate the tower location. A set of existing road grids with up to m equal elevation differences The arithmetic mean of the theoretical baseline path length for each element is used as the tower position. Theoretical baseline path length to the existing road network .

[0026] S5. Based on the calculation results of S3 and S4, perform multi-tower clustering to obtain a multi-tower cluster set. With the set of theoretically unreachable tower positions Output the final fixed grouping results. For example... Figure 2 As shown.

[0027] Specifically, step S5 includes the following steps: S501, Initialization; , Group ; S502~S503, iterative grouping; S502, if Then the tower position Join a group ; S503, comparison , ,like Tower position Join a group ;like ,make Furthermore, the tower position Join a group ; S504 outputs the final fixed grouping result; make until the entire set of tower positions is traversed. All elements in the set will be used to obtain the multi-tower cluster collection. and the set of theoretically unreachable tower positions Output the final fixed grouping result.

[0028] This embodiment uses a section of a 500kV transmission line project in a mountainous area as an example to illustrate the implementation process of this tower clustering method. This section of the line is approximately 15 kilometers long, with a total of 32 towers (T01~T32). The terrain along the line is a mix of mountains and hills, and the surface cover includes scattered villages, ponds, existing rural roads, and cash crops. Maximum allowable slope... Road width .

[0029] S1, Data Acquisition and Preprocessing: Obtain the geographic coordinates (WGS84 coordinate system, latitude and longitude coordinates) and topographic elevation data (DEM) of all tower locations of the transmission line. Acquire power transmission corridor data (2km wide, 17km long), including land feature data such as houses, water systems, roads, economic crop areas, sensitive areas, and other general areas; Collect existing road network data, including road location and road grade data, classifying them into expressways, county roads and above, and rural roads, such as... Figure 3 As shown, red represents existing county roads and above, green represents existing rural roads, cyan represents water areas, white represents houses, and green represents cash crops.

[0030] Define cost attributes, maximum allowable slope =15, obstacle area 999, economic crop area 1.8, other general area 1.0, road area 0.

[0031] S2, Transmission Line Corridor Environment Map Modeling: Define a raster map; rasterize geographic coordinate data and terrain elevation data, perform raster map data layer calibration, and obtain the raster set of tower locations on the transmission line. , Current road grid set .

[0032] Raster map construction: such as Figure 4 As shown, the entire corridor was divided into a 5m × 5m grid, and data layer calibration was performed: Elevation layer: Fill in the elevation value of each raster based on the DEM data; Attribute Layer: 32 tower sites are designated as tower sites (attribute value = 2), labeled as S; existing roads are current roads (attribute value = 1, 18022 grids), labeled as E; houses, waterways, and sensitive areas are all impassable areas, labeled as obstacle areas (attribute value = 10, 1140633 grids), labeled as O; economic crop areas are high-cost features (attribute value = 3, 1021 grids), labeled as C; other ordinary areas (attribute value = 0), labeled as N; Basic cost layer: obstacle area 999, economic crop area 3.8, other general areas 1.0, road area 0; Tower location grid set 32 elements; Current road grid set 18022 elements; S3, Calculate the tower location grid set One of the tower locations With another adjacent tower site Theoretical baseline path length .

[0033] The calculation process is explained in detail for typical tower locations T4 and T5. For example... Figure 5 As shown, the local raster map (i.e., a strip with a width of 5 grids) is formed on the straight paths T4 and T5 with a specified width.

[0034] S301, Calculate the accessibility score; The obstacle area within the path zone accounts for 10% of the grid area, with an accessibility score of approximately 0.90; since the accessibility score is ≥0.7, it is determined to be passable; S302, calculated terrain relief coefficient: 0.0376; S303, calculate detour parameters and calculate tower location grid set. One of the tower locations With another adjacent tower site Theoretical baseline path length The detour parameter is 1.1376, and the theoretical baseline path length is... It is 729.6m; S4. Calculate the tower location grid set any tower location to the existing road grid set The theoretical baseline path length, taking tower position T15 as an example: S401, Initialize search; With T15 as the center, search for road grids within a radius of 100 grids (500m); 42 candidate road grids were obtained, with an elevation range of 1120m-1245m; Based on stratified sampling by elevation, six representative points were selected: R154, R155, R156, R157, R158, and R159, with an elevation interval of approximately 20.8m between each target. S402, Accessibility Filtering; The accessibility scores from T15 to the six representative road points are calculated as follows: R154 has an accessibility score of 0.43, R155 has an accessibility score of 0.48, R156 has an accessibility score of 0.81, R157 has an accessibility score of 0.85, R158 has an accessibility score of 0.92, and R159 has an accessibility score of 0.32. Remove three road points with an accessibility score less than 0.5 (i.e., R154, R155, and R159). The remaining 3 valid access points are: R156, R157, and R158. S403, Calculate the average path length; T15 to R156: 485m; T15 to R157: 512m; T15 to R158: 467m; The arithmetic mean of the lengths of the three effective theoretical paths is 488m; S5. Based on this, multi-tower clusters are divided to obtain multi-tower clusters. With the set of theoretically unreachable tower positions The Output the final fixed grouping result; S501: Initialization; (Group gathering is empty); (Ungrouped tower site set); (Current group); S502~S503, iterative grouping; Select T1 as the starting tower position and add... ; Compare the path length from T1 to T2 (320m) with the distance from T1 to the road network (620m): 320 < 620, so add T2. ; Compare the path length from T2 to T3 (295m) with the distance from T2 to the road network (580m): 295 < 580, so add T3. ; ... (Continue iterating) When the path length from T3 to T4 (720m) is greater than the distance from T15 to the road network (650m), stop the current cluster. Will join in Clear ; Choose T4 as the new starting point to begin a new group; S504: Output the final fixed grouping result; Ultimately, 16 clusters were obtained, comprising a total of 32 tower slots; the cluster division results are as follows: Figure 7 As shown in the figure and Table 1.

[0035] Table 1. List of Regular Group Members

[0036] The intelligent planning system for tower site clusters based on temporary access road sharing adopts an intelligent planning method for tower site clusters based on temporary access road sharing, including a data acquisition and preprocessing module, a transmission line corridor environment map modeling module, a first calculation module, a second calculation module, and a multi-tower cluster division module. The data acquisition and preprocessing module is used to acquire the geographic coordinates and terrain elevation data of all tower locations of the transmission line; acquire the land feature type data and existing road network data within the transmission line corridor, including data on houses, water systems, roads, economic crop areas, sensitive areas, and other general areas; and the existing road network data including road location and road grade data. It also defines cost attributes, including the maximum allowable slope. Road width Areas containing obstacles, areas containing cash crops, other general areas, and road areas; The transmission line corridor environment map modeling module is used to define a raster map; rasterize geographic coordinate data and terrain elevation data; perform raster map data layer calibration; and obtain a raster set of tower locations on the transmission line. , Current road grid set ; The first calculation module is used to calculate the tower location grid set. One of the tower locations With another adjacent tower site Theoretical baseline path length ; The second calculation module is used to calculate the tower location grid set. any tower location To the existing road grid set Theoretical baseline path length ; The multi-tower clustering module is used to obtain a set of multi-tower clusters. With the set of theoretically unreachable tower positions Output the final fixed grouping result.

[0037] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of an intelligent planning method for tower site clustering based on temporary access road sharing.

[0038] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a smart planning method for tower site clustering based on temporary access road sharing.

[0039] The specific embodiments described are preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. All equivalent changes made to the structure, shape, and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for intelligent planning of tower site clusters based on shared temporary access roads, characterized in that, Including the following steps: S1. Data Acquisition and Preprocessing; Acquire geographic coordinates and terrain elevation data for all tower locations along the transmission line; acquire feature type data and existing road network data within the transmission line corridor, including data on buildings, water systems, roads, economic crop areas, sensitive areas, and other general areas; and road network data including road location and road grade data; define cost attributes, including the maximum allowable slope. Road width Areas containing obstacles, areas containing cash crops, other general areas, and road areas; S2, Environmental map modeling of power transmission line corridors; Define a raster map; rasterize geographic coordinate data and terrain elevation data, perform raster map data layer calibration, and obtain the raster set of tower locations on the transmission line. , Current road grid set ; S3, Calculate the tower location grid set One of the tower locations With another adjacent tower site Theoretical baseline path length ; S4. Calculate the tower location grid set any tower location To the existing road grid set Theoretical baseline path length ; S5. Based on the calculation results of S3 and S4, perform multi-tower clustering to obtain a multi-tower cluster set. With the set of theoretically unreachable tower positions Output the final fixed grouping result.

2. The intelligent planning method for tower site clusters based on temporary access road sharing as described in claim 1, characterized in that, Step S2 specifically includes the following steps: S201 defines a raster map, including elevation layers. Attribute layer and basic cost layer ; Elevation layer , Represents grid Elevation value; Attribute layer , ; in: Indicates the starting point, i.e., the tower location; Indicates the destination, i.e., the current road surface; This indicates an area containing obstacles, including buildings, waterways, and sensitive areas. Indicates the region of cash crops; Indicates other ordinary areas; Basic cost layer : Represents grid Basic toll costs; in: ,when hour; ,when hour; The value is determined based on the specific project requirements, and the range is 3 to 10. ,when hour; ,when hour; S202, according to road width The geographic coordinate data and terrain elevation data in S1 are rasterized, and the raster map elevation layer, attribute layer, and basic cost layer are labeled; houses, water systems, and sensitive areas are labeled as... The economic crop area is marked as Other ordinary areas are designated as N, and existing roads are designated as... Mark the tower location as ; S203, Obtain the set of tower location grids on the transmission line. T and existing road grid sets .

3. The intelligent planning method for tower site clusters based on temporary access road sharing as described in claim 1, characterized in that, Step S3 specifically includes the following steps: S301, Calculate the tower location grid set Two adjacent tower sites and Accessibility score between Determine whether the conditions are met. , This represents the accessibility score threshold, ranging from 0.5 to 0.8; if the threshold is not met, then the tower location grid set... One of the tower locations With another adjacent tower site Theoretical baseline path length between End; otherwise, proceed to S302; ； in, express The number of grid cells representing an obstacle region of a specified width along a straight path; express The straight path specifies the number of upper grid cells of width; The specified width can be 5 to 10 grid cells; ； ； S302, Calculate the tower location grid set One of the tower locations To another adjacent tower The terrain relief coefficient of a local raster map with a specified width along a straight path. ; ； in, Indicates one of the tower locations To another adjacent tower The standard deviation of elevation within a local raster map of a specified width along a straight path; S303, first calculate the detour parameters ; ； in, This indicates the number of grid cells representing the obstacle area in a local grid map; Indicates the number of grid cells in a local raster map; Then calculate the tower location grid set. One of the tower locations With another adjacent tower site Theoretical baseline path length between ; ； ； in, express and The theoretical distance; express and The difference in elevation.

4. The intelligent planning method for tower site clusters based on temporary access road sharing as described in claim 1, characterized in that, Step S4 specifically includes the following steps: S401, Initialize search; initialization , Group ; Take the tower location grid set any tower location ,by Using a circle as the center, obtain the set of existing road grid cells from all grid cells within a radius of 500m. and the corresponding elevation value list List of elevation values After sorting, stratified sampling is performed to obtain a set of m existing road grid cells with equal elevation differences. ; S402, Accessibility Filtering; Calculate tower location A set of existing road grids with m equal elevation differences Reachability score for each element Remove middle The corresponding element, if If empty, then the tower position Add to the set of theoretically unreachable tower positions ; ； in, express The number of grid cells representing an obstacle region of a specified width along a straight path; express The straight path specifies the number of upper grid cells of width; The specified width can be 5 to 10 grid cells; S403, Calculate the average path length; Calculate the tower location using step S3 A set of existing road grids with up to m equal elevation differences The theoretical baseline path length for each element is then used to calculate the tower location. A set of existing road grids with up to m equal elevation differences The arithmetic mean of the theoretical baseline path length for each element is used as the tower position. Theoretical baseline path length to the existing road network .

5. The intelligent planning method for tower site clusters based on temporary access road sharing as described in claim 1, characterized in that, Step S5 specifically includes the following steps: S501, Initialization; , Group ; S502~S503, iterative grouping; S502, if Then the tower position Join a group ; S503, comparison , ,like Tower position Join a group ;like ,make Furthermore, the tower position Join a group ; S504 outputs the final fixed grouping result; make until the entire set of tower positions is traversed. All elements in the set will be used to obtain the multi-tower cluster collection. and the set of theoretically unreachable tower positions Output the final fixed grouping result.

6. A smart planning system for tower site clusters based on shared temporary access roads, characterized in that: The method for intelligent planning of tower site clusters based on temporary access road sharing as described in any one of claims 1-5 includes a data acquisition and preprocessing module, a transmission line corridor environment map modeling module, a first calculation module, a second calculation module, and a multi-tower cluster division module. The data acquisition and preprocessing module is used to acquire the geographic coordinates and terrain elevation data of all tower locations of the transmission line; acquire the land feature type data and existing road network data within the transmission line corridor, including data on houses, water systems, roads, economic crop areas, sensitive areas, and other general areas; and the existing road network data including road location and road grade data. It also defines cost attributes, including the maximum allowable slope. Road width Areas containing obstacles, areas containing cash crops, other general areas, and road areas; The transmission line corridor environment map modeling module is used to define a raster map; rasterize geographic coordinate data and terrain elevation data; perform raster map data layer calibration; and obtain a raster set of tower locations on the transmission line. , Current road grid set ; The first calculation module is used to calculate the tower location grid set. One of the tower locations With another adjacent tower site Theoretical baseline path length ; The second calculation module is used to calculate the tower location grid set. any tower location To the existing road grid set Theoretical baseline path length ; The multi-tower clustering module is used to obtain a set of multi-tower clusters. With the set of theoretically unreachable tower positions Output the final fixed grouping result.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the intelligent planning method for tower site clustering based on temporary access road sharing as described in any one of claims 1-5.

8. A computing 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, it implements the intelligent planning method for tower site clustering based on temporary access road sharing as described in any one of claims 1-5.

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