Inspection route planning method and device, electronic equipment and storage medium

Abstract

The application provides a kind of inspection route formulation method, device, electronic equipment and storage medium, wherein the method comprises: determining the road section parameter of each road section in the area to be inspected, and the road section parameter includes at least one of the passing difficulty, the passing rule and the passing obstacle point;Determine the road network grid based on the road section parameter of each road section;Determine the weight of each road network node in the road network grid based on the road network grid and the historical event data;Determine the way point in the area to be inspected based on the weight of each road network node in the road network grid, and determine the inspection route in the area to be inspected based on the way point, the weight determined according to the historical event data can reflect the intensive degree of the distribution of urban management events in the surrounding area, thereby providing key support for subsequent formulation of inspection route, overcoming the defect that the formulation of inspection route in the traditional scheme lacks effective data support, resulting in low feasibility of inspection route and poor inspection effect, realizing the dual improvement of inspection rate and efficiency.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method, apparatus, electronic device, and storage medium for determining inspection routes. Background Technology

[0002] With the implementation of refined urban management requirements, many regions have adopted multi-person working groups to conduct regular inspections of urban management incidents. Urban management incidents refer to non-fixed issues in the city that are closely related to the behavior and activities of the public, such as street vendors, posting small advertisements, and road collapses. These incidents are characterized by their unpredictable location, random timing, and wide variety. Moreover, the daily occurrence of such incidents is large; according to statistics from urban areas, hundreds, or even thousands, of urban management incidents occur every day. This undoubtedly poses a great challenge to urban patrols and refined management. Due to limitations in manpower and resources, working groups usually cannot patrol all areas during actual inspections and can only select key areas and road sections for patrol. In this situation, the formulation of patrol routes is particularly important.

[0003] Currently, when formulating inspection routes, most working groups rely on past experience, manually identifying high-risk areas, and combining key construction projects and complex market environments to select key route points. These key route points are then connected to form the inspection route.

[0004] In obtaining inspection routes through key waypoints, common methods include optimal path analysis and traveling salesman analysis (TSA). Optimal path analysis involves analyzing the network to select the path with the least resistance between two points. If performing optimal path analysis on multiple nodes, they must be visited sequentially according to the order of selection. It's important to note that "least resistance" here has multiple meanings. For example, it could be based on single-factor considerations such as shortest time, lowest cost, best road conditions, and fewest toll booths, or it could be based on a comprehensive consideration of multiple factors such as best road conditions and fewest toll booths, lowest cost and shortest time. The shortest path is a single-factor special case of the optimal path problem, where the shortest distance is considered optimal.

[0005] Traveling Salesman Analysis (TSA) is an unordered path analysis method, meaning the traveling salesman can decide the order in which nodes are visited, with the goal of minimizing or near-minimizing the total impedance of the travel route. The difference between TSA and optimal path analysis lies in how the order of node visits is handled during the traversal of all network nodes. Optimal path analysis requires visiting nodes in a specified order (the order in which nodes are selected), while TSA can determine the order in which nodes are visited.

[0006] However, the above-mentioned method for formulating inspection routes has the following drawbacks. First, it relies too heavily on human experience and is highly subjective. Second, the formulation process lacks effective data support, which results in the inability to inspect key areas when conducting inspections based on this route, leading to poor inspection results.

[0007] Secondly, the consideration of road conditions in key areas and sections is too idealistic. It does not take into account whether the current road conditions are easy to pass, and it does not add weight to congested or difficult road sections, resulting in low feasibility of the final inspection route and a time-consuming and laborious inspection process. Summary of the Invention

[0008] This invention provides a method, apparatus, electronic device, and storage medium for determining inspection routes, in order to address the shortcomings of existing technologies that rely on manual selection of route points, which are highly subjective, and the lack of effective data support in the process of determining inspection routes, resulting in low feasibility of inspection routes and poor inspection results.

[0009] This invention provides a method for determining inspection routes, comprising:

[0010] Determine the road segment parameters for each road segment in the area to be inspected, wherein the road segment parameters include at least one of the following: traffic difficulty, traffic rules, and traffic obstacle points;

[0011] The road network grid is determined based on the road segment parameters of each road segment;

[0012] Based on the road network grid and historical event data, the weight of each road network node in the road network grid is determined;

[0013] Based on the weights of each road network node in the road network grid, the waypoints in the area to be inspected are determined, and the inspection route in the area to be inspected is determined based on the waypoints.

[0014] According to a method for determining inspection routes provided by the present invention, the step of determining the weight of each road network node in the road network grid based on the road network grid and historical event data includes:

[0015] Based on the road network grid and the location information in the historical event data, the historical event points within the road network grid are determined;

[0016] Based on the historical event points within the road network grid, determine the historical event points within the neighboring grids corresponding to each road network node in the road network grid;

[0017] The weights of the corresponding road network nodes in the road network grid are determined based on the number of historical event points in each neighboring grid.

[0018] According to a method for determining inspection routes provided by the present invention, the step of determining the weight of the corresponding road network node in the road network grid based on the number of historical event points in each neighboring grid includes:

[0019] If any neighboring grid contains a preset region, then the new weight of any neighboring grid is determined based on the road segment parameters of each road segment in the preset region.

[0020] Based on the newly added weights of each neighboring grid and the number of historical event points within each neighboring grid, the weights of the corresponding road network nodes in the road network grid are determined.

[0021] The preset areas include areas for newly added engineering projects and / or densely populated areas.

[0022] According to a method for determining inspection routes provided by the present invention, determining waypoints in the area to be inspected based on the weights of each network node in the road network grid includes:

[0023] From each road network node of the road network grid, select the waypoints in the area to be inspected;

[0024] The path points are the road network nodes corresponding to the first preset number of weights when the road network nodes in the road network grid are arranged in descending order of weight.

[0025] According to a method for determining an inspection route provided by the present invention, the step of determining the inspection route in the area to be inspected based on the waypoints includes:

[0026] Determine the start and end points of the area to be inspected;

[0027] Input the starting and ending points and the way points into the road network model to obtain the inspection route in the area to be inspected output by the road network model.

[0028] The road network model is trained based on the sample start and end points, sample waypoints, and sample inspection routes in the sample inspection area.

[0029] According to a method for determining inspection routes provided by the present invention, the step of determining the road network grid based on the road segment parameters of each road segment includes:

[0030] Based on the road segment parameters of each road segment, determine the road network data;

[0031] The road network data is processed to obtain a road network grid.

[0032] According to a method for determining inspection routes provided by the present invention, the step of performing road network closure processing on the road network data to obtain a road network grid includes:

[0033] If the road network data indicates that the distance between the end of any road segment and the adjacent road segment is within a preset range, then the end of any road segment is extended so that the end of any road segment is perpendicularly connected to the adjacent road segment to obtain a road network grid.

[0034] The preset range is determined based on the length of any road segment.

[0035] According to a method for determining an inspection route provided by the present invention, the method further includes, after determining the inspection route in the area to be inspected based on the waypoints:

[0036] Obtain real-time road segment parameters for each road segment in the area to be inspected;

[0037] Based on the real-time road segment parameters, the weights of each road network node in the road network grid are updated, and the waypoints in the area to be inspected are updated based on the updated weights of each road network node.

[0038] Based on the updated waypoints in the area to be inspected, the inspection route in the area to be inspected is adjusted.

[0039] The present invention also provides an inspection route planning device, comprising:

[0040] The road segment parameter determination unit is used to determine the road segment parameters of each road segment in the area to be inspected. The road segment parameters include at least one of the following: traffic difficulty, traffic rules, and traffic obstacle points.

[0041] The road network grid determination unit is used to determine the road network grid based on the road segment parameters of each road segment;

[0042] The node weight determination unit is used to determine the weight of each road network node in the road network grid based on the road network grid and historical event data.

[0043] The inspection route determination unit is used to determine the waypoints in the area to be inspected based on the weights of each road network node in the road network grid, and to determine the inspection route in the area to be inspected based on the waypoints.

[0044] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the inspection route planning method as described above.

[0045] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the inspection route formulation method as described above.

[0046] The present invention provides a method, apparatus, electronic device, and storage medium for determining inspection routes. Based on the road segment parameters of each road segment in the area to be inspected, a road network grid is determined. Then, based on the road network grid and historical event data, the weights of each road network node in the grid are determined. The road segment parameters include at least one of traffic difficulty, traffic rules, and traffic obstacles. Based on the weights of each road network node in the grid, waypoints in the area to be inspected are determined, and the inspection route in the area is determined based on these waypoints. The weights of each road network node, calculated from massive amounts of historical event data, can reflect the density of urban management events in the surrounding area of ​​the node, thus providing crucial assistance for subsequent inspection route development. This overcomes the shortcomings of traditional methods, which rely on manual selection of waypoints, are highly subjective, and lack effective data support in the route development process, resulting in low feasibility and poor inspection results. While ensuring the feasibility of the inspection route, this invention saves manpower and resources, achieving a dual improvement in inspection speed and efficiency. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0048] Figure 1 This is a flowchart illustrating the inspection route planning method provided by the present invention;

[0049] Figure 2 This is an example diagram of historical event points within the road network grid provided by the present invention;

[0050] Figure 3 This is an example diagram illustrating the process of determining the weights of road network nodes provided by the present invention;

[0051] Figure 4 This is an example diagram of the road network grid provided by the present invention;

[0052] Figure 5 This is a flowchart of the inspection route planning method provided by the present invention;

[0053] Figure 6 This is a schematic diagram of the inspection route planning device provided by the present invention;

[0054] Figure 7 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0056] This invention provides a method for determining inspection routes. Based on a road network grid, it combines massive amounts of historical event data for weight analysis to determine inspection routes according to the weights of each road network node. This method saves manpower and resources while simultaneously improving inspection speed and efficiency. Figure 1 This is a flowchart illustrating the inspection route planning method provided by the present invention, as shown below. Figure 1 As shown, the method includes:

[0057] Step 110: Determine the road segment parameters for each road segment in the area to be inspected. The road segment parameters include at least one of the following: traffic difficulty, traffic rules, and traffic obstacles.

[0058] Specifically, before formulating the inspection route, it is first necessary to determine the road segment parameters of each road segment in the area to be inspected. These road segment parameters are parameters that characterize the traffic conditions of the corresponding road segment, such as traffic difficulty, traffic rules, and traffic obstacles. Furthermore, the road segment parameters of each road segment can be obtained through road network model analysis. In other words, the road network model can be used for path search and path location to determine the road segment parameters of each road segment.

[0059] Traffic difficulty can be divided into several levels: smooth traffic, low traffic difficulty, moderate traffic difficulty, and high traffic difficulty. Each level of traffic difficulty can be assigned a corresponding weight. For example, when traffic is smooth, the weight can be set to 0; when the road segment is slightly congested, i.e., low traffic difficulty, the weight can be set to 1; when the road segment is moderately congested, i.e., moderate traffic difficulty, the weight can be set to 2; and when the road segment is severely congested, i.e. high traffic difficulty, the weight can be set to 3. In this way, the traffic difficulty of the corresponding road segment can be determined by the weight.

[0060] Traffic rules refer to the driving rules for the corresponding road segment, such as whether it is a one-way street, whether left turns are allowed, and whether U-turns are allowed. Obstacles refer to areas in the corresponding road segment that cannot be passed due to temporary road repairs or road closures. Identifying the obstacles in each road segment can help in the formulation of subsequent inspection routes, that is, it can automatically avoid road segments with obstacles in the area to be inspected.

[0061] Step 120: Determine the road network grid based on the road segment parameters of each road segment;

[0062] Specifically, in step 110, based on the road segment parameters of each road segment in the area to be inspected, step 120 can be executed to construct a road network grid based on the road segment parameters of each road segment. The specific process can be as follows: First, determine the road network data according to the traffic difficulty, communication rules and traffic obstacles in the road segment parameters of each road segment; then, construct the road network grid based on the road network data. Specifically, the road network data can be processed by road network closure to convert the linear road network data into grid surface data, thereby obtaining a surface road network grid.

[0063] During the process of closing the road network data, when the road network data shows that the distance between the end of any road segment and the adjacent road segment exceeds the preset range, the road segment can be removed; the adjacent road segment here is the road segment closest to the end of the corresponding road segment, which can also be called the nearest road segment.

[0064] Accordingly, when the distance between the end of a road segment and an adjacent road segment is within a preset range, the end of the road segment can be extended so that it can connect with the adjacent road segment, thereby forming a closed road network grid.

[0065] It should be noted that the preset range here refers to the tolerable distance range between the end of the corresponding road segment and the adjacent road segment. It can be set according to the actual situation. Preferably, in this embodiment of the invention, the preset range can be determined according to the length of the corresponding road segment. For example, it can be set to 0 to half the length of the corresponding road segment.

[0066] Furthermore, when the road network data shows that the end of any road segment extends beyond the neighboring road segment, and there are no other road segments in front of the end of that road segment, the portion of that road segment that extends beyond the neighboring road segment can be cut off, thus obtaining a closed road network grid.

[0067] Step 130: Based on the road network grid and historical event data, determine the weight of each road network node in the road network grid;

[0068] Specifically, after obtaining the road network grid in step 120, step 130 can be executed. Based on the road network grid and combined with historical event data, the weights of each road network node in the road network grid are determined. The specific process includes the following steps:

[0069] First, the road network grid and historical event data are overlaid. Specifically, the POI (Point of Interest) location information points in the historical event data are overlaid onto the road network grid. This allows us to identify urban management events that occurred within the road network grid within the historical time frame specified by the historical event data, i.e., historical event points within the road network grid.

[0070] The POI (Point of Interest) here refers to the location of an urban management incident in the area to be inspected. It can also be represented as the location information of the urban management incident, which can be characterized by latitude and longitude.

[0071] Subsequently, based on historical event points within the road network grid, the weight of each road network node in the grid can be calculated and determined. This weight can reflect the density of urban management events in the surrounding area of ​​the corresponding road network node.

[0072] In this embodiment of the invention, weight analysis is performed on the basis of road network grid and massive historical event data, which can provide key assistance for subsequent waypoint selection based on the weight and inspection route planning.

[0073] Step 140: Based on the weights of each road network node in the road network grid, determine the waypoints in the area to be inspected, and determine the inspection route in the area to be inspected based on the waypoints.

[0074] Specifically, after obtaining the weights of each road network node in the road network grid through the above steps, step 140 can be executed to determine the waypoints in the area to be inspected based on the weights of each road network node, and to determine the inspection route in the area to be inspected based on the waypoints. This process specifically includes the following steps:

[0075] Since the weight reflects the density of urban management events in the surrounding area of ​​the corresponding road network node, the larger the weight of the road network node, the denser the distribution of urban management events in its surrounding area; correspondingly, the smaller the weight of the road network node, the sparser the distribution of urban management events in its surrounding area. Since the purpose of formulating inspection routes is to inspect as many urban management events as possible, in this embodiment of the invention, the weight of each road network node in the road network grid can be used as a reference to select waypoints from each road network node. That is, a preset number of road network nodes corresponding to weights can be selected in order from high to low weights and used as waypoints in the area to be inspected.

[0076] Considering that there may be newly added engineering projects or densely populated areas in the area to be inspected, and that selecting key areas (path points) based on weights is prone to omissions, in this embodiment of the invention, after selecting the path points in the area to be inspected based on weights, the path points can be supplemented, that is, the newly added engineering projects or densely populated areas are added as new path points to the path points in the previously obtained area to be inspected, thereby forming the final path points.

[0077] Once the waypoints are obtained, they can be combined with the start and end points in the area to be inspected to conduct a spatial GIS (Geographic Information System) traveling salesman analysis. This can also be understood as connecting the start and end points and waypoints in the area to be inspected according to the traveling salesman analysis method to form the optimal inspection route.

[0078] It should be noted that the start and end points here can be set according to actual needs. That is, they can be set at the same location in the area to be inspected, or they can be set at different locations. This embodiment of the invention does not make specific limitations on this.

[0079] In addition, the process of determining the inspection route in the area to be inspected by means of waypoints can be accomplished with the help of a road network model. Specifically, the process can be as follows: first, input the start and end points and waypoints in the area to be inspected into the road network model; then, the road network model performs spatial GIS traveling salesman analysis on the input start and end points and waypoints, and finally obtains the inspection route in the area to be inspected output by the road network model.

[0080] Before inputting the start and end points and waypoints in the area to be inspected into the road network model, the road network model can be pre-trained using sample start and end points and sample waypoints in the sample inspection area, as well as sample inspection routes in the sample inspection area. This process specifically includes the following steps: First, collect a large number of sample start and end points and sample waypoints in the sample inspection area, and determine the sample inspection routes in the sample inspection area; then, based on the sample start and end points, sample waypoints, and sample inspection routes in the sample inspection area, train the initial road network model to obtain the trained road network model.

[0081] The inspection route formulation method provided by this invention determines the road network grid based on the road segment parameters of each road segment in the area to be inspected, and determines the weight of each road network node in the road network grid based on the road network grid and historical event data. The road segment parameters include at least one of traffic difficulty, traffic rules, and traffic obstacles. Based on the weight of each road network node in the road network grid, waypoints in the area to be inspected are determined, and the inspection route in the area to be inspected is determined based on the waypoints. The weights of each road network node calculated based on massive amounts of historical event data can reflect the density of urban management events in the surrounding area of ​​the node, thus providing crucial assistance for the subsequent formulation of inspection routes. This overcomes the shortcomings of traditional methods that rely on manual selection of waypoints, which are highly subjective, and the lack of effective data support in the inspection route formulation process, resulting in low feasibility and poor inspection effects. While ensuring the feasibility of the inspection route, this method saves manpower and resources, achieving a dual improvement in inspection speed and efficiency.

[0082] Based on the above embodiments, step 130 includes:

[0083] Based on the road network grid and the location information in historical event data, historical event points within the road network grid are determined;

[0084] Based on historical event points within the road network grid, determine the historical event points within the neighboring grids corresponding to each road network node in the road network grid;

[0085] The weights of the corresponding road network nodes in the road network grid are determined based on the number of historical event points in each neighboring grid.

[0086] Specifically, step 130, which involves determining the weights of each road network node in the road network grid based on the road network grid and incorporating historical event data, includes the following steps:

[0087] First, POI location information points within a preset time range (historical time range) can be obtained from the GPS (Global Positioning System) location information reported and saved over the years. These POI location information points are the locations where urban management events occurred in the area to be inspected, and can also be represented as the location information of urban management events, which can be characterized by latitude and longitude. The preset time range can be set according to actual needs, for example, it can be one year, that is, one year, one and a half years, two years, etc., from the current time.

[0088] Subsequently, based on the location information in the historical event data and the road network grid, the historical event points within the road network grid can be determined. Specifically, the location information in the road network grid and the historical event data can be overlaid. This process can be completed using the GIS desktop processing software SuperMap iDesktop, that is, by calling the spatial overlay analysis module to overlay the location information in the historical event data onto the road network grid, thereby obtaining the urban management events that occurred in the road network grid within a preset time range, i.e., the historical event points within the road network grid.

[0089] Subsequently, based on the historical event points within the road network grid, the spatial containment module in the GIS desktop processing software SuperMap iDesktop can be used to perform topology calculations to determine the historical event points contained in each grid under the road network grid.

[0090] Subsequently, based on the historical event points contained in each grid of the road network grid, the historical event points in the neighboring grids corresponding to each road network node in the road network grid can be determined. Then, based on the number of historical event points in each neighboring grid and the number of neighboring grids, the average value of the historical event points in the neighboring grids can be determined and used as the weight of the corresponding road network node.

[0091] The following example illustrates the process of determining the weights of road network nodes:

[0092] Figure 2 This is an example diagram of historical event points within the road network grid provided by the present invention. Figure 3 This is an example diagram illustrating the weight determination process for road network nodes provided by the present invention. See also... Figure 2 and Figure 3 It can be seen that the number of historical event points in the four neighboring grids of road network node A is 3, 4, 4 and 5 respectively, and the average value of the historical event points in the four neighboring grids is 4. Therefore, the weight of road network node A is also 4.

[0093] Based on the above embodiments, in step 130, determining the weight of the corresponding road network node in the road network grid based on the number of historical event points in each neighboring grid includes:

[0094] If any neighboring grid contains a preset region, then the new weight of that neighboring grid is determined based on the road segment parameters of each road segment in the preset region.

[0095] Based on the newly added weights of each neighboring grid and the number of historical event points within each neighboring grid, the weights of the corresponding road network nodes in the road network grid are determined.

[0096] The preset regions include areas with newly added engineering projects and / or densely populated areas.

[0097] Considering that in the process of determining the weight of the corresponding road network node based on the number of historical event points in each neighboring grid, there may be newly added engineering project areas and densely populated areas in the neighboring grid, ignoring these situations may easily lead to a large discrepancy between the determined weight and the actual situation. That is, the calculated weight cannot well represent the density of urban management events in the area surrounding the node. Therefore, in the embodiments of the present invention, the above situations can be taken into account in the process of calculating the weight of each grid node in the road network grid.

[0098] Specifically, the process of determining the weights of corresponding road network nodes in the road network grid based on the number of historical event points in each neighboring grid can be divided into the following steps:

[0099] First, determine whether any neighboring grid of any road network node in the road network grid contains a preset area. The preset area here can be a newly added project area, a densely populated area, etc.

[0100] Furthermore, if the neighborhood grid includes a preset area, a corresponding weight can be set for the neighborhood grid, i.e., a new weight. The new weight represents the estimated new urban management events that may occur in the neighborhood grid due to the existence of the preset area. It should be noted that the setting of the new weight can refer to the road segment parameters of each road segment in the corresponding preset area. That is, the new weight of the neighborhood grid can be determined based on one or more of the traffic difficulty, traffic rules, and traffic obstacles of each road segment in the preset area.

[0101] Subsequently, the above process can be repeated to determine the new weights of each neighboring grid corresponding to the road network node. Based on the new weights of each neighboring grid, and combined with the number of historical fact points in each neighboring grid, the weight of the road network node is determined together.

[0102] Accordingly, if the neighborhood grid does not contain the preset region, there is no need to set new weights for the neighborhood grid; furthermore, if none of the neighborhood grids corresponding to the road network node contain the preset region, the weights of the corresponding road network node can be determined directly based on the number of historical event points in each neighborhood grid.

[0103] Based on the above embodiments, in step 140, determining the waypoints in the area to be inspected based on the weights of each network node in the road network grid includes:

[0104] Select the route points in the area to be inspected from each node of the road network grid;

[0105] The path points are the road network nodes corresponding to the first preset number of weights when the road network nodes in the road network grid are arranged in descending order of weight.

[0106] Specifically, step 140, which involves determining the waypoints in the area to be inspected based on the weights of each road network node in the road network grid, includes the following steps:

[0107] Considering that the weight can reflect the density of urban management events in the surrounding area of ​​the corresponding road network node, that is, the larger the weight of the road network node, the denser the distribution of urban management events in its surrounding area; correspondingly, the smaller the weight of the road network node, the sparser the distribution of urban management events in its surrounding area. Since the purpose of formulating inspection routes is to inspect urban management events as much as possible, based on this, in this embodiment of the invention, the size relationship between the weights of each road network node in the road network grid can be determined first.

[0108] Then, based on this size relationship, a preset number of waypoints can be selected from each road network node. Specifically, according to the order of the weights of each road network node in the road network grid from high to low, a preset number of road network nodes corresponding to the weights can be selected in sequence and used as waypoints. The preset number can be set according to actual needs. As a preferred embodiment of the present invention, the preset number is determined to be 30% of the total number of road network nodes in the road network grid.

[0109] Considering that in traditional solutions, the process of obtaining inspection routes through key waypoints only involves connecting these waypoints in an orderly manner using the shortest path, without considering the overall unordered connection method, and omitting the possibility that unordered connections might be less costly and save more manpower and resources, based on the above embodiment, step 140, determining the inspection route in the area to be inspected based on waypoints, includes:

[0110] Determine the start and end points of the area to be inspected;

[0111] Input the start and end points, as well as the way points, into the road network model to obtain the inspection route in the area to be inspected output by the road network model.

[0112] The road network model is trained based on the sample start and end points, sample waypoints, and sample inspection routes in the sample inspection area.

[0113] Specifically, the process of determining the inspection route in the area to be inspected based on the waypoints in the area includes the following steps:

[0114] First, a starting point and an ending point can be set for the planning of this inspection route. That is, a starting point and an ending point can be set in the area to be inspected. The starting point and the ending point can be set in the same location in the area to be inspected or in different locations. This embodiment of the invention does not make specific limitations on this.

[0115] Subsequently, the starting and ending points in the area to be inspected, as well as the waypoints determined through the above process, can be input into the road network model. The road network model performs spatial GIS traveling salesman analysis on the input starting and ending points and waypoints, that is, it connects the starting and ending points and waypoints in the area to be inspected according to the traveling salesman analysis method to form the optimal inspection route, and finally obtains the inspection route in the area to be inspected output by the road network model.

[0116] Before inputting the start and end points and waypoints in the area to be inspected into the road network model, the road network model can be pre-trained by using sample start and end points and sample waypoints in the sample inspection area, as well as sample inspection routes in the sample inspection area.

[0117] The training process of the road network model includes the following steps: First, a large number of sample start and end points and sample waypoints are collected from the sample inspection areas, and sample inspection routes are determined within these areas. Then, based on the sample start and end points, sample waypoints, and sample inspection routes within the sample inspection areas, the initial road network model is trained to obtain the trained road network model. It should be noted that the initial road network model can be constructed based on the city's main traffic roads.

[0118] The method provided in this invention traverses all road segments in the area to be inspected through a road network model, connecting the start and end points and waypoints in the area to be inspected in an unordered manner to form an optimal inspection route. While ensuring the feasibility of the training route, it greatly saves manpower and material resources in the inspection process, thereby achieving a dual improvement in inspection speed and efficiency.

[0119] Based on the above embodiments, step 120 includes:

[0120] Based on the road segment parameters of each road segment, determine the road network data;

[0121] The road network data is processed to form a road network grid.

[0122] Specifically, step 120, the process of constructing a road network grid based on the road segment parameters of each road segment in the area to be inspected, includes the following steps:

[0123] First, road network data is determined based on the traffic difficulty, communication rules, and traffic obstacles in the road segment parameters of each road segment;

[0124] Subsequently, a road network grid can be constructed based on the road network data. This means that the road network data can be processed to close the network, transforming the linear road network data into grid surface data, thereby obtaining a surface-shaped road network grid.

[0125] In the process of closing the road network data, when the road network data shows that the distance between the end of any road segment and the adjacent road segment exceeds a preset range, the road segment can be removed; correspondingly, when the distance between the end of the road segment and the adjacent road segment is within the preset range, the end of the road segment can be extended so that it can connect with the adjacent road segment, thereby forming a closed road network grid.

[0126] Furthermore, when the road network data shows that the end of any road segment extends beyond the neighboring road segment, and there are no other road segments in front of the end of that road segment, the portion of that road segment that extends beyond the neighboring road segment can be cut off, thus obtaining a closed road network grid.

[0127] Based on the above embodiments, in step 120, the road network data is subjected to road network closure processing to obtain a road network grid, including:

[0128] If the road network data indicates that the distance between the end of any road segment and the adjacent road segment is within a preset range, then the end of the road segment is extended so that the end of the road segment is perpendicularly connected to the adjacent road segment to obtain the road network grid.

[0129] The preset range is determined based on the length of the road segment.

[0130] Specifically, the process of performing road network closure processing on the road network data to obtain the road network grid includes the following steps:

[0131] First, based on road network data, we can determine the distance between the end of each road segment and the adjacent road segment. The adjacent road segment here is the road segment closest to the end of the corresponding road segment, which can also be called the nearest road segment.

[0132] Subsequently, when the distance between the end of any road segment and the adjacent road segment is within a preset range, the end of the road segment can be extended so that the end of the road segment can be perpendicularly connected to the adjacent road segment, thereby forming a closed road network grid.

[0133] Accordingly, when the distance between the end of any road segment and an adjacent road segment exceeds a preset range, that road segment can be removed; Figure 4 This is an example diagram of the road network grid provided by the present invention, such as... Figure 4 As shown, after the above processing, the linear road network data is converted into grid surface data, thus obtaining a surface road network grid.

[0134] It should be noted that the preset range here refers to the tolerable distance range between the end of the corresponding road segment and the adjacent road segment. It can be set according to the actual situation. Preferably, the preset range in the embodiment of the present invention can be determined according to the length of the corresponding road segment. For example, the preset range can be set to Where l represents the length of the corresponding road segment, and a is a preset parameter, which can be 1, 2, 3, 4, etc.

[0135] Furthermore, when the road network data indicates that the distance between the end of any road segment and its neighboring road segment exceeds a preset range, and there are no other road segments in front of the end of that road segment, the portion of that road segment that exceeds the neighboring road segment can be cut off, thus obtaining a closed road network grid.

[0136] Considering that in traditional solutions, inspection routes are usually planned well in advance and then used for a period of time after they are obtained, and that traffic data (road conditions, construction data, traffic flow data, etc.) is constantly changing, the timeliness of inspection routes obtained according to the above solutions cannot be well guaranteed. Furthermore, when temporary road repairs or closures occur, which affect traffic, it is impossible to add obstacle points and achieve real-time dynamic planning of inspection routes. To address this issue, based on the above embodiment, step 140, which determines the inspection route in the area to be inspected based on waypoints, further includes:

[0137] Obtain real-time road segment parameters for each road segment in the area to be inspected;

[0138] Based on real-time road segment parameters, the weights of each road network node in the road network grid are updated, and the waypoints in the area to be inspected are updated based on the updated weights of each road network node.

[0139] Based on the waypoints in the updated inspection area, adjust the inspection route in the inspection area.

[0140] Specifically, after obtaining the inspection route in the area to be inspected through the above steps, since the traffic conditions of each road segment and the reported historical event data are constantly changing, in order to ensure the timeliness of the finally determined inspection route, in this embodiment of the invention, the inspection route can also be updated to obtain the latest inspection route, thereby ensuring the effectiveness of the subsequent inspection process. The above process specifically includes the following steps:

[0141] First, obtain the real-time road segment parameters of each road segment in the area to be inspected. This process is basically the same as step 110, except that the latest road segment parameters, i.e. real-time road segment parameters, are obtained here.

[0142] Subsequently, the road network grid can be updated based on real-time road segment parameters to obtain the updated road network grid. Then, based on the updated road network grid and historical event data within a new preset time range, the weights of each road network node in the road network grid can be updated.

[0143] Subsequently, based on the weights of each road network node in the updated road network grid, the waypoints in the area to be inspected are updated, that is, the waypoints in the area to be inspected are adjusted.

[0144] After that, the inspection route in the updated inspection area can be adjusted based on the waypoints in the inspection area. That is, spatial GIS traveling salesman analysis is performed based on the waypoints in the updated inspection area and the new start and end points to obtain the new inspection route.

[0145] The method provided in this invention updates the inspection route in the inspection area based on the real-time road segment parameters of each road segment and the progress of historical event data. While ensuring the effectiveness of the inspection route, it realizes dynamic planning of the inspection route, ensuring its timeliness. This not only saves time and effort in the inspection process, but also ensures the inspection effect.

[0146] Figure 5 This is a general flowchart of the inspection route formulation method provided by the present invention, as follows: Figure 5 As shown, the method includes:

[0147] Step 510: Determine the road segment parameters for each road segment in the area to be inspected. The road segment parameters include at least one of the following: traffic difficulty, traffic rules, and traffic obstacles.

[0148] Step 521: Determine the road network data based on the road segment parameters of each road segment;

[0149] Step 522: If the road network data indicates that the distance between the end of any road segment and the adjacent road segment is within a preset range, then the end of the road segment is extended so that the end of the road segment is perpendicularly connected to the adjacent road segment to obtain the road network grid; the preset range is determined based on the length of the road segment.

[0150] Step 531: Based on the road network grid and the location information in the historical event data, determine the historical event points within the road network grid;

[0151] Step 532: Based on the historical event points within the road network grid, determine the historical event points within the neighboring grids corresponding to each road network node in the road network grid;

[0152] Step 533: If any neighboring grid contains a preset area, then based on the road segment parameters of each road segment in the preset area, determine the new weight of the neighboring grid. The preset area includes newly added engineering project areas and / or densely populated areas.

[0153] Step 534: Based on the newly added weights of each neighboring grid and the number of historical event points in each neighboring grid, determine the weights of the corresponding road network nodes in the road network grid.

[0154] Step 541: Select the path points in the area to be inspected from each road network node in the road network grid. The path points are the road network nodes corresponding to the first preset number of weights when each road network node in the road network grid is arranged in descending order of weight.

[0155] Step 542: Determine the start and end points of the area to be inspected;

[0156] Step 543: Input the start and end points and way points into the road network model to obtain the inspection route in the area to be inspected output by the road network model. The road network model is trained based on the sample start and end points, sample way points and sample inspection routes in the sample inspection area.

[0157] The method provided in this invention determines a road network grid based on the road segment parameters of each road segment in the area to be inspected, and determines the weight of each road network node in the road network grid based on the road network grid and historical event data. The road segment parameters include at least one of traffic difficulty, traffic rules, and traffic obstacles. Based on the weights of each road network node in the road network grid, waypoints in the area to be inspected are determined, and the inspection route in the area to be inspected is determined based on the waypoints. The weights of each road network node calculated based on massive amounts of historical event data can reflect the density of urban management events in the surrounding area of ​​the node, thus providing crucial assistance for the subsequent formulation of inspection routes. This overcomes the shortcomings of traditional solutions, which rely on manual selection of waypoints, are highly subjective, and lack effective data support in the process of formulating inspection routes, resulting in low feasibility and poor inspection effects. While ensuring the feasibility of inspection routes, this method saves manpower and resources, achieving a dual improvement in inspection speed and efficiency.

[0158] The inspection route planning device provided by the present invention is described below. The inspection route planning device described below and the inspection route planning method described above can be referred to in correspondence.

[0159] Figure 6 This is a schematic diagram of the inspection route planning device provided by the present invention, as shown below. Figure 6 As shown, the device includes:

[0160] The road segment parameter determination unit 610 is used to determine the road segment parameters of each road segment in the area to be inspected. The road segment parameters include at least one of the following: traffic difficulty, traffic rules, and traffic obstacle points.

[0161] The road network grid determination unit 620 is used to determine the road network grid based on the road segment parameters of each road segment;

[0162] The node weight determination unit 630 is used to determine the weight of each road network node in the road network grid based on the road network grid and historical event data.

[0163] The inspection route determination unit 640 is used to determine the waypoints in the area to be inspected based on the weights of each road network node in the road network grid, and to determine the inspection route in the area to be inspected based on the waypoints.

[0164] The inspection route planning device provided by this invention determines the road network grid based on the road segment parameters of each road segment in the area to be inspected, and determines the weight of each road network node in the road network grid based on the road network grid and historical event data. The road segment parameters include at least one of traffic difficulty, traffic rules, and traffic obstacles. Based on the weight of each road network node in the road network grid, waypoints in the area to be inspected are determined, and the inspection route in the area to be inspected is determined based on the waypoints. The weights of each road network node calculated based on massive amounts of historical event data can reflect the density of urban management events in the surrounding area of ​​the node, thus providing crucial assistance for the subsequent planning of inspection routes. This overcomes the shortcomings of traditional solutions, which rely on manual selection of waypoints and suffer from high subjectivity, as well as the lack of effective data support in the route planning process, resulting in low feasibility and poor inspection results. While ensuring the feasibility of the inspection route, this device saves manpower and resources, achieving a dual improvement in inspection speed and efficiency.

[0165] Based on the above embodiments, the node weight determination unit 630 is used for:

[0166] Based on the road network grid and the location information in the historical event data, the historical event points within the road network grid are determined;

[0167] Based on the historical event points within the road network grid, determine the historical event points within the neighboring grids corresponding to each road network node in the road network grid;

[0168] The weights of the corresponding road network nodes in the road network grid are determined based on the number of historical event points in each neighboring grid.

[0169] Based on the above embodiments, the node weight determination unit 630 is used for:

[0170] If any neighboring grid contains a preset region, then the new weight of that neighboring grid is determined based on the road segment parameters of each road segment in the preset region.

[0171] Based on the newly added weights of each neighboring grid and the number of historical event points within each neighboring grid, the weights of the corresponding road network nodes in the road network grid are determined.

[0172] The preset areas include areas for newly added engineering projects and / or densely populated areas.

[0173] Based on the above embodiments, the inspection route determination unit 640 is used for:

[0174] From each road network node of the road network grid, select the waypoints in the area to be inspected;

[0175] The path points are the road network nodes corresponding to the first preset number of weights when the road network nodes in the road network grid are arranged in descending order of weight.

[0176] Based on the above embodiments, the inspection route determination unit 640 is used for:

[0177] Determine the start and end points of the area to be inspected;

[0178] Input the starting and ending points and the way points into the road network model to obtain the inspection route in the area to be inspected output by the road network model.

[0179] The road network model is trained based on the sample start and end points, sample waypoints, and sample inspection routes in the sample inspection area.

[0180] Based on the above embodiments, the road network grid determination unit 620 is used for:

[0181] Based on the road segment parameters of each road segment, determine the road network data;

[0182] The road network data is processed to obtain a road network grid.

[0183] Based on the above embodiments, the road network grid determination unit 620 is used for:

[0184] If the road network data indicates that the distance between the end of any road segment and the adjacent road segment is within a preset range, then the end of the road segment is extended so that the end of the road segment is perpendicularly connected to the adjacent road segment to obtain a road network grid.

[0185] The preset range is determined based on the length of the road segment.

[0186] Based on the above embodiments, the device further includes an inspection route update unit, used for:

[0187] Obtain real-time road segment parameters for each road segment in the area to be inspected;

[0188] Based on the real-time road segment parameters, the weights of each road network node in the road network grid are updated, and the waypoints in the area to be inspected are updated based on the updated weights of each road network node.

[0189] Based on the updated waypoints in the area to be inspected, the inspection route in the area to be inspected is adjusted.

[0190] Figure 7 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 7As shown, the electronic device may include a processor 710, a communications interface 720, a memory 730, and a communication bus 740, wherein the processor 710, communications interface 720, and memory 730 communicate with each other via the communication bus 740. The processor 710 can call logical instructions in the memory 730 to execute a patrol route planning method. This method includes: determining road segment parameters for each road segment in the area to be patrolled, the road segment parameters including at least one of traffic difficulty, traffic rules, and traffic obstacles; determining a road network grid based on the road segment parameters; determining the weight of each road network node in the road network grid based on the road network grid and historical event data; determining waypoints in the area to be patrolled based on the weights of each road network node in the road network grid; and determining the patrol route in the area to be patrolled based on the waypoints.

[0191] Furthermore, the logical instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0192] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the inspection route formulation method provided by the above methods, the method comprising: determining the road segment parameters of each road segment in the area to be inspected, the road segment parameters including at least one of traffic difficulty, traffic rules, and traffic obstacle points; determining a road network grid based on the road segment parameters of each road segment; determining the weight of each road network node in the road network grid based on the road network grid and historical event data; determining the waypoints in the area to be inspected based on the weights of each road network node in the road network grid, and determining the inspection route in the area to be inspected based on the waypoints.

[0193] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the inspection route formulation method provided by the above methods. The method includes: determining road segment parameters of each road segment in the area to be inspected, the road segment parameters including at least one of traffic difficulty, traffic rules, and traffic obstacle points; determining a road network grid based on the road segment parameters of each road segment; determining the weight of each road network node in the road network grid based on the road network grid and historical event data; determining waypoints in the area to be inspected based on the weights of each road network node in the road network grid; and determining an inspection route in the area to be inspected based on the waypoints.

[0194] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0195] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0196] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining inspection routes, characterized in that, include: Determine the road segment parameters for each road segment in the area to be inspected, wherein the road segment parameters include at least one of the following: traffic difficulty, traffic rules, and traffic obstacle points; The road network grid is determined based on the road segment parameters of each road segment; Based on the road network grid and historical event data, the weight of each road network node in the road network grid is determined; Based on the weights of each road network node in the road network grid, the waypoints in the area to be inspected are determined, and the inspection route in the area to be inspected is determined based on the waypoints. The determination of the weights of each road network node in the road network grid based on the road network grid and historical event data includes: Based on the road network grid and the location information in the historical event data, the historical event points within the road network grid are determined; Based on the historical event points within the road network grid, determine the historical event points within the neighboring grids corresponding to each road network node in the road network grid; The weights of the corresponding road network nodes in the road network grid are determined based on the number of historical event points in each neighboring grid. The determination of the road network grid based on the road segment parameters of each road segment includes: Based on the road segment parameters of each road segment, determine the road network data; If the road network data indicates that the distance between the end of any road segment and its neighboring road segment exceeds a preset range, then that road segment will be removed. If the road network data indicates that the distance between the end of any road segment and the adjacent road segment is within a preset range, then the end of any road segment is extended so that the end of any road segment is perpendicularly connected to the adjacent road segment to obtain a road network grid. If the road network data indicates that the end of any road segment extends beyond a neighboring road segment, and there are no other road segments in front of the end of any road segment, then the portion of any road segment that extends beyond the neighboring road segment is cut off to obtain the road network grid. The preset range is determined based on the length of any road segment.

2. The inspection route formulation method according to claim 1, characterized in that, The determination of the weight of the corresponding road network node in the road network grid based on the number of historical event points in each neighboring grid includes: If any neighboring grid contains a preset region, then the new weight of any neighboring grid is determined based on the road segment parameters of each road segment in the preset region. Based on the newly added weights of each neighboring grid and the number of historical event points within each neighboring grid, the weights of the corresponding road network nodes in the road network grid are determined. The preset areas include areas for newly added engineering projects and / or densely populated areas.

3. The inspection route formulation method according to claim 1 or 2, characterized in that, The step of determining the waypoints in the area to be inspected based on the weights of each network node in the road network grid includes: From each road network node of the road network grid, select the waypoints in the area to be inspected; The path points are the road network nodes corresponding to the first preset number of weights when the road network nodes in the road network grid are arranged in descending order of weight.

4. The method for determining inspection routes according to claim 1 or 2, characterized in that, Determining the inspection route in the area to be inspected based on the waypoints includes: Determine the start and end points of the area to be inspected; Input the starting and ending points and the way points into the road network model to obtain the inspection route in the area to be inspected output by the road network model. The road network model is trained based on the sample start and end points, sample waypoints, and sample inspection routes in the sample inspection area.

5. The method for determining inspection routes according to claim 1 or 2, characterized in that, The process of determining the inspection route in the area to be inspected based on the waypoints further includes: Obtain real-time road segment parameters for each road segment in the area to be inspected; Based on the real-time road segment parameters, the weights of each road network node in the road network grid are updated, and the waypoints in the area to be inspected are updated based on the updated weights of each road network node. Based on the updated waypoints in the area to be inspected, the inspection route in the area to be inspected is adjusted.

6. A patrol route planning device, characterized in that, include: The road segment parameter determination unit is used to determine the road segment parameters of each road segment in the area to be inspected. The road segment parameters include at least one of the following: traffic difficulty, traffic rules, and traffic obstacle points. The road network grid determination unit is used to determine the road network grid based on the road segment parameters of each road segment; The node weight determination unit is used to determine the weight of each road network node in the road network grid based on the road network grid and historical event data. The inspection route determination unit is used to determine the waypoints in the area to be inspected based on the weights of each road network node in the road network grid, and to determine the inspection route in the area to be inspected based on the waypoints. The determination of the weights of each road network node in the road network grid based on the road network grid and historical event data includes: Based on the road network grid and the location information in the historical event data, the historical event points within the road network grid are determined; Based on the historical event points within the road network grid, determine the historical event points within the neighboring grids corresponding to each road network node in the road network grid; The weights of the corresponding road network nodes in the road network grid are determined based on the number of historical event points in each neighboring grid. The determination of the road network grid based on the road segment parameters of each road segment includes: Based on the road segment parameters of each road segment, determine the road network data; If the road network data indicates that the distance between the end of any road segment and its neighboring road segment exceeds a preset range, then that road segment will be removed. If the road network data indicates that the distance between the end of any road segment and the adjacent road segment is within a preset range, then the end of any road segment is extended so that the end of any road segment is perpendicularly connected to the adjacent road segment to obtain a road network grid. If the road network data indicates that the end of any road segment extends beyond a neighboring road segment, and there are no other road segments in front of the end of any road segment, then the portion of any road segment that extends beyond the neighboring road segment is cut off to obtain the road network grid. The preset range is determined based on the length of any road segment.

7. An electronic 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 inspection route formulation method as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the inspection route formulation method as described in any one of claims 1 to 5.

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