Real-time construction method and system for dynamic road network of strip mine

Abstract

The invention provides a strip mine dynamic road network real-time construction method and system, and relates to the technical field of strip mines, and the method comprises the steps: obtaining a set of loading points and a set of unloading points of operation equipment, and track data of transportation equipment between the loading points and the unloading points; based on the spatial distribution of the trajectory data, constructing an actual trajectory passed by the transportation equipment between the loading point and the unloading point as a correlation path between the loading point and the unloading point; cutting the associated path by using the intersection node to obtain a plurality of non-overlapped atomic paths; and constructing the atomic paths and the intersection nodes into a directed graph, and performing assignment on the directed graph based on the path attributes and the node attributes to obtain a dynamic road network. According to the invention, through intelligent analysis of the vehicle track and the loading and unloading signal, automatic construction of the dynamic road network of the strip mine is realized, the road network generation efficiency is improved, and the manual planning cost is reduced.

Description

Technical Field

[0001] The present invention relates to open-pit mine technology, and in particular to a method and system for real-time construction of a dynamic road network in an open-pit mine. Background Art

[0002] In an open-pit mine, road changes are frequent. The excavation face is constantly being excavated and expanded, the waste dump is continuously filled, and the engineering department is also constantly planning and constructing internal roads.

[0003] The rapid change of the path makes it impossible for mine workers to accurately reach a certain location in the open-pit mine; in the field of truck dispatching, it is impossible to accurately judge the distance from the loading point to the unloading point, so it is impossible to estimate the running time of the truck from the loading point to the unloading point, resulting in waste of resources and reduced efficiency. Summary of the Invention

[0004] Embodiments of the present invention provide a method and system for real-time construction of a dynamic road network in an open-pit mine, which can solve the problems in the prior art.

[0005] In a first aspect of an embodiment of the present invention, a method for constructing a dynamic road network in an open-pit mine is provided, including: Obtaining a set of loading points and a set of unloading points of working equipment, and trajectory data of transportation equipment between the loading points and the unloading points; Based on the spatio-temporal distribution correlation of the loading points, the unloading points, and the trajectory data, constructing an actual trajectory passed by the transportation equipment between the loading points and the unloading points as an associated path between the loading points and the unloading points, wherein intersection nodes are configured in the associated path, and the intersection nodes have node attributes; Using the intersection nodes to cut the associated path to obtain a plurality of non-overlapping atomic paths, wherein the atomic paths have path attributes; Constructing the atomic paths and the intersection nodes into a directed graph, and assigning values to the directed graph based on the path attributes and the node attributes to obtain a dynamic road network.

[0006] In an alternative embodiment, the constructing an actual path passed by the working equipment between the loading points and the unloading points as an associated path between the loading points and the unloading points based on the spatial distribution of the trajectory data includes: Generating a plurality of trajectory time series respectively according to the time sequence of the trajectory data corresponding to each transportation equipment; Traversing all combinations of the loading points and the unloading points, and screening out combinations in which the same transportation equipment passes through as associated combination pairs; Connecting the trajectory time series of the transportation equipment in the associated combination pairs in chronological order to obtain the actual trajectory; Determine the associated path based on the actual trajectory.

[0007] In an alternative embodiment, after connecting the trajectory time series of the transportation equipment in the associated combination pair in chronological order to obtain the associated path, the method further includes: Divide the space where the associated path is located to obtain a plurality of space segments; If there are at least two valid path segments in each space segment of the associated combination pair, confirm that the associated path corresponding to the associated combination is valid.

[0008] In an alternative embodiment, constructing the actual trajectory passed by the transportation equipment between the loading point and the unloading point based on the spatial distribution of the trajectory data as the associated path between the loading point and the unloading point includes: Perform normalization and / or thickening processing on the actual trajectory to obtain preprocessed trajectory data; Respectively fit the first path from the loading point to the unloading point and the second path from the unloading point to the loading point based on the global trend and local trend of the preprocessed trajectory; Construct the associated path based on the first path and the second path.

[0009] In an alternative embodiment, respectively fitting the first path from the loading point to the unloading point and the second path from the unloading point to the loading point based on the global trend and local trend of the preprocessed trajectory includes: Divide the actual trajectory to obtain a plurality of trajectory segments; Respectively normalize the coordinate scale and density of the trajectory segments to obtain normalized trajectory segments; Thicken the normalized trajectory segments by interpolation according to the fitting dimensions of the first path and the second path.

[0010] In an alternative embodiment, constructing the actual trajectory passed by the transportation equipment between the loading point and the unloading point based on the spatial distribution of the trajectory data as the associated path between the loading point and the unloading point includes: Detect the intersection area between the associated paths; Configure the intersection node and the node attributes of the intersection node based on the geometric features of the associated path and / or the intersection point of the associated path in the intersection area.

[0011] In an alternative embodiment, after constructing the atomic path and the intersection node into a directed graph and assigning values to the directed graph based on the path attributes and the node attributes to obtain a dynamic road network, the method further includes; Dynamically program the shortest path weights between each pair of intersection nodes in the directed graph based on the path attributes and the node attributes to generate a complete path matrix, where each element in the path matrix represents the shortest path cost between any two intersection nodes.

[0012] In an alternative embodiment, the obtaining of the loading point set and the unloading point set of the working equipment includes: Obtain the loading data and the unloading data of the working equipment; Cluster the loading data and the unloading data respectively to obtain a set of loading points and a set of unloading points.

[0013] In the second aspect of the embodiments of the present invention, Provide an open-pit mine dynamic road network real-time construction system, including: a data acquisition device for acquiring the loading data and the unloading data of the working equipment and the trajectory data of the transportation equipment; a server is connected to the data acquisition device, including a processor and a memory for storing instructions executable by the processor; Wherein, the processor is configured to call the instructions stored in the memory to execute the method described above.

[0014] In the third aspect of the embodiments of the present invention, Provide a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the method described above is implemented.

[0015] The beneficial effects of this application are as follows: Obtain the set of loading points and the set of unloading points of the working equipment and the trajectory data of the transportation equipment between the loading points and the unloading points; construct the actual trajectory passed by the transportation equipment between the loading points and the unloading points based on the spatial distribution of the trajectory data as the associated path between the loading points and the unloading points, where intersection nodes are configured in the associated path; use the intersection nodes to cut the associated path to obtain a number of non-overlapping atomic paths, where the atomic paths have path attributes; construct the atomic paths and the intersection nodes into a directed graph, and encapsulate the directed graph to obtain a dynamic road network. Fit the actual driving path of the transportation equipment between the loading point and the unloading point of the working equipment based on the actual driving trajectories of all transportation equipment. The geometric position of this path highly fits the road center line, and it has high standardization and consistency. After the path fitting is completed, intersection nodes are configured, which can make the topological structure integrity of the road network and the accuracy of the navigation function. And through path cutting, atomic path extraction and directed graph encapsulation, the efficient generation and optimal path planning ability of the dynamic road network can be realized, providing precise technical support for the real-time navigation and update of the open-pit mine road network. Description of the Drawings

[0016] Figure 1 It is a schematic flowchart of the method for real-time construction of the dynamic road network in the open-pit mine according to the embodiment of the present invention; Figure 2 It is a schematic diagram of the principle of the DBSCAN algorithm according to the embodiment of the present invention; Figure 3 It is a schematic diagram of the principle of the Graham convex hull scanning algorithm; Figure 4 It is a schematic overview diagram of the cutting path according to the embodiment of the present invention; Figure 5 It is a schematic diagram of the details of the cutting path according to the embodiment of the present invention; Figure 6 It is a schematic diagram showing the complete fitting road network according to the embodiment of the present invention; Figure 7 It is a schematic overall diagram of the two-way fitting result according to the embodiment of the present invention; Figure 8 It is a schematic diagram of the details of the two-way fitting result according to the embodiment of the present invention. Detailed implementation manners

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part rather than all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] The technical solutions of the present invention will be described in detail below with specific embodiments. These specific embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0019] The present invention provides a method for constructing a dynamic road network in an open-pit mine, as Figure 1 shown, which may include the following steps: S10. Obtain the set of loading points, the set of unloading points of the working equipment, and the trajectory data of the transportation equipment between the loading points and the unloading points. In this embodiment, the working equipment can be the working equipment in an open-pit mine, for example, it can be loading equipment and unloading equipment such as excavators and electric shovels. Sensors for collecting loading data can be installed on the loading equipment. In this embodiment, taking the working equipment as an excavator as an example, the positioning sensor and the loading sensor are installed on the electric shovel. During the excavation process, the sensors collect the loading data of the excavator, and the loading data can include a loading signal and a loading positioning signal. The transportation equipment can use a truck, and the truck is equipped with an on-vehicle terminal. The on-vehicle terminal can include a positioning module and an unloading sensor. The unloading data including an unloading signal and an unloading positioning signal is collected through the positioning module and the unloading sensor. Among them, the positioning module can be set in the cab, and the unloading sensor can be a lifting sensor installed on the vehicle body. The transportation equipment collects the lifting sensor to collect the unloading signal at the dump site, coal pile, and crushing station nodes through the on-vehicle terminal of the truck. The positioning module can use trajectory data such as positioning data, speed, and heading angle during transportation. Of course, during unloading, the operation signal generated during the operation of the electric shovel can also be used as the unloading signal.

[0020] In an open-pit mine, there are often multiple working equipment for loading, and there are also multiple transportation equipment for collection, transportation, and unloading. Therefore, there are multiple loading points on the loading operation surface in the mine, trajectory data exists during the transportation process, and there are multiple unloading points on the unloading surface in the mine. The loading points and unloading points are often scattered. Therefore, in this embodiment, the loading data and the unloading data can be screened and clustered by a clustering method to obtain the set of loading points and the set of unloading points.

[0021] In this embodiment, the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm as shown in Figure 2 can be used to screen and cluster the loading data and the unloading data. Specifically, the coordinate data of the collected loading data and unloading data can be subjected to DBSCAN clustering. According to the density and neighborhood radius of the loading points and unloading points, a number of loading fences and unloading fences are determined. Among them, the loading fence can represent the loading operation surface in the mine, and the unloading fence can represent the unloading operation surface in the mine.

[0022] In this embodiment, a neighborhood with a radius of r can be preset. Select a certain point as the designated point P among several loading points or several unloading points. The neighborhood of the designated point P is the set of all points within a circle with the designated point P as the center and r as the radius. The set contains all the coordinates of the loading points and unloading points. If the r-neighborhood of the designated point P contains at least minPts points, the designated point P is regarded as a core point. If the designated point P does not meet the core point condition, but the designated point P is a point within the r-neighborhood of a certain core point, it is regarded as a boundary point. Points that are neither core points nor boundary points are marked as noise points, and noise points are invalid interference data.

[0023] Specifically, mark all points as unvisited. Traverse all unvisited points, and successively take all unvisited points as the designated point P, calculate the set of points within its r-neighborhood. If the number of neighborhood points is greater than or equal to minPts, mark the designated point P as a core point and start expanding the cluster. If the number of neighborhood points is less than minPts, mark it as a noise point. When expanding the cluster, if the neighborhood point is unvisited, mark it as visited and continue to calculate its r-neighborhood. If the neighborhood point is also a core point, merge the points within its neighborhood into the current cluster. If the neighborhood point is a boundary point, directly add it to the current cluster.

[0024] After traversing all unvisited points in the above manner, several clusters are obtained, and each cluster is a loading working face or an unloading point working face.

[0025] Specifically, after obtaining the coordinates of each loading working face or unloading point working face, calculate the convex edge boundary of each cluster. See Figure 3 As shown, the Graham scan algorithm based on polar angle sorting and stack operation obtains accurate loading points and unloading points. See Figure 3 As shown, find the point with the smallest y coordinate among all points in each cluster. If there are multiple such points, select the point with the smallest x coordinate. Take this point as the base point and sort the other points by polar angle. Use a stack to save the polygon vertices and check point by point whether they form the convex hull boundary. If the angle formed by a certain point and the two top points of the stack is not a left turn, pop the nearest point from the stack. Repeat the above operations until all points are processed. Finally, calculate the landfill area of the waste dump according to the unloading point coordinate data, that is, the representative unloading point set can be accurately calculated, and the excavation or loading area can be calculated according to the loading point coordinate data, that is, the representative loading point set can be accurately calculated.

[0026] Through the loading data and unloading data collected by the sensors of the working equipment, use the density-based clustering algorithm to determine the loading and unloading areas, and extract the coordinates of the loading points and unloading points in the loading area and unloading area to ensure the high-precision definition of the data of the loading points and unloading points, providing a reliable basis for subsequent path planning.

[0027] S20. Construct the actual trajectory passed by the transportation equipment between the loading point and the unloading point as the associated path between the loading point and the unloading point based on the spatio-temporal distribution correlation of the loading point, the unloading point, and the trajectory data. Among them, intersection nodes are configured in the associated path, and the intersection nodes have node attributes.

[0028] In this embodiment, there are m loading points in the loading point set and n unloading points in the unloading point set. Then, theoretically, there are m×n paths between the loading point set and the unloading point set, that is, between the loading working area and the unloading working area. However, not every path is actually passed by the transportation equipment. Therefore, it is necessary to accurately determine the path correlation between the loading point and the unloading point, that is, it is necessary to determine whether there is a path between each loading point and each unloading point.

[0029] In fact, a certain transportation equipment needs to pass through the loading point, the transportation path, and the unloading point during transportation. Therefore, if there is a path between the loading point and the unloading point, there is a temporal correlation between the loading point, the transportation path, and the unloading point. Moreover, there is a spatial correlation between the transportation path and the loading point, and between the transportation path and the unloading point. That is, if there are loading points and unloading points with paths, there are records of the same transportation equipment passing near the loading point and the unloading point, and the trajectory data of the transportation path between the loading point and the unloading point should be temporally continuous. Based on this, in this embodiment, the actual trajectory between the loading point and the unloading point is screened through the spatio-temporal distribution correlation of the loading point, the unloading point, and the trajectory data.

[0030] Exemplarily, multiple trajectory time series are generated respectively according to the time sequence of the trajectory data corresponding to each transportation equipment. The actual trajectory data of the transportation equipment is generated into multiple trajectory time series with time sequence marks according to the time stamps of the recorded trajectory points. In this embodiment, through the unique identifier of the transportation equipment, the trajectory data is grouped by the transportation equipment, and the trajectory point coordinates of each transportation equipment are sorted according to the time stamps of the trajectory points, and multiple trajectory time series corresponding to each transportation equipment are generated respectively.

[0031] Traverse all the combinations of the loading points and the unloading points, and screen out the combinations in which the same transportation equipment passes through as the associated combinations among the combinations; randomly combine all the loading points and unloading points in the calculated loading point set and unloading point set to obtain combinations of loading points and unloading points. Exemplarily, for each loading point and n unloading points, the number of combinations is m×n. Traverse all the loading points and the combinations of the unloading points, and use the unique identifier of the transportation equipment to screen out the combinations of the loading points and unloading points that the same transportation equipment has reached among all the combinations. Exemplarily, between each pair of loading points and unloading points, screen using the spatial distribution characteristics of the trajectory data of the transportation equipment. Determine whether there is an association, that is, whether there is an actual path, between the loading point and the unloading point in the combination by calculating whether there are recorded trajectory points where the same transportation equipment passes near the loading point and near the unloading point (for example, within a range of 30 meters centered on the loading point and the unloading point) in the same combination. If there is no overlapping transportation equipment passing through a certain combination, directly exclude the path corresponding to the combination; if there is overlapping transportation equipment, there is an actual path between the loading point and the unloading point in the combination. Take the corresponding combination as the associated combination.

[0032] Connect the trajectory time series of the transportation equipment in the associated combination in chronological order to obtain the actual trajectory. In this embodiment, splicing the trajectory time series corresponding to the transportation equipment that appears at the loading point and the unloading point in the associated combination in chronological order can obtain the actual trajectory of the same transportation equipment within a specific time period, and the associated path can be determined based on this actual trajectory.

[0033] In one embodiment, factors such as drift and interference may exist in the trajectory point coordinates, resulting in inaccurate positioning. In addition, some transportation equipment may take wrong turns, detours, etc. Therefore, some interference paths may be generated. Therefore, in order to obtain the associated path between the loading point and the unloading point more accurately, in this embodiment, the above actual path can also be verified. In this embodiment, divide the space where the actual trajectory is located into multiple space segments; if there are at least two valid path segments in each space segment of the associated combination, there is the associated path in the space where the actual trajectory is located. If there is an associated path (i.e., the real path) between the loading point and the unloading point, then there is at least a situation where the same transportation equipment passes through at least twice on the associated path. Therefore, in this embodiment, after obtaining the actual trajectory, cut the space where the actual trajectory is located into multiple space segments containing the actual trajectory. Specifically, reference can be made to Figure 4 and Figure 5The schematic diagram showing the cut path. After obtaining the spatial segment, if the number of valid short paths in the spatial segment is greater than or equal to 2, it can be considered that the same transportation device passes through at least twice in the area where the current path is located. Therefore, it can be determined that there is a reliable associated path between the loading point and the unloading point.

[0034] In one embodiment, there are also some intersections between the loading point and the unloading point. Therefore, to ensure the integrity of the topological structure of the road network and the accuracy of the navigation function, it is necessary to set intersection nodes on the associated path to ensure the accuracy and rationality of each intersection node in the road network, thereby optimizing the overall performance and reliability of the road network and laying a technical foundation for the efficient construction and real-time update of the dynamic road network. Based on this, in this embodiment, the intersection area between the associated paths is detected; the intersection node and the node attributes of the intersection node are configured based on the geometric features of the associated path and / or the intersection point of the associated path in the intersection area. In this embodiment, based on the associated path, the algorithm automatically detects the intersection area of the associated path. By analyzing the geometric features of the path (such as intersection points, included angles, and overlapping areas), potential intersection nodes are automatically identified and set. The accuracy of the intersection node position is determined by the resolution and density based on the associated path, ensuring that reasonable node markings are available at all path intersections.

[0035] For complex terrains or areas with significant dynamic changes, there may be special cases that cannot be fully covered by automatic configuration. In such a situation, the intersection nodes can be manually marked and adjusted through an interactive tool. Combining the path fitting results, the user can intuitively add, delete, or move nodes in the intersection area to ensure the integrity of the road network structure.

[0036] Analyze the corresponding associated path coverage rate based on the number of actual paths calculated above, and verify the rationality of the intersection nodes by detecting the connectivity of the associated paths and the integrity of the intersection points. Determine the missing or abnormal intersection nodes. For the intersection area without marked intersection nodes, the corresponding intersection nodes can be supplemented through the associated path coverage rate, connectivity, and integrity of the intersection points associated with the intersection area. Among them, the supplementary conditions can be that the associated path coverage rate is greater than the preset coverage rate, the connectivity is greater than the preset connectivity, and the integrity of the intersection point is greater than the preset integrity. For redundant or misaligned nodes, they are adjusted through an optimization algorithm.

[0037] After the intersection node configuration is completed, node attribute information (such as intersection type, priority or traffic rules of each path and / or transportation device at the intersection node) is assigned to each intersection node, and a topological relationship data table of the road network is generated. The attributes of the nodes are combined with the path information to provide accurate basic data support for subsequent navigation algorithms and path planning.

[0038] S30. Cut the associated path using the intersection nodes to obtain a number of non - overlapping atomic paths, where each atomic path has path attributes.

[0039] After path fitting and intersection node configuration are completed, it is necessary to finely cut the round - trip path between the loading point and the unloading point to construct a complete road network topology structure and achieve an efficient path planning function.

[0040] Perform segmentation processing on the associated path according to the configured intersection nodes and intersection node attributes. Use node coordinates to accurately cut the critical path to generate a number of non - overlapping minimum path units, that is, atomic paths. Each atomic path has adjacent intersection nodes as endpoints and carries path attribute information, such as path length, direction weight, and travel time, etc. To ensure that the road network has high cohesion and low coupling logically, providing a standardized input for subsequent path calculations.

[0041] S40. Construct a directed graph with the atomic paths and the intersection nodes, and assign values to the directed graph based on the path attributes and the node attributes to obtain a dynamic road network.

[0042] Organize the atomic paths and intersection nodes into a directed graph structure, and use an adjacency matrix or an adjacency list to efficiently encapsulate the relationship between the paths and the intersection nodes. The edges between intersection nodes represent paths, and the edge weights are dynamically assigned according to path attributes (such as distance or time cost). To achieve an accurate expression of the topological relationship of the road network, facilitating path search and update. Based on the constructed directed graph, use the Floyd - Warshall algorithm to calculate the global shortest path matrix. This algorithm iteratively optimizes the shortest path weights between each pair of nodes through a dynamic programming method to generate a complete path matrix. Each element in the matrix represents the shortest path cost between any two nodes, which can be used for fast path query and also provides basic support for navigation and scheduling algorithms.

[0043] In an exemplary embodiment, according to actual application requirements, the generated shortest path matrix can be further processed. For example, a path dynamic update module can be added to adjust path weights in real - time to cope with traffic flow changes; or the path planning efficiency can be improved through a topology optimization algorithm. The final road network data can be directly applied to in - vehicle terminals and scheduling systems to achieve full - process support from path search to navigation guidance. Through path cutting, atomic path extraction, and directed graph encapsulation, combined with the shortest path matrix generated by the Floyd - Warshall algorithm, the system realizes the efficient generation of a dynamic road network and the ability of optimal path planning, providing accurate technical support for real - time navigation and update of the open - pit mine road network. See Figure 6 the shown road network display diagram.

[0044] In this application, based on the loading and unloading data of operating equipment in open-pit mines and the actual driving trajectories of all transportation equipment, paths in the road network are fitted and generated. The geometric positions of the paths highly conform to the road centerlines, and they have high standardization and consistency, ensuring the accuracy and reliability of the road network data. Through the shortest path planning, it supports efficient navigation on vehicle-mounted terminals and mobile devices, providing users with accurate and convenient path guidance services, and significantly improving the operation efficiency and operation convenience.

[0045] In order to make the paths in the dynamic road network more refined, the actual trajectories or associated paths can be fitted and optimized to improve the accuracy of the paths that make up the road network, and thus improve the accuracy of the dynamic road network. Based on this, in this embodiment, the actual paths or associated paths obtained by screening through the actual paths can be further fitted and optimized to construct standardized associated paths.

[0046] Specifically, the actual trajectories or associated paths determined by the actual trajectories are thickened to obtain preprocessed trajectory data. In this embodiment, the object of thickening processing can be the uncut actual trajectories or the associated paths after effective short-path verification within the spatial segments obtained by cutting the space where the actual trajectories are located. In this embodiment, the cut associated paths can be taken as an example for illustration. Among them, the reliable associated paths between the determined loading points and unloading points can be presented in the form of cut path segments. The path coordinates after cutting often show uneven and irregular distributions. Direct local fitting may cause fitting failures or large errors in some sections. Therefore, first, the cut paths are subjected to data standardization processing to unify the coordinate scales and densities of the paths. Combining with the fitting radius r, the paths are thickened by interpolation methods to make the distribution density of the path segments match the fitting requirements, thereby improving the stability and accuracy of fitting.

[0047] In addition, the actual trajectories can also be thickened. In this embodiment, the actual trajectories are segmented to obtain multiple trajectory segments; the coordinate scales and densities of the trajectory segments are standardized respectively to obtain standardized trajectory segments; according to the fitting sizes of the first path and the second path, the standardized trajectory segments are thickened by interpolation methods. Specifically, the specific methods for fitting and thickening the first path and the second path can refer to the methods for fitting and thickening the segmented associated paths in the above embodiments.

[0048] After obtaining the thickened path, a two-way path fitting for the space (area) where the actual trajectory is located can be performed based on the thickened path to ensure the coherence and symmetry of the path. In this embodiment, the first path between the loading point and the unloading point and the second path between the unloading point and the loading point can be respectively fitted based on the global trend and the local trend of the preprocessed trajectory; wherein, the first path and the second path can respectively correspond to the forward path and the reverse path, and a two-way path of the transportation device between the loading point and the unloading point is obtained. The associated path is constructed based on the first path and the second path.

[0049] Specifically, the thickened path is segmented and fitted, and the recursive center movement method is used to gradually model the path trend: taking the loading point as the initial center, intercepting the path data within the radius r range, and analyzing the path direction in this area. A fitting curve is fitted based on the trend of the local path, and the intersection point of the curve and the boundary of the circle is the position of the next center. Move the center to the new position, repeat the above interception and fitting process, and gradually expand the fitting range until the path is fitted to the unloading point position. Using the same method, a reverse path fitting model from the unloading point to the loading point is constructed. Through the two-way fitting of the forward and reverse paths, the coherence and symmetry of the path are ensured. Specifically, reference can be made to Figure 7 and Figure 8 the two-way path fitting results shown.

[0050] During the fitting process, the global trend is captured through the trend change of the path, the overall path model is generated by combining the local fitting results, and all path segments are optimized and smoothed to improve the accuracy and practicality of the path fitting. Based on the above path fitting and optimization methods, a high-precision associated path between the loading point and the unloading point can be generated, providing reliable basic data for the construction of the dynamic road network, and realizing the two-way coherence and optimal planning of the path.

[0051] The embodiment of the present application also provides an open-pit mine dynamic road network construction system, including: a data acquisition device and a server. The data acquisition device is used to collect the loading data and unloading data of the operating equipment, as well as the trajectory data of the transportation equipment, and transmit the loading data, unloading data and trajectory data to the server, and the server executes the above open-pit mine dynamic road network construction method.

[0052] In this embodiment, the data acquisition device is installed on the operating equipment and the transportation equipment. The data acquisition device may include a vehicle-mounted terminal and sensors. Exemplarily, the vehicle-mounted terminal is firmly installed at a predetermined position in the cab. The vehicle-mounted terminal should avoid interfering with the driver's operation and ensure the reliability of the power connection and signal transmission. The vehicle-mounted terminal can collect the positioning data of the operating equipment and the transportation equipment to determine the loading point coordinates, unloading point coordinates and the trajectory data of the transportation equipment.

[0053] Install high-precision sensors on operating equipment such as excavators to collect loading or unloading data of the operating equipment. For example, install high-precision sensors at the bucket part to monitor excavation actions and excavation position information in real time; deploy lifting sensors near the truck lift to collect lifting actions and their corresponding unloading point data in real time. All sensors need to be calibrated and tested to ensure the accuracy and integrity of the collected data. After installation, a comprehensive inspection of equipment connection, signal quality, and data transmission needs to be carried out to confirm that it meets the system operation requirements.

[0054] Deploy the server-side program to a dedicated server inside the open-pit mine. Before deployment, the server environment needs to be configured, including operating system optimization, database initialization, and installation and debugging of related dependencies, to ensure that the system operation environment fully matches the program requirements. After deployment, functional testing and performance stress testing are carried out to verify the stability and efficiency of the server-side for data reception, processing, and storage. To ensure system security, network access control policies, encrypted communication channels, and backup mechanisms also need to be configured to prevent external attacks or data loss from affecting the system operation.

[0055] A program capable of executing the method for constructing a dynamic road network in an open-pit mine is deployed in the server. Relevant parameters need to be configured, including parameter debugging of the path fitting algorithm, setting of time scheduling tasks, and formatting definition of output results, to execute the method for constructing a dynamic road network in an open-pit mine. In addition, a timed task (such as daily or weekly timed update) is set in the server according to business requirements to ensure that the road network data can reflect the latest dynamic changes in the mining area in real time. The system also needs to integrate a log recording and monitoring module to track the operation status and abnormal conditions for subsequent maintenance and optimization. After deployment, a full-process test is carried out, including input data simulation, path generation verification, and result visualization, to ensure the accuracy and timeliness of road network generation.

[0056] The server provided by the embodiment of the present application includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus. The memory is used to store computer programs; the processor is used to execute the methods in the embodiments of any one of the above by running the computer programs stored on the memory.

[0057] Optionally, in this embodiment, the above communication bus may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3It is represented only by a thick line, but it does not mean that there is only one bus or one type of bus.

[0058] The communication interface is used for communication between the above computer device and other devices.

[0059] The memory may include RAM, or may include non-volatile memory, for example, at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0060] The above processor may be a general-purpose processor, which may include but is not limited to: CPU (Central Processing Unit, central processor), NP (Network Processor, network processor), etc.; it may also be a DSP (Digital Signal Processing, digital signal processor), ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), FPGA (Field-Programmable Gate Array, field-programmable gate array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0061] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and will not be elaborated herein.

[0062] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the relevant hardware of the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: flash drive, ROM, RAM, disk or optical disc, etc.

[0063] As an exemplary embodiment, the present application also provides a computer-readable storage medium, in which a computer program is stored, and the computer program is configured to execute the method steps of any one of the embodiments when running.

[0064] Optionally, in this embodiment, the above storage medium may be used to execute the program code of the method steps of the embodiments of the present application.

[0065] Optionally, in this embodiment, the storage medium is configured to store for executing the method in the above embodiments.

[0066] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and will not be elaborated herein.

[0067] Optionally, in this embodiment, the above storage medium may include, but is not limited to: various media that can store program codes, such as USB flash drives, ROMs, RAMs, mobile hard disks, magnetic disks, or optical discs.

[0068] The serial numbers of the embodiments of the present application are only for description and do not represent the superiority or inferiority of the embodiments.

[0069] If the integrated units in the above embodiments are implemented in the form of software function units and sold or used as independent products, they can be stored in the above computer-readable storage media. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods in the above embodiments.

[0070] In the several embodiments provided by the present application, it should be understood that the disclosed client can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of units or modules can be in an electrical or other form.

[0071] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution provided in this embodiment.

[0072] In addition, the functional units in each embodiment of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software function units.

[0073] In the above embodiments of the present application, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0074] The above are only the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A method for constructing a dynamic road network in an open-pit mine, characterized in that, Including: Obtaining a set of loading points and a set of unloading points of a working device, as well as trajectory data of a transportation device between the loading points and the unloading points; Constructing an actual trajectory passed by the transportation device between the loading point and the unloading point based on the spatio-temporal distribution correlation of the loading point, the unloading point and the trajectory data as an associated path between the loading point and the unloading point, wherein intersection nodes are configured in the associated path, and the intersection nodes have node attributes; Cutting the associated path by using the intersection nodes to obtain a number of non-overlapping atomic paths, wherein the atomic paths have path attributes; Constructing the atomic paths and the intersection nodes into a directed graph, and assigning values to the directed graph based on the path attributes and the node attributes to obtain a dynamic road network.

2. The method for constructing a dynamic road network in an open-pit mine according to claim 1, characterized in that, The constructing the actual path passed by the working device between the loading point and the unloading point based on the spatial distribution of the trajectory data as the associated path between the loading point and the unloading point includes: Generating a plurality of trajectory time series respectively according to the time sequence of the trajectory data corresponding to each transportation device; Traversing all combinations of the loading points and the unloading points, and screening out the combination pairs in which the same transportation device passes through as associated combination pairs; Connecting the trajectory time series of the transportation devices in the associated combination pairs in chronological order to obtain the actual trajectory; Determining the associated path based on the actual trajectory.

3. The method for constructing a dynamic road network in an open-pit mine according to claim 2, characterized in that, The determining the associated path based on the actual trajectory includes: Dividing the space where the actual trajectory is located to obtain a plurality of space segments; If there are at least two effective path segments in each space segment of the associated combination pair, there is an associated path in the space where the actual trajectory is located.

4. The method for constructing a dynamic road network in an open-pit mine according to any one of claims 1 to 3, characterized in that, The constructing the actual trajectory passed by the transportation device between the loading point and the unloading point based on the spatial distribution of the trajectory data as the associated path between the loading point and the unloading point includes: Performing normalization and / or thickening processing on the actual trajectory to obtain preprocessed trajectory data; Fitting a first path between the loading point and the unloading point and a second path between the unloading point and the loading point respectively based on the global trend and the local trend of the preprocessed trajectory; Constructing the associated path based on the first path and the second path.

5. The method for constructing a dynamic road network in an open-pit mine according to claim 4, characterized in that, The fitting the first path between the loading point and the unloading point and the second path between the unloading point and the loading point respectively based on the global trend and the local trend of the preprocessed trajectory includes: Dividing the actual trajectory to obtain a plurality of trajectory segments; Normalizing the coordinate scale and density of the trajectory segments respectively to obtain normalized trajectory segments; Thickening the normalized trajectory segments by an interpolation method according to the fitting sizes of the first path and the second path.

6. The method for constructing a dynamic road network in an open-pit mine according to claim 1, characterized in that, The constructing the actual trajectory passed by the transportation device between the loading point and the unloading point based on the spatial distribution of the trajectory data as the associated path between the loading point and the unloading point includes: Detecting an intersection area between the associated paths; Configure the intersection node and the node attributes of the intersection node based on the geometric features of the associated path and / or the intersection point of the associated path in the intersection area.

7. The method for constructing a dynamic road network in an open-pit mine according to claim 1, characterized in that, After constructing the atomic path and the intersection node into a directed graph and assigning values to the directed graph based on the path attributes and the node attributes to obtain a dynamic road network, it further includes; Dynamically plan the shortest path weights between each pair of intersection nodes in the directed graph based on the path attributes and the node attributes to generate a complete path matrix, where each element in the path matrix represents the shortest path cost between any two intersection nodes.

8. The method for constructing a dynamic road network in an open-pit mine according to claim 1, characterized in that, The obtaining the set of loading points and the set of unloading points of the working equipment includes: Obtain the loading data and unloading data of the working equipment; Cluster the loading data and the unloading data respectively to obtain a set of loading points and a set of unloading points.

9. A real-time construction system for a dynamic road network in an open-pit mine, characterized in that, Includes: A data acquisition device for acquiring the loading data and unloading data of the working equipment and the trajectory data of the transportation equipment; A server is connected to the data acquisition device and includes a processor and a memory for storing instructions executable by the processor; Wherein, the processor is configured to call the instructions stored in the memory to execute the open-pit mine dynamic road network construction method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, Stores computer program instructions, and when the computer program instructions are executed by the processor, the open-pit mine dynamic road network construction method according to any one of claims 1 to 8 is implemented.

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