CN117151320A - Path design data determining method and device for power station area and electronic equipment - Google Patents

Path design data determining method and device for power station area and electronic equipment Download PDF

Info

Publication number
CN117151320A
CN117151320A CN202311110434.2A CN202311110434A CN117151320A CN 117151320 A CN117151320 A CN 117151320A CN 202311110434 A CN202311110434 A CN 202311110434A CN 117151320 A CN117151320 A CN 117151320A
Authority
CN
China
Prior art keywords
data
power station
task
determining
path
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202311110434.2A
Other languages
Chinese (zh)
Inventor
樊梦佳
王小瞳
恽珺
陈海洋
李立刚
李佳玮
母春阁
母春明
苗海颖
邓润
任义勇
孙彦杰
张继杰
张思思
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Rongtong Smart Technology Group Co ltd
State Grid Corp of China SGCC
State Grid Beijing Electric Power Co Ltd
Original Assignee
Beijing Rongtong Smart Technology Group Co ltd
State Grid Corp of China SGCC
State Grid Beijing Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Rongtong Smart Technology Group Co ltd, State Grid Corp of China SGCC, State Grid Beijing Electric Power Co Ltd filed Critical Beijing Rongtong Smart Technology Group Co ltd
Priority to CN202311110434.2A priority Critical patent/CN117151320A/en
Publication of CN117151320A publication Critical patent/CN117151320A/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
    • G07C1/20—Checking timed patrols, e.g. of watchman

Abstract

The invention discloses a method and a device for determining path design data of a power station area and electronic equipment. Wherein the method comprises the following steps: determining a predetermined power station area; calling terrain data corresponding to a preset power station area and task scheduling data of a target object; according to the topographic data and the task scheduling data, determining predicted route data of the target object for executing the target task; determining path use state data in a preset power station area according to the predicted route data; and determining path design data corresponding to the preset power station area according to the path use state data. The invention solves the technical problems that when the object in the preset power station area executes the task, the road through which the task is executed is possibly tedious and disordered, and the efficiency of executing the task by the object is low in the related art.

Description

Path design data determining method and device for power station area and electronic equipment
Technical Field
The invention relates to the field of power system planning and design, in particular to a method and a device for determining path design data of a power station area and electronic equipment.
Background
In order to ensure the normal operation of the power grid, the tasks such as inspection, maintenance or manual operation are required to be executed on various devices, systems and the like of the power station at regular intervals, and because the setting of the power station is generally in a remote area and the place is large, in the related art, when the task is executed by an object located in a predetermined power station area, the road through which the task is executed may be tedious and disordered, and the technical problem of low task execution efficiency of the object exists.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a method and a device for determining path design data of a power station area and electronic equipment, which are used for at least solving the technical problems that when an object positioned in a preset power station area in the related technology executes a task, the road through which the task is executed is possibly tedious and disordered, and the efficiency of executing the task by the object is low.
According to an aspect of the embodiment of the present invention, there is provided a path design data determining method for a power station area, including: determining a predetermined power station area, wherein the predetermined power station area comprises a predetermined power station and an area with a predetermined range from the predetermined power station; invoking terrain data corresponding to the preset power station area and task scheduling data of a target object, wherein the task scheduling data comprises a target task, and the target object is an object for executing the target task in the preset power station area; determining predicted route data of the target object for executing the target task according to the terrain data and the task scheduling data; determining path use state data in the preset power station area according to the predicted route data; and determining path design data corresponding to the preset power station area according to the path use state data.
Optionally, the determining, according to the terrain data and the task scheduling data, predicted route data of the target object for executing the target task includes: dividing the preset power station area to obtain a plurality of sub-power station areas; determining sub-area topographic data corresponding to the plurality of sub-power station areas respectively; and determining predicted route data of the target object for executing the target task according to the sub-region topographic data and the task scheduling data which correspond to the sub-region topographic data and the task scheduling data, wherein the predicted route data comprises region data of sub-power station regions through which the target object sequentially passes and time data of the target object passing through the corresponding sub-power station regions.
Optionally, the determining, according to the terrain data and the task scheduling data, predicted route data of the target object for executing the target task includes: calling a preset prediction route library corresponding to the topographic data; and determining the predicted route data of the target object for executing the target task under the condition that the predicted route data corresponding to the target task exists in the preset predicted route library.
Optionally, after determining the predicted route data of the target object for executing the target task according to the topographic data and the task scheduling data, the method further includes: determining real-time route data when the target object executes the target task; and under the condition that the route corresponding to the route deviation prediction route data corresponding to the real-time route data exceeds a preset deviation index, determining the residual route data of the target object for executing the target task according to the terrain data, wherein the task scheduling data and the real-time route data.
Optionally, the determining, according to the terrain data and the task scheduling data, predicted route data of the target object for executing the target task includes: inputting the terrain data and the task scheduling data into a route prediction model to obtain predicted route data of the target object for executing the target task, wherein the route prediction model is obtained by training an initial model according to sample data, and the sample data comprises: sample topography data, sample task scheduling data, and sample route data for a sample object to perform a sample task.
Optionally, after determining the path usage status data in the predetermined power station area according to the predicted route data, the method further includes: determining idle path data according to path use state data in a preset power station area, wherein the idle path data is data corresponding to an idle path, and the idle path is a path with a path occupied index smaller than a preset threshold value; and determining the next task allocated to the target object according to the idle path data.
Optionally, the determining path design data corresponding to the predetermined power station area according to the path usage status data includes: under the condition that the path design data comprise a to-be-designed road, determining non-existing road data according to path use state data in a preset power station area, wherein the non-existing road data are data corresponding to the non-existing road, and the non-existing road is a path which is not an actual road in the preset power station area; and determining the road to be designed according to the non-existing road data.
According to an aspect of the embodiment of the present invention, there is provided a path design data determining apparatus for a power station area, including: a first determining module, configured to determine a predetermined power station area, where the predetermined power station area includes a predetermined power station and an area within a predetermined range from the predetermined power station; the scheduling module is used for scheduling the topographic data corresponding to the preset power station area and the task scheduling data of a target object, wherein the task scheduling data comprises a target task, and the target object is an object for executing the target task in the preset power station area; the second determining module is used for determining predicted route data of the target object for executing the target task according to the topographic data and the task scheduling data; the third determining module is used for determining path use state data in the preset power station area according to the predicted route data; and the fourth determining module is used for determining path design data corresponding to the preset power station area according to the path use state data.
According to an aspect of an embodiment of the present invention, there is provided an electronic apparatus including: a processor; a memory for storing the processor-executable request; wherein the processor is configured to execute the request to implement the path design data determination method of the power plant area of any one of the above.
According to an aspect of an embodiment of the present invention, there is provided a computer-readable storage medium including: the method of determining path design data for a power plant area according to any one of the preceding claims, when executed by a processor of an electronic device, is enabled to be performed by the electronic device.
In the embodiment of the invention, a preset power station area is determined, wherein the preset power station area comprises a preset power station and an area with a preset range from the preset power station; the method comprises the steps of calling terrain data corresponding to a preset power station area and task scheduling data of a target object, wherein the task scheduling data comprise the target task, and the target object is an object for executing the target task in the preset power station area; according to the topographic data and the task scheduling data, the predicted route data of the target object for executing the target task is determined, and the route using state data in the preset power station area is determined according to the predicted route data, so that the purpose of determining the route design data corresponding to the preset power station area according to the route using state data is achieved. The predicted route data is determined according to the topographic data and the task scheduling data, and task execution, path selection and resource allocation are optimized through the determined predicted route data, so that the task efficiency and success rate are improved, and the technical problems that when an object located in a preset power station area executes the task in the related technology, the road through which the task is executed is possibly tedious and disordered, and the task execution efficiency of the object is low are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a method of determining path design data for a power plant area in accordance with an embodiment of the present application;
fig. 2 is a block diagram of a path design data determining apparatus of a power station area according to an embodiment of the present application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
According to an embodiment of the present application, there is provided an embodiment of a path design data determination method for a power station area, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order different from that herein.
Fig. 1 is a flowchart of a method for determining path design data of a power station area according to an embodiment of the present application, as shown in fig. 1, the method comprising the steps of:
step S102, determining a preset power station area, wherein the preset power station area comprises a preset power station and an area with a preset range from the preset power station;
in the providing step S102 of the present application, the predetermined power station area mainly includes the predetermined power station itself and a predetermined range area at a certain distance from the predetermined power station, and this area is defined to meet the functional requirement and the safety requirement of the predetermined power station, where the predetermined power station included in the predetermined power station area may refer to an electric power facility constructed at a specific location for generating, storing energy, transmitting power, receiving energy, and the like. The predetermined power station provides energy for a power supply network, and can be a traditional energy power station, such as a thermal power plant and a nuclear power station, or a new energy power station, such as a wind power plant and a solar power station.
After setting the predetermined power station, it is necessary to determine the area within a certain range from the power station, which range can be determined according to the requirements and specific requirements of the power station, as a part of the predetermined power station area.
It should be noted that the definition of the predetermined power station area helps to plan and manage the relevant resources and land, ensuring that the operation and development of the predetermined power station meets the requirements.
Step S104, calling terrain data corresponding to a preset power station area and task scheduling data of a target object, wherein the task scheduling data comprises a target task, and the target object is an object for executing the target task in the preset power station area;
in the providing step S104 of the present application, the above-mentioned topographic data may obtain topographic data corresponding to the predetermined power station area from a Geographic Information System (GIS) or other reliable data source; the task scheduling data may include the task type, task description, task time limit, execution place, priority, and related attributes of the target object; the target object may be a staff member of a predetermined power station.
It should be noted that, based on the topographic data, the planner can be helped to better understand the topographic features of the predetermined power station area, so as to conduct path planning, select an optimal execution path, improve task execution efficiency, and through the task scheduling data, the planner can better understand the characteristics and requirements of the tasks, and can conduct reasonable arrangement and scheduling of the tasks based on the information. Therefore, the efficiency of task execution can be improved, the task can be completed on time, and available resources can be utilized to the maximum extent. That is, the acquisition of the topographic data corresponding to the predetermined power station area and the task scheduling data of the target object is helpful to optimize the path planning, improve the task execution safety, and provide basis for decision making, thereby improving the efficiency and effect of task execution.
Step S106, according to the topographic data and the task scheduling data, determining predicted route data of the target object for executing the target task;
in step S106, the predicted route data is combined with the topographic data and the task scheduling data, so as to perform path planning and optimization, determine an optimal route for the target object to execute the task according to the requirements of the target task and the topographic conditions, and generate the predicted route data by using a path planning algorithm, other algorithms and other methods.
In the case where the target objects are plural, the following is specifically described: taking the task priority of each target object into consideration, preferentially arranging the tasks of each target object, and determining the task execution sequence of each target object according to factors such as the emergency degree, importance and the like of the tasks; the method has the advantages that the cross or coincidence of the predicted routes of different target objects is avoided, the paths among the different target objects can not interfere with each other by adjusting the execution sequence of the target object tasks, if the different target objects need the same resources for task execution, resource scheduling and allocation are needed to avoid resource conflict and waste, under the condition of a plurality of target objects, the coordination and cooperation among the target objects can be encouraged, and the overall task execution efficiency and route planning result can be optimized through sharing information, mutual coordination and mutual assistance.
By the steps, the predicted route data of the target object for executing the target task can be determined according to the topographic data and the task scheduling data, and the determined predicted route data can provide a knowledge guide for the execution of the target task, thereby being beneficial to optimizing task execution, path selection and resource allocation and improving the efficiency and success rate of the task.
Step S108, determining path use state data in a preset power station area according to the predicted route data;
in the present application providing step S108, the above-mentioned path usage status data may refer to data describing the usage of the path at a certain moment, and these data may be provided to a user or a system for evaluating the feasibility of the path and selecting the best path, such as:
1) Path traffic capability: the traffic capacity of the path, i.e. the degree of smoothness of the path, is described. The level or index may be used to indicate, for example, high, medium, low traffic capacity.
2) Obstacle information: recording the condition of obstacles on the path, including road construction, traffic accidents, traffic control and the like. Information such as the type of obstacle, location, and range of influence can be described.
3) Limiting conditions: limiting conditions on the recording path, such as speed limit, weight limit, forbidden, etc. Specific values or rules of the constraints may be described.
4) Real-time traffic information: real-time traffic conditions on the path are provided, including congestion level, traffic flow, etc. A color or index may be used to indicate traffic conditions, e.g., red for congestion and green for clear.
5) Weather influence: the influence of weather on the use of the path is recorded, such as wet road or reduced visibility caused by rain and snow weather.
6) Road condition event: and recording the emergency events occurring on the path, such as traffic accidents, road closure and the like. Information such as event type, location, and scope of influence may be described.
It should be noted that, according to the predicted route data generated in the foregoing steps, route information of the target object for executing the target task is obtained, where the information includes a start point and an end point of the route, a path node passing through, path data of each node, and the like; according to the predicted route data, the actual situation and related data are combined to determine the use state of the path in the predetermined power station area, for example, the following states can be included:
1) Passable state: the method indicates that the path is smooth, no obstacle or restriction exists, and free passage can be realized.
2) Partial traffic state: indicating that the path has some obstacles or restrictions but still can pass, attention is paid to avoidance or corresponding measures are taken.
3) Closed state: indicating that the path is completely closed, cannot be passed, and requires the selection of other paths or the alternative.
4) Limit traffic state: the representation path has some limiting conditions, such as speed limit, weight limit and the like, and related regulations need to be complied with.
It should be noted that, the path usage status data may be determined, recorded and updated according to the usage status of the path, and by determining the path usage status data in the predetermined power station area, a decision maker, a task scheduling system, etc. may help to understand the usage status of different paths in the predetermined power station area, so as to make reasonable path selection and task scheduling decisions, which is helpful to optimize task execution efficiency, avoid congestion and delay, and improve overall traffic smoothness and safety.
Step S110, determining path design data corresponding to the preset power station area according to the path use state data.
In the step S110 of providing the present application, the path design data refers to an actual road design, the path data related to the area in the path usage status data may be screened out according to the range of the predetermined power station area, for the step, the corresponding path design data may be determined according to the path usage status data, and then the path meeting the requirement of the predetermined power station area may be selected according to the traffic capacity, the obstacle information, the limitation condition, etc. in the path usage status data, or the path may be weighted and selected according to the traffic capacity, the influence range of the obstacle, and the limitation condition, and the path design may be performed based on the selected path, for example: the collection of task routes of each employee can be counted, the geographical route collection in the task routes of the employees is compared with the roads in the website map library, the use information collection and the non-existing route collection of the existing roads are obtained, the non-existing route collection comprises the intersection of the task execution routes of the employees and the roads in the website map library, and the route design data corresponding to the preset power station area can be determined according to the use information collection and the non-existing route collection of the existing roads.
It should be noted that, by determining the path design data corresponding to the predetermined power station area, reference and basis can be provided for path construction and planning, which is helpful for optimizing the layout of the path network, improving the traffic efficiency, and ensuring that the paths in the predetermined power station area meet the safety requirements and the traffic fluency.
Determining a predetermined power station area through the steps S102-S110, wherein the predetermined power station area comprises a predetermined power station and an area which is a predetermined range from the predetermined power station; the method comprises the steps of calling terrain data corresponding to a preset power station area and task scheduling data of a target object, wherein the task scheduling data comprise the target task, and the target object is an object for executing the target task in the preset power station area; according to the topographic data and the task scheduling data, the predicted route data of the target object for executing the target task is determined, and the route using state data in the preset power station area is determined according to the predicted route data, so that the purpose of determining the route design data corresponding to the preset power station area according to the route using state data is achieved. The predicted route data is determined according to the topographic data and the task scheduling data, and task execution, path selection and resource allocation are optimized through the determined predicted route data, so that the task efficiency and success rate are improved, and the technical problems that when an object located in a preset power station area executes the task in the related technology, the road through which the task is executed is possibly tedious and disordered, and the task execution efficiency of the object is low are solved.
As an alternative embodiment, determining predicted route data of a target object for executing a target task according to terrain data and task scheduling data includes: dividing a preset power station area to obtain a plurality of sub power station areas; determining sub-area topographic data corresponding to the plurality of sub-power station areas respectively; and determining predicted route data of the target object for executing the target task according to the sub-region topographic data and the task scheduling data which correspond to the sub-region topographic data and the task scheduling data respectively, wherein the predicted route data comprises region data of sub-power station regions through which the target object sequentially passes and time data of the target object passing through the corresponding sub-power station regions.
In this embodiment, the entire power station area is divided into a plurality of sub-power station areas based on the scale and demand of a predetermined power station, and the sub-power station areas may be divided according to the functional demand, geographical position, and the like within the power station; for each sub-power station area, acquiring corresponding topographic data comprising topographic data in the sub-power station area; carefully analyzing task scheduling data, knowing the requirements of a target task and a target object, and determining the task which the target object needs to execute in a preset power station area and the corresponding task execution time; combining the topographic data and the task scheduling data of the sub-power station area to conduct route planning; according to task requirements and topography characteristics, calculating predicted route data of the target object in each sub-power station area, wherein the predicted route data comprises area data and time data of the sub-power station area through which the target object passes; combining the predicted route data of each sub-power station area to generate final predicted route data; the method comprises the steps of sequentially passing region data of the sub-power station regions through which the target object passes and time data of the target object passing through the corresponding sub-power station regions.
It should be noted that, through the above steps, the predicted route data of the target object for executing the target task may be obtained, where the predicted route data includes the area data and the time data of the target object in each sub-power station area, and the predetermined power station area, the sub-power station area, and the predicted route data is helpful for planning and scheduling the target task, so as to effectively improve the execution efficiency of the target task, and ensure the efficient completion of the task.
As an alternative embodiment, determining predicted route data of a target object for executing a target task according to terrain data and task scheduling data includes: calling a preset prediction route library corresponding to the topographic data; in the case where predicted route data corresponding to the target task exists in the predetermined predicted route library, predicted route data for the target object to execute the target task is determined.
In this embodiment, the predicted route library may include route data under different terrain conditions, and may be constructed based on historical data, simulation data, or expertise.
For the above steps, according to the task scheduling data, specific requirements and execution conditions of the target task are determined, a predetermined prediction route library is searched for, whether the prediction route data corresponding to the target task exists is determined, if the prediction route data corresponding to the target task exists in the prediction route library, the prediction route data of the target object for executing the target task can be determined, the prediction route data can include information such as a route, a key point, a driving mode and the like, and if the prediction route data corresponding to the target task is not found, real-time route planning may need to be performed or new prediction route data may need to be generated by using other algorithms. The real-time path planning may generate new predicted route data using a path planning algorithm based on current terrain data and mission scheduling data.
It should be noted that, by calling a predetermined predicted route library corresponding to the topographic data and determining whether the target task has corresponding predicted route data in the library, a reference of a predicted route can be provided for the target object to execute the target task, which is helpful for optimizing decisions such as path selection and task scheduling, and improves the execution efficiency and safety of the target task.
As an alternative embodiment, after determining the predicted route data of the target object for executing the target task according to the topographic data and the task scheduling data, the method further includes: determining real-time route data when a target object executes a target task; and under the condition that the route corresponding to the route deviation prediction route data corresponding to the real-time route data exceeds a preset deviation index, determining the residual route data of the target object for executing the target task according to the terrain data, the task scheduling data and the real-time route data.
In this embodiment, based on predicted route data and real-time data (real-time traffic data, sensor data, etc.), real-time route data when a target object performs a target task is calculated, the real-time route data taking into consideration current traffic conditions, dynamic environmental factors, etc. to adjust original predicted route data, and then the real-time route data is compared with the predicted route data to check whether there is a route deviation, which may be caused by traffic congestion, road closure, etc.; judging the deviation degree between the real-time route data and the predicted route data according to the preset deviation index, and if the route deviation exceeds the preset deviation index, further processing is needed; determining remaining route data of the target object for executing the target task: in case the route deviation exceeds a predetermined index, planning and generation of the remaining route is performed according to the topographic data and the task scheduling data, which may be real-time path planning, using the real-time topographic data and the task scheduling data, generating new route data of the target object from the deviation point to the target point.
By the steps, the real-time route data of the target object when executing the target task can be determined, and the residual route data is determined according to the topographic data and the task scheduling data under the condition that the route deviation exceeds the preset index, so that the route of the target object can be adjusted in time under the condition that the route is changed or unexpected, the smooth completion of the task is ensured, and meanwhile, the flexibility and the adaptability of the route planning can be improved through the generation of the real-time route data and the residual route data.
As an alternative embodiment, determining predicted route data of a target object for executing a target task according to terrain data and task scheduling data includes: the method comprises the steps of inputting terrain data and task scheduling data into a route prediction model to obtain predicted route data of a target object for executing a target task, wherein the route prediction model is obtained by training an initial model according to sample data, and the sample data comprises: sample topography data, sample task scheduling data, and sample route data for a sample object to perform a sample task.
In this embodiment, the route prediction model is obtained by training an initial model according to sample data, wherein the sample data includes terrain data, sample task scheduling data, and sample route data of a sample object for executing a sample task, and the specific process is as follows: collecting a group of sample data, wherein the sample data comprises sample topography data, sample task scheduling data and sample route data for executing sample tasks by corresponding sample objects, the sample topography data comprises information such as topography height, topography type and the like, the sample task scheduling data comprises information such as task requirements, execution time and the like, and the sample route data comprises passing areas, paths and the like; the method comprises the steps of combining sample terrain data, sample task scheduling data and sample route data to generate a training data set, training an initial model by using a proper machine learning algorithm based on the sample data set to obtain a route prediction model, and finally inputting actual terrain data and task scheduling data into the trained route prediction model, wherein the route prediction model can convert the input terrain data and task scheduling data into predicted route data of a target object for executing a target task, and the predicted route data can comprise information such as paths, key points, running modes and the like.
It should be noted that, by inputting the topographic data and the task scheduling data into the route prediction model, the predicted route data of the target task for executing the target object can be obtained, which is conducive to path planning and scheduling based on the topographic data and the task data, so as to improve the execution efficiency and accuracy of the task, thereby optimizing the path planning, enhancing the task execution capacity, improving the safety, optimizing the resource allocation, and being conducive to improving the task execution efficiency, reducing the cost and providing a more reliable task execution result.
As an alternative embodiment, after determining the path usage status data within the predetermined power station area based on the predicted route data, the method further comprises: determining idle path data according to path use state data in a preset power station area, wherein the idle path data is data corresponding to an idle path, and the idle path is a path with a path occupation index smaller than a preset threshold value; and determining the next task allocated to the target object according to the idle path data.
In this embodiment, for the above steps, the above path usage status data may be implemented by means of sensors, monitoring devices, task execution records, and the like. The path use state data can comprise information such as an occupation index, an occupation time, an occupation frequency and the like of the path; and screening out the idle path data by comparing the use states of the paths, wherein the idle path refers to a path with the occupied index smaller than a preset threshold value, namely a path which is rarely occupied or unoccupied.
It should be noted that, firstly, path usage status data in a predetermined power station area needs to be collected, according to the path usage status data, an occupation index of each path can be calculated, a predetermined threshold value is set, paths with occupation indexes smaller than the predetermined threshold value are screened out, and the paths are idle paths; based on the idle path data, a next task assigned to the target object may be determined. This may be determined based on factors such as task priority, location of the target object, task type, etc., for example, a free path that is closer to the current location of the target object and that has a minimum occupancy index may be selected and then taken as the route for the next task.
It should be noted that, through the above steps, idle path data can be determined according to the path usage status data in the predetermined power station area, and a next task is allocated to the target object according to the idle path data, where the selection of the idle path can take into account factors such as reliability of the path, time saving, and resource saving, so as to maximize efficiency and quality of task execution, to a certain extent, the idle path data can be utilized more effectively, and efficiency and accuracy of task allocation are improved.
As an alternative embodiment, determining path design data corresponding to a predetermined power station area based on path usage status data includes: under the condition that the road to be designed is included in the path design data, determining non-existing road data according to the path use state data in the preset power station area, wherein the non-existing road data is data corresponding to the non-existing road, and the non-existing road is a path which is not an actual road in the preset power station area; and determining the road to be designed according to the non-existing road data.
In this embodiment, for the above steps, path usage status data within the predetermined power station area needs to be collected to know which paths already exist, are in use, and which paths are not covered by the actual road; and secondly, screening out paths which are not actual roads in the preset power station area according to the path use state data, wherein the paths are the non-existing roads. The non-existing road data may include information of a start point, an end point, a length, etc. of the path; planning of the road to be designed is performed based on the non-existing road data, which may involve layout of new roads, expansion or improvement of paths, etc. When designing a road to be designed, the use condition of other paths in the path use state data can be considered to optimize the road design and meet the task requirements in a preset power station area; and finally, combining the road data to be designed with the existing path design data to form a new path design data set, wherein the data set comprises complete path design information aiming at the road to be designed in a preset power station area and is used for task scheduling and path planning.
It should be noted that, through the above steps, it is possible to determine path design data corresponding to a predetermined power station area according to the path use state data, the non-existing road data reflecting the condition of a path which does not exist in the predetermined power station area, and the road to be designed is a new road planned and designed based on the non-existing road data. By considering the condition of the road to be designed and determining that no road data exists by utilizing the path use state data in the preset power station area, comprehensive information can be obtained in the path design, flexibility is enhanced, path planning is optimized, reasonable allocation of resources is realized, the quality and efficiency of the path design are improved to a certain extent, and the smooth execution of tasks in the power station area is ensured.
Based on the foregoing embodiments and optional embodiments, an optional implementation is provided, and is specifically described below.
In the related art, since the setting of the power station is generally in a remote area and the site is large, when the staff performs tasks, the tasks are often arranged and planned according to experience and personal judgment, and the planning method relies on personal experience, so that the newly constructed site or the newly entered staff needs to be familiar with the searching process, the problem of difficult target position finding can occur due to detour in a long time, especially for the newly constructed site, the map updating is relatively slow, and some secret-related problems are involved, the specific functions of many areas are not suitable for disclosure, and the reliability of information provided by navigation is relatively low. Thus, problems of reducing work efficiency and even delaying engineering progress may occur.
In view of this, an alternative embodiment of the present application provides a method for determining path design data of a power station area, and the alternative embodiment of the present application is described in detail below.
S1, determining a preset power station area and preset power stations included in the preset power station area;
it should be noted that the predetermined power station area may be selected according to the following manners, for example: selecting power stations and surrounding field areas as basic plane plots, defining and storing the basic plane plots, dividing the basic plane plots to obtain primitive plane plots, naming and describing each primitive plane plot, taking a set of all primitive plane plots as the basic plane plots, calling a Geographic Information System (GIS) system to obtain the height corresponding to each primitive plane plot, establishing a net point map library, and directly selecting a map in a certain range according to the area selection of the power grid design, wherein the area range generally selected is more than 4 times of the actually-related area range. The basic plane block is divided by a Thiessen polygon cutting method, in operation, a geographic information system (Arcgis) can be applied to cut the basic plane block into a plurality of primitive plane blocks, a differential concept is applied to divide a related map, each primitive label is required to be expressed in a form of a pure number by a certain logic relation such as a model label through coordinates, etc., a selected area is expressed in a form of a pure number, each primitive information can be expressed clearly by a mode of arbitrarily selecting or selecting an average value from an elevation data set corresponding to each primitive by the elevation data of the geographic information system, if each primitive is marked by a single number, the corresponding primitive is described to be clear, the longitudinal height information is only required to be increased, and if each primitive is marked by coordinates, the coordinate information and the longitudinal height information are required, wherein the primitive represents the primitive plane block.
S2, calling topographic data corresponding to the preset power station area and task scheduling data of staff;
the topographic data may be topographic data included in the predetermined power station area, the task scheduling data of the staff may be data corresponding to executing a certain task in the predetermined power station area, and the calling process may be: the method comprises the steps of calling staff task execution information, combining the staff task execution information with a website map library to obtain a three-dimensional task route map of staff, recording the staff task execution route in a plane map, finding a primitive plane plot at a corresponding position in a path of the plane map, and expressing the staff task execution route by combining primitive data in the website map library, wherein, if the expression that the staff task execution route advances to a certain position at a certain moment is expressed by adding a corresponding time array form to the primitive, the time array form is not required to be managed, and the time array arrangement order is not required to be managed.
S3, inputting the topographic data and the task scheduling data into a route prediction model, retrieving a preset predicted route library corresponding to the topographic data, and obtaining predicted route data of the staff executing the target task under the condition that the predicted route data corresponding to the target task exists in the preset predicted route library;
the method includes the steps of dividing the preset power station area to obtain a plurality of sub-power station areas, determining sub-area terrain data corresponding to the sub-power station areas respectively, and further determining predicted route data of staff executing a target task, wherein the specific mode is as follows:
the method comprises the steps of calling staff task execution information, combining the staff task execution information with a website map library to obtain a three-dimensional task route map of staff, recording the staff task execution route in a plane map, finding a primitive plane plot at a corresponding position in a path of the plane map, and expressing the staff task execution route by combining primitive data in the website map library, wherein, if the expression that the staff task execution route advances to a certain position at a certain moment is expressed by adding a corresponding time array form to the primitive, the time array form is not required to be managed, and the time array arrangement order is not required to be managed.
After the predicted route data are determined, determining real-time route data when the staff performs a target task; and under the condition that the route corresponding to the route deviation prediction route data corresponding to the real-time route data exceeds a preset deviation index, determining the residual route data of the target object for executing the target task according to the terrain data, the task scheduling data and the real-time route data.
S4, determining path use state data in a preset power station area according to the predicted route data;
after determining the path usage status data in the predetermined power station area, determining idle path data according to the path usage status data in the predetermined power station area, where the idle path data is data corresponding to the idle path, the idle path is a path with a path occupation index smaller than a predetermined threshold, and determining a next task allocated to the employee according to the idle path data.
The above steps can be described as: describing a task route of the staff by applying the name of each primitive plane block and combining task time, and describing the task route as a primitive of a staff task execution route; the staff information, the travel and the task information can be expressed through an array by calling staff information such as the position, the sex, the age, the time of entering the staff, the staff number information and the like, and a machine learning algorithm is used for establishing the relation among the staff information, so that when the staff performs the task each time, the staff only needs to input the personal identity information, for example, the staff information can be input through a mode of a staff card and a mode of a card swiping, the staff information can be input through Bluetooth or radio frequency and the like, then the task to be performed is described and input, the system extracts keywords in the description according to the codes of each task and displays the keywords to the staff for confirmation, and a path recommendation is formed by applying a relation model after the confirmation. When a worker executes a task, the carrying instrument records own track information, the track information element and the time array set represent the track information, after the task is completed, the worker sends the track information to a background system, and the background system compares a deduction result with an actual task according to staff information and travel reverse-pushing task information, so that self supervision is realized, and the model is perfected.
In addition, professional ability of staff can be scored according to usual staff work results and unit assessment standards, and even the ability of staff to do different tasks can be scored artificially, the ability scoring standard is manually specified according to the situation of units, discussion is not involved in the application, and only the ability of staff can be primarily quantified by parameters so as to facilitate system statistics. The information is used as parameters to quantify the identity of staff, then the information of tasks executed by the staff is obtained, and each task is quantitatively marked, such as a maintenance task mark 3, a switch task mark 11 and a line detection task mark 7; meanwhile, different devices are marked with marks, such as a transformer mark 102, a switch mark 107 and the like, namely when staff inputs tasks to be executed, the system needs to be converted into corresponding digital information.
S5, determining path design data corresponding to the preset power station area according to the path use state data.
When the route design data includes a road to be designed, determining non-existing road data according to route use state data in a predetermined power station area, wherein the non-existing road data is data corresponding to the non-existing road, and the non-existing road is a route which is not an actual road in the predetermined power station area; and determining the road to be designed according to the non-existing road data, namely counting the set of the task routes of each employee, comparing the geographical route set in the task routes of the employees with the roads in the site map library to obtain the use information set and the non-existing route set of the existing roads, wherein the non-existing route set comprises the intersection of the task execution route exclusion of the employees and the roads in the site map library.
In the above steps, the serial numbers corresponding to the primitive planar plots used in the task execution process of each employee need to be called, firstly, each task route is screened, routes with abnormal data are selected, then, the frequency of each primitive label is counted, the occurrence frequency of each primitive is marked in the basic planar plots, the occurrence frequency is high, the positions pass through the frequency, the use information of the roads can be obtained through the frequency data, and compared with the roads which exist actually, the use frequency is high, but the positions corresponding to the primitives which do not exist actually are marked, so that the positions possibly serve as the roads, the working efficiency is improved, or the label is omitted in the map, and a designer or manager can examine or repair the roads or modify the map data based on the routes.
It should be further noted that, for the whole steps described above, a three-dimensional visualization management system may be designed, which includes: the system comprises a station, an in-station analysis end and a patrol end, wherein the station analysis end and the patrol end are arranged in a power station, the patrol end is carried by staff, the station comprises a Geographic Information System (GIS) information disclosure library, the GIS information disclosure library is connected with an external network through a network and is used for acquiring GIS information, the GIS information disclosure library is connected with a first site map library in a communication manner, the GIS information disclosure library and the first site map library are stored in different hardware storage devices, the station analysis end and the station analysis end also comprise a front control module, the front control module is in signal connection with the first site map library, and the front control module is used for processing data in the first site map library;
The in-station analysis end is connected with the front-end calculation end in an information manner, the in-station analysis end is used for processing data of the front-end calculation end and the inspection end, the in-station analysis end comprises an in-station memory and a model control module, the in-station memory comprises a second website map library, a task behavior library, a temporary line library, a task route library, a task model rule library, a learning algorithm library and a model control module, and the in-station memory is connected with the model control module;
the inspection terminal comprises a mobile memory and an inspection control module, wherein the mobile memory comprises a third website map library, a task storage library, a line generation library and a planning line library, and is connected with the inspection control module which is also applied with a positioning system.
The GIS information disclosure library and the first site map library can not directly realize information transfer by transmitting information through hardware equipment or adding a secret key in a transmission path.
By applying the system in the application, the front-end computing end, the in-station analysis end and the inspection end can be simply understood as three platforms or three computers, the memory in each terminal is divided into a plurality of areas according to the storage content, and each control module can comprise a display card, a singlechip, a processor, a memory and the like. The GIS information disclosure library in the front-end computing end can be externally connected with a network, GIS information is acquired and downloaded into the GIS information disclosure library of the system, the front-end control module segments GIS map data downloaded from the GIS information disclosure library, the scheme is characterized in that basic plane land parcels are segmented, map data are expressed in a differential mode, a three-dimensional map is described by using minimum information, the segmented data are stored into a first site map library, a second site map library and a third site map library, each site map library is mutually connected, when the map library is modified, updating is carried out from the first site map library or the second site map library, and then updated data are sent to other site map libraries. The front-end computing end, the in-station analysis end and the inspection end are also provided with communication modules, so that information interaction can be carried out by means of an internal wireless network, and a communication mode can be selected according to actual engineering conditions. And the in-station analysis end collects data of the front-end calculation end and the inspection end, trains a path model and obtains path suggestions under different tasks and combinations. The inspection terminal is provided with a navigation positioning system, and is generally used for positioning by means of a Beidou satellite navigation system (BDS) and recording and generating path traces when staff execute tasks, so that the in-station analysis terminal can conveniently learn. The data of the inspection end and the data of the front-end computing end are mutually exchanged, the front-end computing end schedules corresponding path planning for staff by means of a relation model according to tasks, the path planning is sent to the inspection end, the inspection end is provided with an image conversion module and a man-machine interaction module, the path data can be converted into images, and then the images are displayed at a screen of the inspection end.
The visual management system further comprises: downloading GIS data to a GIS information disclosure library, transmitting the GIS data to a first network point map library, marking a proper range of power grid maintenance at a map data position by a front control module as a basic plane block, separating the selected basic plane block to obtain a primitive plane block set, naming each primitive plane, marking the altitude of each primitive plane block according to the GIS data, using a corresponding altitude amount for each primitive plane block, correspondingly placing the marked set of primitive plane blocks at the basic plane block, stretching the altitude to form three-dimensional map data, and storing the three-dimensional map data in the first network point map library, the second network point map library and the third network point map library;
when an employee executes a task, carrying a patrol end, inputting personal job information, task information and a target place into a task storage library by means of a man-machine interaction module of the patrol end, recording the starting time of task execution, after a positioning system is started by a front control module after the starting is triggered, recording an employee route in real time by combining time information to obtain employee task execution information, calling a second site map library by the front control module, describing path information of each time point by using a corresponding primitive plane land parcel name as primitive, storing primitive descriptions into a route generation library, and sending the employee task execution information and the corresponding primitive descriptions in the task storage library to an in-station analysis end by the front control module;
The in-station analysis end model control module stores primitive descriptions of paths of staff collected by the inspection end in a task route library to obtain a path set of the staff, compares existing paths in a map, eliminates the existing paths from the collected path set of the staff to obtain an inexistent path set, obtains suggestions of new roads according to the repetition degree of used primitive planar plots, counts the use condition of each time period of each path, stores the use condition in the task route library, and marks the use condition for management staff.
The model control module in the in-station analysis end stores each employee task execution information collected by the inspection end into a task behavior library, and stores primitive descriptions into a task line library, and the model control module calls a second website map library, a task behavior library, a task route library and a learning algorithm library to perform machine learning training on each employee task execution information and the corresponding primitive descriptions, generates a relation model for establishing task types and primitive descriptions, gives path suggestions for task selection, and stores the relation model described by the task types and the primitives into a task model rule library.
The staff inputs the identity information and the task to be executed to the inspection end, inputs the identity information and the task to be executed to a temporary line library in the in-station analysis end through an internal network, and the front control module invokes a relation model in a task model rule library to give a suggested line of the task to be executed and stores the suggested line into the temporary line library;
After the staff completes the task, the staff task execution information and the actual path are input into a task line library, a front control module calls a relation model in a task model rule library, the executed task information is reversely pushed, and self-supervision learning is realized through the comparison of the result of the reversely pushed task information and the actual path.
The in-station analysis end further comprises an in-station image conversion module, the in-station image conversion module calls primitive descriptions of suggested routes corresponding to task types stored in the second website map library and the temporary line library, converts the primitive descriptions into image data and sends the image data to the inspection end, and the suggested three-dimensional task path map is intuitively displayed through a man-machine interaction module of the inspection end.
By the alternative embodiments, at least the following advantages can be achieved:
(1) The topographic data can be obtained from the preset power station area through measurement by corresponding equipment, namely, a planner can be helped to better know the topographic characteristics of the preset power station area to a certain extent, so that path planning is carried out, an optimal execution path is selected, and the task execution efficiency is improved;
(2) Since the task scheduling data may include the task type, task description, task time limit, execution place, priority, and related attributes of the target object, i.e., through the task scheduling data, the planner can better understand the characteristics and requirements of the task, and can reasonably arrange and schedule the task based on the information. Therefore, the efficiency of task execution can be improved, the task can be completed on time, and available resources can be utilized to the maximum extent;
(3) The predicted route data is determined according to the topographic data and the task scheduling data, namely, the determined predicted route data can provide a known guide for the execution of the target task, thereby being beneficial to optimizing the task execution, the path selection and the resource allocation and improving the efficiency and the success rate of the task;
(4) The path state use data is determined according to the predicted route data, namely, the path use state data in the preset power station area is determined, so that a decision maker, a task scheduling system and the like can be helped to know the use conditions of different paths in the preset power station area so as to make reasonable path selection and task scheduling decisions, the task execution efficiency is improved, congestion and delay are avoided, and the overall traffic smoothness and safety are improved.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present invention.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of the various embodiments of the present invention.
Example 2
According to an embodiment of the present invention, there is also provided an apparatus for implementing the above-mentioned path design data determining method of a power station area, and fig. 2 is a block diagram of a path design data determining apparatus of a power station area according to an embodiment of the present invention, as shown in fig. 2, the apparatus includes: the first determination module 202, the invoking module 204, the second determination module 206, the third determination module 208, and the fourth determination module 210 are described in detail below.
A first determining module 202, configured to determine a predetermined power station area, where the predetermined power station area includes a predetermined power station and an area within a predetermined range from the predetermined power station;
a retrieving module 204, coupled to the first determining module 202, for retrieving topographic data corresponding to a predetermined power station area, and task scheduling data of a target object, where the task scheduling data includes a target task, and the target object is an object that performs the target task in the predetermined power station area;
a second determining module 206, coupled to the retrieving module 204, for determining predicted route data of the target object for executing the target task according to the topographic data and the task scheduling data;
a third determining module 208, coupled to the second determining module 206, for determining path usage status data in the predetermined power plant area according to the predicted path data;
a fourth determining module 210, coupled to the third determining module 208, for determining path design data corresponding to the predetermined power station area according to the path usage status data.
It should be noted that the first determining module 202, the calling module 204, the second determining module 206, the third determining module 208 and the fourth determining module 210 correspond to steps S102 to S110 in the path design data determining method for implementing the power station area, and the plurality of modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in the foregoing embodiment 1.
Example 3
According to another aspect of the embodiment of the present application, there is also provided an electronic device including: a processor; a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the path design data determination method of the utility region of any one of the above.
Example 4
According to another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform the path design data determination method of the power station area of any one of the above.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims (10)

1. A method for determining path design data for a power plant area, comprising:
determining a predetermined power station area, wherein the predetermined power station area comprises a predetermined power station and an area with a predetermined range from the predetermined power station;
invoking terrain data corresponding to the preset power station area and task scheduling data of a target object, wherein the task scheduling data comprises a target task, and the target object is an object for executing the target task in the preset power station area;
determining predicted route data of the target object for executing the target task according to the terrain data and the task scheduling data;
determining path use state data in the preset power station area according to the predicted route data;
and determining path design data corresponding to the preset power station area according to the path use state data.
2. The method of claim 1, wherein determining predicted route data for the target object to perform the target task based on the terrain data and the task scheduling data comprises:
dividing the preset power station area to obtain a plurality of sub-power station areas;
determining sub-area topographic data corresponding to the plurality of sub-power station areas respectively;
and determining predicted route data of the target object for executing the target task according to the sub-region topographic data and the task scheduling data which correspond to the sub-region topographic data and the task scheduling data, wherein the predicted route data comprises region data of sub-power station regions through which the target object sequentially passes and time data of the target object passing through the corresponding sub-power station regions.
3. The method of claim 1, wherein determining predicted route data for the target object to perform the target task based on the terrain data and the task scheduling data comprises:
calling a preset prediction route library corresponding to the topographic data;
and determining the predicted route data of the target object for executing the target task under the condition that the predicted route data corresponding to the target task exists in the preset predicted route library.
4. The method of claim 1, wherein after determining the predicted route data for the target object to perform the target task based on the terrain data and the task scheduling data, further comprising:
determining real-time route data when the target object executes the target task;
and under the condition that the route corresponding to the route deviation prediction route data corresponding to the real-time route data exceeds a preset deviation index, determining the residual route data of the target object for executing the target task according to the terrain data, wherein the task scheduling data and the real-time route data.
5. The method of claim 1, wherein determining predicted route data for the target object to perform the target task based on the terrain data and the task scheduling data comprises:
inputting the terrain data and the task scheduling data into a route prediction model to obtain predicted route data of the target object for executing the target task, wherein the route prediction model is obtained by training an initial model according to sample data, and the sample data comprises: sample topography data, sample task scheduling data, and sample route data for a sample object to perform a sample task.
6. The method of claim 1, wherein after determining path usage status data within the predetermined power plant area based on the predicted route data, further comprising:
determining idle path data according to path use state data in a preset power station area, wherein the idle path data is data corresponding to an idle path, and the idle path is a path with a path occupied index smaller than a preset threshold value;
and determining the next task allocated to the target object according to the idle path data.
7. The method according to any one of claims 1 to 6, wherein the determining path design data corresponding to the predetermined power station area based on the path usage status data includes:
under the condition that the path design data comprise a to-be-designed road, determining non-existing road data according to path use state data in a preset power station area, wherein the non-existing road data are data corresponding to the non-existing road, and the non-existing road is a path which is not an actual road in the preset power station area;
and determining the road to be designed according to the non-existing road data.
8. A path design data determining apparatus for a power station area, comprising:
a first determining module, configured to determine a predetermined power station area, where the predetermined power station area includes a predetermined power station and an area within a predetermined range from the predetermined power station;
the scheduling module is used for scheduling the topographic data corresponding to the preset power station area and the task scheduling data of a target object, wherein the task scheduling data comprises a target task, and the target object is an object for executing the target task in the preset power station area;
the second determining module is used for determining predicted route data of the target object for executing the target task according to the topographic data and the task scheduling data;
the third determining module is used for determining path use state data in the preset power station area according to the predicted route data;
and the fourth determining module is used for determining path design data corresponding to the preset power station area according to the path use state data.
9. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
Wherein the processor is configured to execute the instructions to implement the path design data determination method of a power plant area as claimed in any one of claims 1 to 7.
10. A computer readable storage medium, characterized in that instructions in the computer readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the path design data determination method of a power station area according to any one of claims 1 to 7.
CN202311110434.2A 2023-08-30 2023-08-30 Path design data determining method and device for power station area and electronic equipment Pending CN117151320A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311110434.2A CN117151320A (en) 2023-08-30 2023-08-30 Path design data determining method and device for power station area and electronic equipment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311110434.2A CN117151320A (en) 2023-08-30 2023-08-30 Path design data determining method and device for power station area and electronic equipment

Publications (1)

Publication Number Publication Date
CN117151320A true CN117151320A (en) 2023-12-01

Family

ID=88911289

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202311110434.2A Pending CN117151320A (en) 2023-08-30 2023-08-30 Path design data determining method and device for power station area and electronic equipment

Country Status (1)

Country Link
CN (1) CN117151320A (en)

Similar Documents

Publication Publication Date Title
CN109754594B (en) Road condition information acquisition method and equipment, storage medium and terminal thereof
Li et al. Unmanned aerial vehicle scheduling problem for traffic monitoring
CN113538898A (en) Multisource data-based highway congestion management and control system
CN110705747A (en) Intelligent public transport cloud brain system based on big data
Ram et al. SMARTBUS: A web application for smart urban mobility and transportation
CN112016735B (en) Patrol route planning method and system based on traffic violation hotspot prediction and readable storage medium
CN113570867B (en) Urban traffic state prediction method, device, equipment and readable storage medium
CN110807917A (en) Highway intelligent security system based on cloud calculates
CN111445369A (en) Urban large-scale gathering activity intelligence early warning method and device based on L BS big data
CN103218694A (en) Power emergency monitoring method and system
CN113988476A (en) Dynamic assessment prediction method for road transportation safety risk
CN110021161B (en) Traffic flow direction prediction method and system
CN114363316A (en) Intelligent networking monitoring and supervision system for cross-regional road infrastructure
Ma et al. Public transportation big data mining and analysis
CN113554263A (en) Highway construction organization scheme traffic influence assessment method based on traffic simulation
CN114596709B (en) Data processing method, device, equipment and storage medium
William et al. Edge based Web Computing for Traffic Control Management for Distributed Environment Conditions
CN108447257B (en) Web-based traffic data analysis method and system
CN114298493A (en) Road operation monitoring system, method, terminal and storage medium
CN116975785B (en) Multi-source heterogeneous data fusion analysis method and system based on CIM model
Kolosz et al. A macroscopic forecasting framework for estimating socioeconomic and environmental performance of intelligent transport highways
KR102359902B1 (en) Crossroads LOS Prediction Method Based on Big Data and AI, and Storage Medium Having the Same
CN117151320A (en) Path design data determining method and device for power station area and electronic equipment
CN115440044A (en) Road multi-source event data fusion method and device, storage medium and terminal
Adrees et al. A proposed framework for using GIS to enhance traffic safety in Sudan: a case study

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination