WO2022143017A1 - 一种交通数据仓库的构建方法、装置、存储介质及终端 - Google Patents

一种交通数据仓库的构建方法、装置、存储介质及终端 Download PDF

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Publication number
WO2022143017A1
WO2022143017A1 PCT/CN2021/135717 CN2021135717W WO2022143017A1 WO 2022143017 A1 WO2022143017 A1 WO 2022143017A1 CN 2021135717 W CN2021135717 W CN 2021135717W WO 2022143017 A1 WO2022143017 A1 WO 2022143017A1
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monitoring
task
spatial
target
monitoring object
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PCT/CN2021/135717
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English (en)
French (fr)
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郭胜敏
李运才
杨珍珍
张瑞龙
李睿
聂巧炜
夏曙东
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北京千方科技股份有限公司
北京掌行通信息技术有限公司
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Priority to US18/014,048 priority Critical patent/US20230267830A1/en
Publication of WO2022143017A1 publication Critical patent/WO2022143017A1/zh

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G08G1/0133—Traffic data processing for classifying traffic situation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21—Design, administration or maintenance of databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3051—Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/23—Updating
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/485—Task life-cycle, e.g. stopping, restarting, resuming execution
    • 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
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons

Definitions

  • the invention relates to the technical field of intelligent transportation, in particular to a construction method, device, storage medium and terminal of a traffic data warehouse.
  • Road transportation plays an important role in my country's economic and social development. Maintaining the stable and efficient operation of the road transportation network is of great significance for adjusting the industrial structure, promoting employment and economic development, and accelerating the process of urban-rural integration.
  • road traffic incidents have occurred frequently and have a great social impact, and the operating pressure of the road network to ensure the smoothness of the road network continues to increase.
  • monitoring tasks have differences in their corresponding monitoring business types, temporal and spatial scope, monitoring objects, and monitoring indicators; further, monitoring objects and monitoring temporal and spatial scope, monitoring business and monitoring indicators, and different monitoring tasks
  • monitoring business and monitoring indicators There is a complex coupling relationship, which poses a great challenge to the construction of road network operation management and service platform. How to better support the ability expansion of the business platform through the efficient organization and management of background data, and make it further adapt to various road network management tasks, is a very worthwhile research topic.
  • the embodiments of the present application provide a construction method, device, storage medium and terminal for a traffic data warehouse.
  • a brief summary is given below. This summary is not intended to be an extensive review, nor is it intended to identify key/critical elements or delineate the scope of protection of these embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the detailed description that follows.
  • an embodiment of the present application provides a method for constructing a traffic data warehouse, the method comprising:
  • the index calculation result is configured into the monitoring object after setting the label, and the configured monitoring object is distributed to the task database corresponding to the target monitoring task.
  • calculate the spatial belonging relationship between the spatial scope of each acquisition unit in the collection unit set and the spatial scope of the target monitoring task including:
  • each acquisition unit is marked as belonging to the target monitoring task.
  • calculate the spatial belonging relationship between the spatial scope of each acquisition unit in the collection unit set and the spatial scope of the target monitoring task including:
  • the second spatial attribute description of each acquisition unit in the collection unit set is acquired; wherein, the second spatial attribute description includes the second geometric figure; wherein, the geometric figures include points, lines and surfaces;
  • each acquisition unit is marked as belonging to the target monitoring task.
  • determine the spatial coupling relationship between the monitoring object and the target monitoring task according to the spatial belonging relationship including:
  • the spatial range corresponding to each of the acquisition units does not belong to the spatial range of the target monitoring task, it is determined that the monitoring object is not coupled to the target monitoring task space; or,
  • the spatial range corresponding to each acquisition unit belongs to the spatial range of the target monitoring task, it is determined that the monitoring object is spatially coupled to the target monitoring task; or,
  • the spatial range corresponding to the at least one acquisition unit belongs to the spatial range of the target monitoring task, it is determined that the monitoring object is partially spatially coupled to the target monitoring task.
  • set the calculation label and task label of the monitoring object based on the spatial coupling relationship including:
  • the monitoring object When the monitoring object is spatially coupled with the target monitoring task, acquire the collection unit set corresponding to the coupled part of the target monitoring task in the monitoring object, and generate the target monitoring object;
  • the task label of the target monitoring object is set as the task label of the target monitoring task, and the calculation label of the sampling unit corresponding to the target monitoring object is updated.
  • the method also includes:
  • the life cycle includes the task start time and task end time;
  • the task tag in the task tag in the configured monitoring object is cleared.
  • a target monitoring task based on the creation instruction including:
  • an embodiment of the present application provides an apparatus for constructing a traffic data warehouse, the apparatus comprising:
  • the monitoring task creation module is used to create a target monitoring task based on the creation instruction when the monitoring task creation instruction is received;
  • the acquisition unit acquisition module is used to load the monitoring object corresponding to the monitoring object category parameter set in the target monitoring task, and acquire the collection unit set of the monitoring object;
  • the target monitoring task space range acquisition module is used to obtain the target monitoring task space range corresponding to the monitoring task space range parameter set in the target monitoring task;
  • the spatial belonging relationship calculation module is used to calculate the spatial belonging relationship between the spatial range of each acquisition unit in the collection unit set and the spatial range of the target monitoring task;
  • the spatial coupling relationship determination module is used to determine the spatial coupling relationship between the monitoring object and the target monitoring task according to the spatial belonging relationship
  • the monitoring object generation module is used to set the calculation label and task label of the monitoring object based on the spatial coupling relationship, and generate the monitoring object after setting the label;
  • the monitoring index calculation result output module is used to input the monitoring object after setting the label into the preset monitoring service calculation function, and output the monitoring index calculation result;
  • the data sending module is used for configuring the index calculation result into the monitoring object after setting the label, and distributing the configured monitoring object to the task database corresponding to the target monitoring task.
  • an embodiment of the present application provides a computer storage medium, where the computer storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the above method steps.
  • an embodiment of the present application provides a terminal, which may include: a processor and a memory; wherein, the memory stores a computer program, and the computer program is adapted to be loaded by the processor and execute the above method steps.
  • the construction device of the traffic data warehouse first, when receiving the monitoring task creation instruction, creates the target monitoring task based on the creation instruction, and then loads the monitoring object corresponding to the monitoring object category parameter set in the target monitoring task, And obtain the collection unit set of the monitoring object, then obtain the target monitoring task space range corresponding to the monitoring task space range parameter set in the target monitoring task, and then calculate the space range of each collection unit in the collection unit set and the target monitoring task space range.
  • the spatial attribution relationship between the monitoring objects and the target monitoring task is determined according to the spatial attribution relationship, and then the calculation label and task label of the monitoring object are set based on the spatial coupling relationship, and the monitoring object after setting the label is generated.
  • the labeled monitoring object is input into the preset monitoring service calculation function, the monitoring index calculation result is output, and finally the index calculation result is configured into the labeled monitoring object, and the configured monitoring object is distributed to the target monitoring task corresponding to the in the task database. Because the application is based on the labeling method to reduce the coupling relationship in the road network operation and management business, it can flexibly meet the calculation requirements of different monitoring tasks on the monitoring index data at the background data level, solve the coupling problem in the monitoring data calculation process, and improve system service efficiency.
  • Fig. 1 is a kind of road network operation monitoring business model provided by the embodiment of the present application.
  • FIG. 2 is a coupling relationship diagram of a road network operation monitoring service provided by an embodiment of the present application
  • FIG. 3 is a schematic flowchart of a method for constructing a traffic data warehouse provided by an embodiment of the present application
  • FIG. 4 is a process schematic diagram of a construction process of a traffic data warehouse provided by an embodiment of the present application.
  • FIG. 5 is a schematic diagram of a logical model of a monitoring object provided by an embodiment of the present application.
  • FIG. 6 is a schematic diagram of an apparatus for constructing a traffic data warehouse provided by an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a terminal provided by an embodiment of the present application.
  • the present application provides a construction method, device, storage medium and terminal for a traffic data warehouse, so as to solve the problems existing in the above-mentioned related technical problems.
  • the application because the application is based on the labeling method to reduce the coupling relationship in the road network operation and management business, it can flexibly meet the calculation requirements of different monitoring tasks on monitoring index data at the background data level, and solve the problem of monitoring data.
  • the coupling problem in the calculation process improves the service efficiency of the system, and an exemplary embodiment is used to describe in detail below.
  • Figure 1 is the road network operation monitoring business model. Further analysis of Figure 1 shows that there are multiple coupling relationships within the monitoring unit, between the monitoring unit and the general system:
  • the monitoring object must satisfy the constraints of the spatiotemporal scope.
  • A does not meet the spatial range constraint of monitoring task x but B does, so B will be added to the data requirements of monitoring task x for the general system ;
  • the definition of the space-time range will affect the monitoring business and the calculation of monitoring indicators.
  • the range of the A object is not completely included in the spatial range of the monitoring task x, so the calculation of the monitoring index should be Limited to the spatial range of task x (the shaded part in the figure);
  • the present invention proposes a traffic data warehouse construction method for road network operation and management, which solves the coupling problem in the monitoring data calculation process.
  • the construction method of the traffic data warehouse provided by the embodiment of the present application will be described in detail below with reference to FIG. 3 to FIG. 5 .
  • the method can be realized by relying on a computer program, and can be run on the construction device of the traffic data warehouse based on the von Neumann system.
  • the computer program can be integrated into an application or run as a stand-alone utility application.
  • FIG. 3 provides a schematic flowchart of a method for constructing a traffic data warehouse according to an embodiment of the present application. As shown in FIG. 3, the method of this embodiment of the present application may include the following steps:
  • the monitoring task creation instruction is an instruction input by the user to the client, and the instruction includes multiple parameters for creating a monitoring task.
  • the multiple parameters include the monitoring task identifier id, the life cycle parameter of the monitoring task, the category parameter of the monitoring object in the monitoring task, and the spatial scope parameter of the monitoring task.
  • the multiple parameters are the monitoring task identifier id, the life cycle of the monitoring task, the category of the monitoring object in the monitoring task, and the spatial scope of the monitoring task.
  • the user when creating a monitoring task, the user first determines multiple parameters of the monitoring task, inputs the multiple parameters into the client, and then triggers the monitoring task creation function. After triggering the monitoring task creation function, the user terminal receives the monitoring task creation instruction, extracts multiple parameters contained in the monitoring task creation instruction, then obtains the preset monitoring task definition template tsk, and finally associates the multiple parameters with the monitoring task definition
  • the identifiers in the template tsk are correlated one by one to generate the final target monitoring task.
  • the set monitoring object type parameter is the parameter ⁇ mo.type in the tsk created in step S101 , the monitoring object belongs to a monitoring task, and a monitoring task may include multiple monitoring objects.
  • the collection unit set belongs to the monitoring object, and a monitoring object includes one or more collection units.
  • SD (admin, road, coord, 7) gives the spatial attribute description set of the monitoring object
  • admin is the description of the administrative division to which the object belongs, such as Shandong province, Jinan City, etc.
  • road is the road where the object is located. Name, such as Beijing-Shanghai Expressway, 301 National Road, etc.
  • coord is the description of the GIS attribute of the object
  • a point object is a coordinate
  • a line object is a coordinate point sequence
  • an area object is the point sequence coordinate collection of its boundary.
  • MI ( ⁇ 1 , ⁇ 2 ,..., ⁇ k ) gives the monitoring index set of the monitoring object.
  • Each type of monitoring object has a fixed index set.
  • Index and other indicators while for a toll station, there are indicators such as truck flow, passenger car flow, ETC flow, congestion queue distance, etc., which vary.
  • the monitoring object mo and other properties are preset, not calculated by the system of the present invention, and all known monitoring objects are stored in the monitoring object library.
  • SD (admin, road, coord, . . . ) gives the spatial attribute description set of the sensor, and its meaning is the same as that of the monitoring object, which will not be repeated here.
  • DI ( ⁇ 1 , ⁇ 2 , . and other indicators; for a flow sensor such as a charging gantry, it includes total flow, traffic by vehicle type, traffic by type of charging, etc.
  • OT (mo 1 , mo 2 , . . . , mo m ) gives the calculation label to which the collection unit su defined in the present invention belongs, which means that the index calculation of the monitoring object mo needs to take the monitoring data provided by su as input.
  • the relationship between the monitoring object mo expressed by OT and the acquisition unit su is preset.
  • the commonly used preset method is spatial attribute association. If there is an attribute association relationship between su.SD and mo.SD, set mo ⁇ su.OT. For example, if you want to calculate the congestion index of a provincial administrative division mo, you need to make summary statistics on the congestion of all road sections su in the province, then the SD.admin attribute of the road section su can automatically extract the relationship between mo and su. and stored in su.OT.
  • step S101 After the target monitoring task is created and completed based on step S101, multiple monitoring objects mo corresponding to the parameter value are obtained through the ⁇ mo.type parameter value in the created monitoring task, and finally the monitoring object mo is obtained Corresponding multiple acquisition units ⁇ mo .
  • the present invention reduces the coupling relationship in the road network operation management business based on the labeling method.
  • the coupling relationship between the definition of the space-time range and the calculation of monitoring indicators is solved by defining the calculation label for the monitoring data (coupling relationship 2 in Figure 1); by defining the task label for the monitoring object, the coupling relationship between the monitoring object and the space-time range is solved ( Figure 1).
  • the coupling relationship 1), and the coupling relationship between the monitoring objects included in different monitoring tasks (coupling relationship 3 in Figure 1).
  • a task database is configured for each monitoring task, and the monitoring object indicator data required by the task is stored in the task database.
  • the monitoring object indicator data required by the monitoring task refers to the monitoring
  • the indicator data of the monitoring object corresponding to the task can not only reduce the data coupling between different tasks, but also facilitate the retrieval of task data.
  • the task-related calculation labels and task labels are calculated and transmitted to the general system; monitoring data collection and index calculation (ie, the implementation of monitoring services) All are implemented uniformly in the general system, and the calculation label is used as the parameter of the monitoring business, which can maximize the consistency of monitoring data and index calculation method.
  • the data distribution mechanism based on task labels distributes the monitoring indicators calculated uniformly to the databases of different monitoring tasks, which can improve the computing efficiency and solve the data coupling relationship between different monitoring tasks.
  • the construction of the traffic data warehouse requires two aspects of work, one is reflected in the monitoring unit, and the other is reflected in the construction of the general system. The two need to be closely combined to build a highly flexible task. To maintain the vitality of the road network operation management and service platform.
  • the collection unit set corresponding to the monitoring object mo is ⁇ mo
  • the spatial range of each collection unit su in ⁇ mo can be expressed as su.SD ( su ⁇ mo ), and the collection unit spatial range parameter can be called through su.SD
  • the spatial range of the target monitoring task can be expressed as tsk.TSD
  • TSD is the spatial range parameter of the target monitoring task tsk
  • the spatial range parameter of the target monitoring task can be accessed through sk.TSD.
  • first obtain the first spatial attribute description of the spatial range of the target monitoring task then obtain the second spatial attribute description of each acquisition unit in the collection unit set, and finally when the second spatial attribute description When belonging to the first spatial attribute description, each acquisition unit is marked as belonging to the target monitoring task.
  • the spatial scope of the target detection task is the description of administrative divisions, such as Shandong province, Jinan City, etc., or the name of the road where the object is located, such as Beijing-Shanghai Expressway, 301 National Road, etc.
  • the spatial description of the collection unit Including the description of the administrative division and the name of the road where it is located
  • the spatial description of the target monitoring task including the description of the administrative division and the name of the road where it is located
  • su.SD.admin and su.SD.road and TSD.admin or TSD.road as attributes respectively Comparative analysis of , if su.SD.admin ⁇ TSD.admin or su.SD.road ⁇ TSD.road is established, it is recorded as su ⁇ tsk; otherwise, it is recorded as
  • the first spatial attribute description of the target monitoring task space range is obtained, and then when the first spatial attribute description of the target monitoring task space range is the first geometric figure, each collection unit set is obtained.
  • Collecting the second spatial attribute description of the unit; wherein, the second spatial attribute description includes a second geometric figure; wherein, the geometric figure includes points, lines and surfaces, and secondly, the first geometric figure and the second geometric figure are combined Input the pre-set correlation judgment function, output the judgment result, and finally mark each acquisition unit as belonging to the target monitoring task when the judgment result is true.
  • TSD.coord defines an area
  • su.SD.coord can define a point domain, line domain or area domain.
  • F() defines whether su is geometrically included in the area defined by TSD.coord, such as the ray method to determine whether the point is in the area, etc., which will not be repeated here.
  • the spatial range corresponding to each acquisition unit when the spatial range corresponding to each acquisition unit does not belong to the target monitoring task space, it is determined that the monitoring object is not coupled to the target monitoring task space; or, when the spatial range corresponding to each acquisition unit belongs to the target monitoring task space
  • the spatial coupling between the monitoring object and the target monitoring task is determined; or, when the spatial scope corresponding to at least one acquisition unit belongs to the spatial scope of the target monitoring task, the partial spatial coupling between the monitoring object and the target monitoring task is determined.
  • Partial spatial coupling relationship For example, assuming that the monitoring object is a county, for a specific monitoring task (such as an earthquake), the monitoring object may only partially belong to the spatial range of the monitoring task (the earthquake only destroyed part of the county, not all of it), Then the monitoring object is spatially coupled with the monitoring task part.
  • a specific monitoring task such as an earthquake
  • the spatial coupling relationship between the monitoring object mo and the task tsk can be obtained, which can be divided into the following three cases:
  • the task label of the monitoring object is obtained, and then the target monitoring task is added to the task label of the monitoring object;
  • the monitoring object when the monitoring object is spatially coupled with a part of the target monitoring task, obtain the collection unit set corresponding to the coupled part of the target monitoring task in the monitoring object, generate the target monitoring object, and set the task label of the newly created target monitoring object as target monitoring The task label of the task, and update the calculation label of the sampling unit related to the newly created target monitoring object.
  • the result calculated based on mo can no longer be directly used by tsk, and a copy operation is performed on mo to generate a new monitoring object mo'. Further, first clear mo′.TT, and then set tsk ⁇ mo′.TT; update the calculation label of the sampling unit related to mo′, that is, for the acquisition unit su 1 , if su 1 ⁇ tsk and su 1 ⁇ ⁇ are satisfied mo , then set mo′ ⁇ su 1 .OT. Based on the above settings, all the collection units in the collection unit set ⁇ mo' of the monitoring object mo' are within the spatial range of the task tsk, and the calculation result of mo' only serves the task tsk.
  • the definitions of Fmo.type and su.type ⁇ k are jointly determined by the type of monitoring object mo, the type of collection unit su, and the index mo. ⁇ k to be calculated. Once the above three factors are determined, the monitoring service calculation function F is uniquely determined.
  • the function is calculated according to the monitoring service
  • the definition of for the existing monitoring object mo, if the index value of mo. ⁇ k is counted, it is brought into The calculation results of the monitoring indicators can be obtained; for the newly added monitoring object mo′, if the mo′. ⁇ k indicator value is counted, the The calculation results of monitoring indicators can be obtained.
  • the index values of all monitoring objects mo are calculated, and the distribution module distributes mo to the corresponding task database of tsk ⁇ mo.TT based on the mo.TT set for the front-end and business of monitoring tasks call, wherein the distributed data may be all monitoring object data, may be a certain type of monitoring index value, or may be all index values.
  • the construction device of the traffic data warehouse first, when receiving the monitoring task creation instruction, creates the target monitoring task based on the creation instruction, and then loads the monitoring object corresponding to the monitoring object category parameter set in the target monitoring task, And obtain the collection unit set of the monitoring object, then obtain the target monitoring task space range corresponding to the monitoring task space range parameter set in the target monitoring task, and then calculate the space range of each collection unit in the collection unit set and the target monitoring task space range.
  • the spatial attribution relationship between the monitoring objects and the target monitoring task is determined according to the spatial attribution relationship, and then the calculation label and task label of the monitoring object are set based on the spatial coupling relationship, and the monitoring object after setting the label is generated.
  • the labeled monitoring object is input into the preset monitoring service calculation function, the monitoring index calculation result is output, and finally the index calculation result is configured into the labeled monitoring object, and the configured monitoring object is distributed to the target monitoring task corresponding to the in the task database. Because the application is based on the labeling method to reduce the coupling relationship in the road network operation and management business, it can flexibly meet the calculation requirements of different monitoring tasks on the monitoring index data at the background data level, solve the coupling problem in the monitoring data calculation process, and improve system service efficiency.
  • FIG. 6 shows a schematic structural diagram of an apparatus for constructing a traffic data warehouse provided by an exemplary embodiment of the present invention.
  • the construction device of the traffic data warehouse can be realized as all or a part of the intelligent robot through software, hardware or a combination of the two.
  • the device 1 includes a monitoring task creation module 10, an acquisition unit acquisition module 20, a target monitoring task space range acquisition module 30, a spatial belonging relationship calculation module 40, a spatial coupling relationship determination module 50, a monitoring object generation module 60, and monitoring index calculation result output Module 70 , data sending module 80 .
  • the monitoring task creation module 10 is configured to create a target monitoring task based on the creation instruction when receiving the monitoring task creation instruction;
  • the acquisition unit acquisition module 20 is used to load the monitoring object corresponding to the monitoring object category parameter set in the target monitoring task, and acquire the collection unit set of the monitoring object;
  • the target monitoring task space range obtaining module 30 is used to obtain the target monitoring task space range corresponding to the monitoring task space range parameter set in the target monitoring task;
  • the spatial belonging relationship calculation module 40 is used to calculate the spatial belonging relationship between the spatial scope of each acquisition unit in the collection unit set and the spatial scope of the target monitoring task;
  • the spatial coupling relationship determining module 50 is used for determining the spatial coupling relationship between the monitoring object and the target monitoring task according to the spatial belonging relationship;
  • the monitoring object generation module 60 is used for setting the calculation label and the task label of the monitoring object based on the spatial coupling relationship, and generating the monitoring object after setting the label;
  • the monitoring index calculation result output module 70 is configured to input the monitoring object after setting the label into the preset monitoring service calculation function, and output the monitoring index calculation result;
  • the data sending module 80 is configured to configure the index calculation result into the monitoring object after setting the label, and distribute the configured monitoring object to the task database corresponding to the target monitoring task.
  • the traffic data warehouse construction device when the traffic data warehouse construction device provided in the above embodiments executes the traffic data warehouse construction method, only the division of the above functional modules is used as an example for illustration. In practical applications, the above functions may be allocated by Different functional modules are completed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.
  • the apparatus for constructing a traffic data warehouse provided by the above embodiments and the embodiments of the method for constructing a traffic data warehouse belong to the same concept, and the implementation process thereof is detailed in the method embodiments, which will not be repeated here.
  • the construction device of the traffic data warehouse first, when receiving the monitoring task creation instruction, creates the target monitoring task based on the creation instruction, and then loads the monitoring object corresponding to the monitoring object category parameter set in the target monitoring task, And obtain the collection unit set of the monitoring object, then obtain the target monitoring task space range corresponding to the monitoring task space range parameter set in the target monitoring task, and then calculate the space range of each collection unit in the collection unit set and the target monitoring task space range.
  • the spatial attribution relationship between the monitoring objects and the target monitoring task is determined according to the spatial attribution relationship, and then the calculation label and task label of the monitoring object are set based on the spatial coupling relationship, and the monitoring object after setting the label is generated.
  • the labeled monitoring object is input into the preset monitoring service calculation function, the monitoring index calculation result is output, and finally the index calculation result is configured into the labeled monitoring object, and the configured monitoring object is distributed to the target monitoring task corresponding to the in the task database. Because the application is based on the labeling method to reduce the coupling relationship in the road network operation and management business, it can flexibly meet the calculation requirements of different monitoring tasks on the monitoring index data at the background data level, solve the coupling problem in the monitoring data calculation process, and improve system service efficiency.
  • the present invention further provides a computer-readable medium on which program instructions are stored, and when the program instructions are executed by a processor, implement the construction method of the traffic data warehouse provided by the above method embodiments.
  • the present invention also provides a computer program product containing instructions, which, when running on a computer, causes the computer to execute the traffic data warehouse construction method of each of the above method embodiments.
  • the terminal 1000 may include: at least one processor 1001 , at least one network interface 1004 , user interface 1003 , memory 1005 , and at least one communication bus 1002 .
  • the communication bus 1002 is used to realize the connection and communication between these components.
  • the user interface 1003 may include a display screen (Display) and a camera (Camera), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.
  • Display display screen
  • Camera Camera
  • the optional user interface 1003 may also include a standard wired interface and a wireless interface.
  • the network interface 1004 may optionally include a standard wired interface and a wireless interface (eg, a WI-FI interface).
  • the processor 1001 may include one or more processing cores.
  • the processor 1001 uses various excuses and lines to connect various parts of the entire electronic device 1000, and executes by running or executing the instructions, programs, code sets or instruction sets stored in the memory 1005, and calling the data stored in the memory 1005.
  • Various functions of the electronic device 1000 and processing data may adopt at least one of digital signal processing (Digital Signal Processing, DSP), field-programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). implemented in a hardware form.
  • DSP Digital Signal Processing
  • FPGA Field-Programmable Gate Array
  • PLA programmable logic array
  • the processor 1001 may integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU), a modem, and the like.
  • CPU Central Processing Unit
  • GPU Graphics Processing Unit
  • the CPU mainly deals with the operating system, user interface and application programs, etc.
  • the GPU is used for rendering and drawing the content that needs to be displayed on the display screen
  • the modem is used for processing wireless communication. It can be understood that, the above-mentioned modem may not be integrated into the processor 1001, but is implemented by a single chip.
  • the memory 1005 may include random access memory (Random Access Memory, RAM), or may include read-only memory (Read-Only Memory).
  • the memory 1005 includes a non-transitory computer-readable storage medium.
  • Memory 1005 may be used to store instructions, programs, codes, sets of codes, or sets of instructions.
  • the memory 1005 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), Instructions and the like used to implement the above method embodiments; the storage data area may store the data and the like involved in the above method embodiments.
  • the memory 1005 can optionally also be at least one storage device located away from the aforementioned processor 1001 .
  • the memory 1005 which is a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for constructing a traffic data warehouse.
  • the user interface 1003 is mainly used to provide an input interface for the user to obtain the data input by the user; and the processor 1001 can be used to call the construction application program of the traffic data warehouse stored in the memory 1005, And do the following specifically:
  • the index calculation result is configured into the monitoring object after setting the label, and the configured monitoring object is distributed to the task database corresponding to the target monitoring task.
  • the processor 1001 when the processor 1001 performs the calculation of the spatial belonging relationship between the spatial range of each acquisition unit in the collection unit set and the spatial range of the target monitoring task, the processor 1001 specifically performs the following operations:
  • each acquisition unit is marked as belonging to the target monitoring task.
  • the processor 1001 specifically performs the following operations when executing the calculation of the spatial affiliation between the spatial range of each acquisition unit in the set of acquisition units and the spatial range of the target monitoring task:
  • the second spatial attribute description of each acquisition unit in the collection unit set is acquired; wherein, the second spatial attribute description includes the second geometric figure; wherein, the geometric figures include points, lines and surfaces;
  • each acquisition unit is marked as belonging to the target monitoring task.
  • the processor 1001 when the processor 1001 determines the spatial coupling relationship between the monitoring object and the target monitoring task according to the spatial belonging relationship, the processor 1001 specifically performs the following operations:
  • the spatial range corresponding to each of the acquisition units does not belong to the spatial range of the target monitoring task, it is determined that the monitoring object is not coupled to the target monitoring task space; or,
  • the spatial range corresponding to each acquisition unit belongs to the spatial range of the target monitoring task, it is determined that the monitoring object is spatially coupled to the target monitoring task; or,
  • the spatial range corresponding to the at least one acquisition unit belongs to the spatial range of the target monitoring task, it is determined that the monitoring object is partially spatially coupled to the target monitoring task.
  • the processor 1001 specifically performs the following operations when setting the calculation label and the task label of the monitoring object based on the spatial coupling relationship:
  • the monitoring object When the monitoring object is spatially coupled to a part of the target monitoring task, acquiring a collection unit set corresponding to the coupled part of the target monitoring task in the monitoring object, and generating a target monitoring object;
  • acquiring the collection unit set corresponding to the coupling part of the target monitoring task in the monitoring object, and generating the target monitoring object when specifically executing, may be acquiring the coupling part in the monitoring object that is coupled with the target monitoring task
  • the collection unit set corresponding to the part will generate the target monitoring object for the collection unit set corresponding to the coupling part, or perform a copy action on the collection unit set corresponding to the coupling part and generate the target monitoring object.
  • the task label of the target monitoring object is set as the task label of the target monitoring task, and the calculation label of the sampling unit corresponding to the target monitoring object is updated.
  • the processor 1001 when receiving the monitoring task creation instruction, specifically performs the following operations when creating the target monitoring task based on the creation instruction:
  • the construction device of the traffic data warehouse first, when receiving the monitoring task creation instruction, creates the target monitoring task based on the creation instruction, and then loads the monitoring object corresponding to the monitoring object category parameter set in the target monitoring task, And obtain the collection unit set of the monitoring object, and then obtain the target monitoring task space range corresponding to the monitoring task space range parameter set in the target monitoring task, and then calculate the space range of each collection unit in the collection unit set and the target monitoring task space range.
  • the spatial attribution relationship between the monitoring objects and the target monitoring task is determined according to the spatial attribution relationship, and then the calculation label and task label of the monitoring object are set based on the spatial coupling relationship, and the monitoring object after setting the label is generated.
  • the tagged monitoring object is input into the preset monitoring service calculation function, the monitoring index calculation result is output, and finally the index calculation result is configured into the labeled monitoring object, and the configured monitoring object is distributed to the target monitoring task corresponding to the in the task database.
  • the program can be stored in a computer-readable storage medium, and when the program is executed, it can include It is as the flow of the embodiments of the above-mentioned methods.
  • the storage medium of the program may be a magnetic disk, an optical disk, a read-only storage memory, or a random storage memory, or the like.

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Abstract

本发明公开了一种交通数据仓库的构建方法、装置、存储介质及终端，该方法包括：基于创建指令创建目标监测任务；加载目标监测任务所对应的监测对象和空间范围，获取监测对象的采集单元集合；计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系，并确定空间耦合关系；基于空间耦合关系设置监测对象的标签，生成设置标签后的监测对象后输入预设监测业务计算函数中，输出计算结果；将计算结果配置到设置标签后的监测对象中，并分发至目标监测任务对应的任务数据库中。因此，采用本申请实施例，可以在后台数据层面灵活地满足不同监测任务对监测指标数据的计算要求，解决了监测数据计算过程中耦合难题，提升了***服务效率。

Description

一种交通数据仓库的构建方法、装置、存储介质及终端
优先权信息
本申请要求于2020年12月31日提交中国专利局、申请号为202011640689.6，发明名称为“一种交通数据仓库的构建方法、装置、存储介质及终端”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明涉及智慧交通技术领域，特别涉及一种交通数据仓库的构建方法、装置、存储介质及终端。
背景技术
公路交通运输在我国经济和社会发展中发挥着重要的作用，维持公路交通网络的稳定和高效运转，对调整产业结构、推动就业和经济发展、加快城乡一体化建设进程具有重要的意义。近年来，随着机动车保有量的快速增长、公路运输需求的逐步攀升，公路交通事件屡有发生且社会影响较大，公路网保通保畅的运行压力不断增加。
虽然我国的交通信息化水平取得了长足的发展，但总体而言，路网运行管理和服务的信息化平台集成度偏低，***分散建设、数据尚未汇集，跨区域、跨层级、跨部门信息传递、资源共性和业务联动壁垒突出，路网运行的整体效能难以发挥，在途精准服务难以满足、应急高效处置难以保障。另一方面，随着云计算、大数据、物联网、AI等技术的快速发展与成熟，以及交通传感设备的大量布设，构建全域高精度的路网运行监测能力的技术和数据条件已经成熟。在此背景下，基于多源异构的交通大数据，构建面向路网运行管理和服务的技术平台，是破解目前我国交通信息化问题的必由之路。
在大数据的背景下，业务平台的构建必须以数据为核心，秉持数据驱动业务的理念，后台数据的组织效率将直接影响到业务的扩展能力，并关乎平台的生命力。就路网运行管理和服务平台而言，以最为重要的路网运行监测业务为例，其涉及到众多的监测对象，如各种行政区、高速公路路段、收费站、服务区等POI，每个对象都包括若干个不同的监测指标。此外，不同的监测任务，其对应的监测业务类型、时空范围、监测对象、监测指标等都存在差异；进一步地，监测对象与监测时空范围、监测业务与监测指标、不同的监测任务之间均存在复杂的耦合关系，这对路网运行管理与服务平台的建设提出了很大的挑战。如何通过后台数据的高效组织与管理，以更好地支撑业务平台的能力扩展，使之进一步适应多样的路网管理任务，是一个非常值得研究的课题。
发明内容
本申请实施例提供了一种交通数据仓库的构建方法、装置、存储介质及终端。为了对披露的实施例的一些方面有一个基本的理解，下面给出了简单的概括。该概括部分不是泛泛评述，也不是要确定关键/重要组成元素或描绘这些实施例的保护范围。其唯一目的是用简单的形式呈现一些概念，以此作为后面的详细说明的序言。
第一方面，本申请实施例提供了一种交通数据仓库的构建方法，该方法包括：
当接收到监测任务创建指令时，基于创建指令创建目标监测任务；
加载目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取监测对象的采集单元集合；
获取目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围；
计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系；
根据空间归属关系确定监测对象与目标监测任务的空间耦合关系；
基于空间耦合关系设置监测对象的计算标签和任务标签，生成设置标签后的监测对象；
将设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果；
将指标计算结果配置到所述设置标签后的监测对象中，并将配置后的监测对象分发至目标监测任务对应的任务数据库中。
可选的，计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系，包括：
获取目标监测任务空间范围的第一空间属性描述；
获取采集单元集合中每个采集单元的第二空间属性描述；
当所述第二空间属性描述属于所述第一空间属性描述时，将每个采集单元标记为属于目标监测任务。
可选的，计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系，包括：
获取目标监测任务空间范围的第一空间属性描述；
当目标监测任务空间范围的第一空间属性描述为第一几何图形时，获取采集单元集合中每个采集单元的第二空间属性描述；其中，第二空间属性描述包括第二几何图形；其中，所述几何图形包括点、线和面；
将所述第一几何图形和所述第二几何图形输入预先设定的相关性判断函数中，输出判断结果；
当判断结果为true时，将每个采集单元标记为属于目标监测任务。
可选的，根据空间归属关系确定监测对象与目标监测任务的空间耦合关系，包括：
当每个所述采集单元对应的空间范围不属于所述目标监测任务空间范围时，确定所述监测对象与所述目标监测任务空间不耦合；或者，
当每个所述采集单元对应的空间范围属于所述目标监测任务空间范围时，确定所述监测对象与所述目标监测任务空间耦合；或者，
当所述至少存在一个所述采集单元对应的空间范围属于所述目标监测任务时空间范围，确定所述监测对象与所述目标监测任务的部分空间耦合。
可选的，基于空间耦合关系设置监测对象的计算标签和任务标签，包括：
当监测对象与目标监测任务空间耦合时，获取监测对象的任务标签；
将目标监测任务添加至监测对象的任务标签；或者，
当监测对象与目标监测任务的部分空间耦合时，获取监测对象中与目标监测任务耦合部分所对应的采集单元集合，并生成目标监测对象；
将所述目标监测对象的任务标签设置为所述目标监测任务的任务标签，并更新所述目标监测对象所对应的采样单元的计算标签。
可选的，方法还包括：
获取目标监测任务中设定的生命周期；其中，生命周期包括任务开始时间和任务结束时间；
当结束时间和当前时刻一致时，清除所述配置后的监测对象中任务标签内的任务标签。
可选的，当接收到监测任务创建指令时，基于创建指令创建目标监测任务，包括：
当接收到监测任务创建指令时，提取监测任务创建指令中包含的多个参数；
获取预先设定的监测任务定义模板；
将多个参数与监测任务定义模板内的标识进行关联，生成目标监测任务；其中，监测任务定义模板为tsk＝<id，(t bgn，t end)，Ω mo.type，TSD>，id唯一标识一个监测任务tsk，(t bgn，t end)分别是任务的开始时间和结束时间，定义了任务的生命周期；Ω mo.type是任务定义的监测对象的类别，TSD是空间范围参数。
第二方面，本申请实施例提供了一种交通数据仓库的构建装置，装置包括：
监测任务创建模块，用于当接收到监测任务创建指令时，基于创建指令创建目标监测任务；
采集单元获取模块，用于加载目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取监测对象的采集单元集合；
目标监测任务空间范围获取模块，用于获取目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围；
空间归属关系计算模块，用于计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系；
空间耦合关系确定模块，用于根据空间归属关系确定监测对象与目标监测 任务的空间耦合关系；
监测对象生成模块，用于基于空间耦合关系设置监测对象的计算标签和任务标签，生成设置标签后的监测对象；
监测指标计算结果输出模块，用于将设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果；
数据发送模块，用于将指标计算结果配置到所述设置标签后的监测对象中，并将配置后的监测对象分发至目标监测任务对应的任务数据库中。
第三方面，本申请实施例提供一种计算机存储介质，计算机存储介质存储有多条指令，指令适于由处理器加载并执行上述的方法步骤。
第四方面，本申请实施例提供一种终端，可包括：处理器和存储器；其中，存储器存储有计算机程序，计算机程序适于由处理器加载并执行上述的方法步骤。
本申请实施例提供的技术方案可以包括以下有益效果：
在本申请实施例中，交通数据仓库的构建装置首先当接收到监测任务创建指令时，基于创建指令创建目标监测任务，再加载目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取监测对象的采集单元集合，然后获取目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围，其次计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系，再根据空间归属关系确定监测对象与目标监测任务的空间耦合关系，再基于空间耦合关系设置监测对象的计算标签和任务标签，生成设置标签后的监测对象，再将设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果，最后将指标计算结果配置到所述设置标签后的监测对象中，并将配置后的监测对象分发至目标监测任务对应的任务数据库中。由于本申请基于标签化方法来降低路网运行管理业务中的耦合关系，从而可以在后台数据层面灵活地满足不同监测任务对监测指标数据的计算要求，解决了监测数据计算过程中耦合难题，提升了***服务效率。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，并不能限制本发明。
附图说明
此处的附图被并入说明书中并构成本说明书的一部分，示出了符合本发明的实施例，并与说明书一起用于解释本发明的原理。
图1是本申请实施例提供的一种路网运行监测业务模型；
图2是本申请实施例提供的一种路网运行监测业务的耦合关系图；
图3是本申请实施例提供的一种交通数据仓库的构建方法的流程示意图；
图4是本申请实施例提供的一种交通数据仓库的构建过程的过程示意图；
图5是本申请实施例提供的一种监测对象的逻辑模型示意图；
图6是本申请实施例提供的一种交通数据仓库的构建装置的示意图；
图7是本申请实施例提供的一种终端示意图。
具体实施方式
以下描述和附图充分地示出本发明的具体实施方案，以使本领域的技术人员能够实践它们。
应当明确，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本发明保护的范围。
下面的描述涉及附图时，除非另有表示，不同附图中的相同数字表示相同或相似的要素。以下示例性实施例中所描述的实施方式并不代表与本发明相一致的所有实施方式。相反，它们仅是如所附权利要求书中所详述的、本发明的一些方面相一致的***和方法的例子。
在本发明的描述中，需要理解的是，术语“第一”、“第二”等仅用于描述目的，而不能理解为指示或暗示相对重要性。对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本发明中的具体含义。此外，在本发明的描述中，除非另有说明，“多个”是指两个或两个以上。“和/或”，描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。字符“/”一般表示前后关联对象是一种“或”的关系。
本申请提供了一种交通数据仓库的构建方法、装置、存储介质及终端，以解决上述相关技术问题中存在的问题。在本申请实施例中，由于本申请基于标签化方法来降低路网运行管理业务中的耦合关系，从而可以在后台数据层面灵活地满足不同监测任务对监测指标数据的计算要求，解决了监测数据计算过程中耦合难题，提升了***服务效率，下面采用示例性的实施例进行详细说明。
例如图1所示，图1是路网运行监测业务模型，从图1进一步分析可知，监测单元内部、监测单元与通用体系之间，存在多重耦合关系：
首先，如图1耦合关系①所示，监测对象必须满足时空范围的约束。如图2(a)所示，对于两个同类型的点对象A和B，A不满足监测任务x的空间范围约束而B满足，因此B会加入到监测任务x对通用体系的数据要求中；
然后，如图1耦合关系②所示，某些情况下，时空范围的定义会影响监测业务及监测指标的计算。如图2(b)所示，对于两个面对象A和B，相较于B对象，A对象的范围并没有完整地被包含在监测任务x的空间范围内，所以其监测指标的计算应该限定于任务x的空间范围内(图中阴影部分)；
最后，如图1耦合关系③所示，不同的监测任务之间可能存在数据上的耦合关系。如图2(c)所示，点对象A在空间上既归属于任务x，也归属与任务 y，为了避免重复计算，则需要考虑点对象A的结果如何在任务间进行分享。
综上，在路网运行管理和服务平台的构建过程中，其业务的特性决定了不可避免地会遇到各类耦合关系的困扰，给任务的弹性及平台的计算效率带来了很大的挑战。如何在后台数据的组织过程中能够对上述耦合关系进行有效地处理，将大大延展平台的服务能力。因此，本发明提出一种面向路网运行管理的交通数据仓库构建方法，解决监测数据计算过程中的耦合难题。
下面将结合附图3-附图5，对本申请实施例提供的交通数据仓库的构建方法进行详细介绍。该方法可依赖于计算机程序实现，可运行于基于冯诺依曼体系的交通数据仓库的构建装置上。该计算机程序可集成在应用中，也可作为独立的工具类应用运行。
图3为本申请实施例提供了一种交通数据仓库的构建方法的流程示意图。如图3所示，本申请实施例的方法可以包括以下步骤：
S101，当接收到监测任务创建指令时，基于创建指令创建目标监测任务；
其中，监测任务创建指令是用户输入到客户端的指令，该指令中包含了创建监测任务的多个参数。其中，多个参数包括监测任务标识id、监测任务的生命周期参数、监测任务中监测对象的类别参数以及监测任务的空间范围参数。
具体地，多个参数分别为监测任务标识id、监测任务的生命周期、监测任务中监测对象的类别以及监测任务的空间范围。
通常，创建的监测任务(Monitoring Task)可定义为tsk＝<id，(t bgn，t end)，Ω mo.type，TSD>，id唯一标识一个监测任务tsk，(t bgn，t end)分别是任务的开始时间和结束时间，定义了任务的生命周期；Ω mo.type是任务定义的监测对象的类别集合。
在一种可能的实现方式中，在创建监测任务时，用户首先确定监测任务的多个参数，并将多个参数输入客户端中，再触发监测任务创建功能。在触发监测任务创建功能后，用户终端接收监测任务创建指令，并提取监测任务创建指令中包含的多个参数，然后获取预先设定的监测任务定义模板tsk，最后将多个参数与监测任务定义模板tsk内的标识进行逐一关联，生成最终的目标监测任务。
S102，加载目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取监测对象的采集单元集合；
其中，设定的监测对象类别参数是步骤S101中创建完成的tsk中的参数Ω mo.type，监测对象属于监测任务，一个监测任务可包含多个监测对象。采集单元集合属于监测对象，一个监测对象包括一个或多个采集单元。
通常，例如图5所示，图5为监测对象的逻辑模型，监测对象(Monitoring Object)可定义为mo＝<id，type，name，SD，MI，TT>，其中，id唯一标识一个监测对象；type定义了该监测对象的类型，如行政区划、高速公路以及POI等；name为该监测对象的名称。
SD＝(admin，road，coord，…)给出了该监测对象的空间属性描述集合， admin是该对象所属于行政区划的描述，如山东省、济南市等；road是该对象所在的道路的名称，如京沪高速、301国道等；coord是该对象的GIS属性的描述，点对象是一个坐标，线对象是一个坐标点序，面对象则是其边界的点序坐标集合。
MI＝(δ 1，δ 2，…，δ k)给出了该监测对象的监测指标集合，每一类监测对象都有固定的指标集，如对于一个省而言，有人口、流量、拥堵指数等指标；而对于一个收费站而言，则有货车流量、客车流量、ETC流量、拥堵排队距离等指标，不一而同。
TT＝(tsk 1，tsk 2，…，tsk m)给出了本发明定义的对象mo所属的任务标签，指的是监测对象mo及其监测指标被若干个监测任务tsk所需要。
需要指出的是，除了本发明定义的TT属性，监测对象mo及其他属性都是预置的，而不是由本发明的***计算出来的，所有已知的监测对象都被存储在监测对象库中。
通常，采集单元(Sampling Unit)可表示为su＝<id，type，name，SD，DI，OT>，id唯一标识一个采集单元；type定义了该采集单元的类型，如是一个拥堵传感器、或者一个流量传感器；name为该传感器的名称。
SD＝(admin，road，coord，…)给出了该传感器的空间属性描述集合，其含义与监测对象相同，这里不再赘述。
DI＝(γ 1，γ 2，…，γ k)给出了该采集单元能够采集的监测数据集，如对于一个拥堵传感器如路段而言，有拥堵等级、平均行驶速度、旅行时间、排队长度等指标；对于一个流量传感器如收费没门架而言，包括总流量、分车型流量、分收费类型流量等。
OT＝(mo 1，mo 2，…，，mo m)给出了本发明定义的采集单元su所属的计算标签，指的是监测对象mo的指标计算需要以su提供的监测数据为输入。
这里需要指出的是，OT所表达的监测对象mo与采集单元su的关系是被预置的，常用的预置方法是空间属性关联，如果su.SD与mo.SD存在属性关联关系，则设置mo→su.OT。例如，如果想计算一个省级行政区划mo的拥堵指数情况，需要将该省内所有路段su的拥堵情况做汇总统计，则路段su的SD.admin属性自动可以提取出mo与su的关联关系，并存储到su.OT中。
在一种可能的实现方式中，在基于步骤S101创建完成目标监测任务后，通过创建的监测任务内的Ω mo.type参数值获取该参数值对应的多个监测对象mo，最后获取监测对象mo对应的多个采集单元Ω mo。
S103，获取目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围；
通常，本发明基于标签化方法来降低路网运行管理业务中的耦合关系。通过对监测数据定义计算标签，来解决时空范围定义与监测指标计算的耦合关系(图1中耦合关系②)；通过对监测对象定义任务标签，来解决监测对象与时空 范围的耦合关系(图1中耦合关系①)，以及不同监测任务之间所包含的监测对象的耦合关系(图1中耦合关系③)。
如图4所示，为每一个监测任务配置任务数据库，将该任务所需的监测对象指标数据都存储到任务数据库中，需要说明到的是，监测任务所需的监测对象指标数据是指监测任务所对应的监测对象的指标数据，这样不仅可以降低不同任务之间的数据耦合，也可以方便对任务数据的调阅。通过监测单元内部的空间计算，结合通用体系监测数据中的监测对象情况，计算出任务相关的计算标签和任务标签，并传给通用体系；监测数据的采集和指标计算(即监测业务的实施)均在通用体系内统一执行，计算标签作为监测业务的参数，可以最大化地保持监测数据和指标计算方法的同一性。此外，基于任务标签的数据分发机制，将统一计算的监测指标分配到不同监测任务的数据库中，这样可以提高计算效率，解决不同监测任务之间的数据耦合关系。
综上，如图4所示，交通数据仓库的构建需要两方面的工作，一方面体现在监测单元内部，另一方面则体现在通用体系的建设，二者需紧密结合才能构建具有高度任务弹性的交通数据仓库，以维持路网运行管理和服务平台的生命力。
S104，计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系；
通常，监测对象mo对应的采集单元集合为Ω mo，Ω mo中每个采集单元su的空间范围可表示为su.SD(su∈Ω mo)，通过su.SD可以调用到采集单元空间范围参数；目标监测任务空间范围可表示为tsk.TSD，TSD是目标监测任务tsk的空间范围参数，通过sk.TSD可调用到目标监测任务的空间范围参数。
在一种可能的实现方式中，首先获取目标监测任务的空间范围的第一空间属性描述，然后获取采集单元集合中每个采集单元的第二空间属性描述，最后当所述第二空间属性描述属于所述第一空间属性描述时，将每个采集单元标记为属于目标监测任务。
例如，如果目标检测任务的空间范围为行政区划的描述，如山东省、济南市等，或者是该对象所在的道路的名称，如京沪高速、301国道等，则将采集单元的空间描述(包括行政区划的描述和所在的道路的名称)与目标监测任务的空间描述(包括行政区划的描述和所在的道路的名称)进行对比分析，判断两者之间的归属性。
例如用定义的字符可以描述为：如果任务的空间范围是基于TSD.admin或TSD.road输入的，则分别将su.SD.admin与su.SD.road与TSD.admin或TSD.road做属性的比较分析，如su.SD.admin∈TSD.admin或su.SD.road∈TSD.road成立，则记为su∈tsk；否则记为
Figure PCTCN2021135717-appb-000001
在另一种可能的实现方式中，获取目标监测任务空间范围的第一空间属性描述，然后当目标监测任务空间范围的第一空间属性描述为第一几何图形时，获取采集单元集合中每个采集单元的第二空间属性描述；其中，第二空间属性 描述包括第二几何图形；其中，所述几何图形包括点、线和面，其次将所述第一几何图形和所述第二几何图形输入预先设定的相关性判断函数中，输出判断结果，最后当判断结果为true时，将每个采集单元标记为属于目标监测任务。
如果任务的空间范围是基于TSD.coord输入的，则需要根据su.SD.coord与TSD.coord进行空间几何计算。在本发明中，TSD.coord定义的是一个面域，而su.SD.coord定义的可以是一个点域、线域或面域，这里定义TSD.coord与su.SD.coord的相关关系由函数F(TSD.coord，su.SD.coord)定义，如果F()＝True，则记为su∈tsk，否则记为
Figure PCTCN2021135717-appb-000002
F()定义了su是否几何包含于TSD.coord定义的面域内，如判断点是否在面域内的射线法等，这里不再赘述。
S105，根据空间归属关系确定监测对象与目标监测任务的空间耦合关系；
在一种可能的实现方式中，当每个采集单元对应的空间范围不属于目标监测任务空间范围时，确定监测对象与目标监测任务空间不耦合；或者，当每个采集单元对应的空间范围属于目标监测任务空间范围时，确定监测对象与目标监测任务空间耦合；或者，当至少存在一个采集单元对应的空间范围属于目标监测任务时空间范围，确定监测对象与目标监测任务的部分空间耦合。
部分空间耦合关系例如，假设监测对象为一个县，针对一个特定的监测任务(如地震)，监测对象可能只是部分属于监测任务的空间范围(地震只破坏了县的部分空间，而不是全部)，那么监测对象与监测任务部分空间耦合。
综上，基于上述tsk.TSD与su.SD的空间耦合关系分析，可以得到监测对象mo与任务tsk的空间耦合关系，分如下三种情况：
1)对于任意一个su∈Ω mo，
Figure PCTCN2021135717-appb-000003
则记为
Figure PCTCN2021135717-appb-000004
即该监测对象与监测任务无关；
2)对于任意一个su∈Ω mo，su∈tsk，则记为mo∈tsk，即该监测对象与监测任务有关；
3)存在一个或多个su 1∈Ω mo，有su 1∈tsk，且存在一个或多个su 2∈Ω mo，有
Figure PCTCN2021135717-appb-000005
即该监测对象与监测任务部分相关。
S106，基于空间耦合关系设置监测对象的计算标签和任务标签，生成设置标签后的监测对象；
在一种可能的实现方式中，当监测对象与目标监测任务空间耦合时，获取监测对象的任务标签，然后将目标监测任务添加至监测对象的任务标签；
或者，当监测对象与目标监测任务的部分空间耦合时，获取监测对象中与目标监测任务耦合部分所对应的采集单元集合，并生成目标监测对象，将新建目标监测对象的任务标签设置为目标监测任务的任务标签，并更新与新建目标监测对象相关的采样单元的计算标签。
可以理解地，每新建一个监测对象，与其相关的采样单元的计算标签将进行一次更新。
例如，对于mo属于tsk的情况，设置tsk→mo.TT，将tsk加入对象mo的任 务标签中。
对于mo部分属于tsk的情况，此时基于mo计算的结果已经无法直接被tsk所使用，对mo执行拷贝操作，生成一个新的监测对象mo′。进一步地，首先将mo′.TT清空，再置tsk→mo′.TT；更新与mo′相关的采样单元的计算标签，即对于采集单元su 1，若满足su 1∈tsk且su 1∈Ω mo，则设置mo′→su 1.OT。基于上述设置，监测对象mo′的采集单元集合Ω mo′中的所有采集单元均在任务tsk的空间范围内，且mo′的计算结果只服务于任务tsk。
S107，将设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果；
其中，监测业务计算函数(Monitoring Calculation Function)为
Figure PCTCN2021135717-appb-000006
给出了基于监测对象mo相关的采集单元集合Ω mo计算监测对象指标mo.δ k的方法，其中，Ω mo＝{su|mo∈su.OT。Fmo.type，su.typeδk的定义由监测对象mo的类型、采集单元su的类型，以及需要计算的指标mo.δ k共同决定，一旦上述三个因素确定，则监测业务计算函数F唯一确定。
在一种可能的实现方式中，根据监测业务计算函数
Figure PCTCN2021135717-appb-000007
的定义，对于已有的监测对象mo，如果统计mo.δ k指标值，则带入
Figure PCTCN2021135717-appb-000008
即可获得监测指标计算结果；对于新增的监测对象mo′，如果统计mo′.δ k指标值，则带入
Figure PCTCN2021135717-appb-000009
即可获得监测指标计算结果。基于上述逻辑，在不改变监测业务计算函数定义的前提下，实现了监测任务与监测对象的多样化空间耦合关系的计算。
S108，将指标计算结果配置到所述设置标签后的监测对象中，并将配置后的监测对象分发至目标监测任务对应的任务数据库中。
在一种可能的实现方式中，计算出所有监测对象mo的指标值，分发模块基于mo.TT集合，将mo分发到对应的tsk∈mo.TT的任务数据库中，供监测任务的前端和业务进行调用，其中，分发的数据可以为全部的监测对象数据，可以为某一类型的监测指标值，也可以为全部的指标值。进一步地，任务都是具有生命周期的，如果时间超过了tsk.t end设定的时间，则清理所有监测对象mo.TT中的tsk标签，如果对象mo.TT＝{}，则说明该对象已失效，不需要再进行计算。具体为，用户终端获取目标监测任务中设定的生命周期；其中，生命周期包括任务开始时间和任务结束时间；当结束时间和当前时刻一致时，清除所述配置后的监测对象中任务标签内的任务标签。
在本申请实施例中，交通数据仓库的构建装置首先当接收到监测任务创建指令时，基于创建指令创建目标监测任务，再加载目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取监测对象的采集单元集合，然后获取目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围，其次计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系，再根据空间归属关系确定监测对象与目标监测任务的空间 耦合关系，再基于空间耦合关系设置监测对象的计算标签和任务标签，生成设置标签后的监测对象，再将设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果，最后将指标计算结果配置到所述设置标签后的监测对象中，并将配置后的监测对象分发至目标监测任务对应的任务数据库中。由于本申请基于标签化方法来降低路网运行管理业务中的耦合关系，从而可以在后台数据层面灵活地满足不同监测任务对监测指标数据的计算要求，解决了监测数据计算过程中耦合难题，提升了***服务效率。
下述为本发明装置实施例，可以用于执行本发明方法实施例。对于本发明装置实施例中未披露的细节，请参照本发明方法实施例。
请参见图6，其示出了本发明一个示例性实施例提供的交通数据仓库的构建装置的结构示意图。该交通数据仓库的构建装置可以通过软件、硬件或者两者的结合实现成为智能机器人的全部或一部分。该装置1包括监测任务创建模块10、采集单元获取模块20、目标监测任务空间范围获取模块30、空间归属关系计算模块40、空间耦合关系确定模块50、监测对象生成模块60、监测指标计算结果输出模块70、数据发送模块80。
监测任务创建模块10，用于当接收到监测任务创建指令时，基于创建指令创建目标监测任务；
采集单元获取模块20，用于加载目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取监测对象的采集单元集合；
目标监测任务空间范围获取模块30，用于获取目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围；
空间归属关系计算模块40，用于计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系；
空间耦合关系确定模块50，用于根据空间归属关系确定监测对象与目标监测任务的空间耦合关系；
监测对象生成模块60，用于基于空间耦合关系设置监测对象的计算标签和任务标签，生成设置标签后的监测对象；
监测指标计算结果输出模块70，用于将设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果；
数据发送模块80，用于将指标计算结果配置到所述设置标签后的监测对象中，并将配置后的监测对象分发至目标监测任务对应的任务数据库中。
需要说明的是，上述实施例提供的交通数据仓库的构建装置在执行交通数据仓库的构建方法时，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要将上述功能分配由不同的功能模块完成，即将设备的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。另外，上述实施例提供的交通数据仓库的构建装置与交通数据仓库的构建方法实施例属于同一构思，其实现过程详见方法实施例，这里不再赘述。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
在本申请实施例中，交通数据仓库的构建装置首先当接收到监测任务创建指令时，基于创建指令创建目标监测任务，再加载目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取监测对象的采集单元集合，然后获取目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围，其次计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系，再根据空间归属关系确定监测对象与目标监测任务的空间耦合关系，再基于空间耦合关系设置监测对象的计算标签和任务标签，生成设置标签后的监测对象，再将设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果，最后将指标计算结果配置到所述设置标签后的监测对象中，并将配置后的监测对象分发至目标监测任务对应的任务数据库中。由于本申请基于标签化方法来降低路网运行管理业务中的耦合关系，从而可以在后台数据层面灵活地满足不同监测任务对监测指标数据的计算要求，解决了监测数据计算过程中耦合难题，提升了***服务效率。
本发明还提供一种计算机可读介质，其上存储有程序指令，该程序指令被处理器执行时实现上述各个方法实施例提供的交通数据仓库的构建方法。
本发明还提供了一种包含指令的计算机程序产品，当其在计算机上运行时，使得计算机执行上述各个方法实施例的交通数据仓库的构建方法。
请参见图7，为本申请实施例提供了一种终端的结构示意图。如图7所示，终端1000可以包括：至少一个处理器1001，至少一个网络接口1004，用户接口1003，存储器1005，至少一个通信总线1002。
其中，通信总线1002用于实现这些组件之间的连接通信。
其中，用户接口1003可以包括显示屏(Display)、摄像头(Camera)，可选用户接口1003还可以包括标准的有线接口、无线接口。
其中，网络接口1004可选的可以包括标准的有线接口、无线接口(如WI-FI接口)。
其中，处理器1001可以包括一个或者多个处理核心。处理器1001利用各种借口和线路连接整个电子设备1000内的各个部分，通过运行或执行存储在存储器1005内的指令、程序、代码集或指令集，以及调用存储在存储器1005内的数据，执行电子设备1000的各种功能和处理数据。可选的，处理器1001可以采用数字信号处理(Digital Signal Processing，DSP)、现场可编程门阵列(Field-Programmable Gate Array，FPGA)、可编程逻辑阵列(Programmable Logic Array，PLA)中的至少一种硬件形式来实现。处理器1001可集成中央处理器(Central Processing Unit，CPU)、图像处理器(Graphics Processing Unit，GPU)和调制解调器等中的一种或几种的组合。其中，CPU主要处理操作***、 用户界面和应用程序等；GPU用于负责显示屏所需要显示的内容的渲染和绘制；调制解调器用于处理无线通信。可以理解的是，上述调制解调器也可以不集成到处理器1001中，单独通过一块芯片进行实现。
其中，存储器1005可以包括随机存储器(Random Access Memory，RAM)，也可以包括只读存储器(Read-Only Memory)。可选的，该存储器1005包括非瞬时性计算机可读介质(non-transitory computer-readable storage medium)。存储器1005可用于存储指令、程序、代码、代码集或指令集。存储器1005可包括存储程序区和存储数据区，其中，存储程序区可存储用于实现操作***的指令、用于至少一个功能的指令(比如触控功能、声音播放功能、图像播放功能等)、用于实现上述各个方法实施例的指令等；存储数据区可存储上面各个方法实施例中涉及到的数据等。存储器1005可选的还可以是至少一个位于远离前述处理器1001的存储装置。如图7所示，作为一种计算机存储介质的存储器1005中可以包括操作***、网络通信模块、用户接口模块以及交通数据仓库的构建应用程序。
在图7所示的终端1000中，用户接口1003主要用于为用户提供输入的接口，获取用户输入的数据；而处理器1001可以用于调用存储器1005中存储的交通数据仓库的构建应用程序，并具体执行以下操作：
当接收到监测任务创建指令时，基于创建指令创建目标监测任务；
加载目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取监测对象的采集单元集合；
获取目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围；
计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系；
根据空间归属关系确定监测对象与目标监测任务的空间耦合关系；
基于空间耦合关系设置监测对象的计算标签和任务标签，生成设置标签后的监测对象；
将设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果；
将指标计算结果配置到所述设置标签后的监测对象中，并将配置后的监测对象分发至目标监测任务对应的任务数据库中。
在一个实施例中，处理器1001在执行计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系时，具体执行以下操作：
获取目标监测任务空间范围的第一空间属性描述；
获取采集单元集合中每个采集单元的第二空间属性描述；
当所述第二空间属性描述属于所述第一空间属性描述时，将每个采集单元标记为属于目标监测任务。
在一个实施例中，处理器1001在执行计算采集单元集合中每个采集单元 的空间范围与目标监测任务空间范围之间的空间归属关系时，具体执行以下操作：
获取目标监测任务空间范围的第一空间属性描述；
当目标监测任务空间范围的第一空间属性描述为第一几何图形时，获取采集单元集合中每个采集单元的第二空间属性描述；其中，第二空间属性描述包括第二几何图形；其中，所述几何图形包括点、线和面；
将所述第一几何图形和所述第二几何图形输入预先设定的相关性判断函数中，输出判断结果；
当判断结果为true时，将每个采集单元标记为属于目标监测任务。
在一个实施例中，处理器1001在执行根据空间归属关系确定监测对象与目标监测任务的空间耦合关系时，具体执行以下操作：
当每个所述采集单元对应的空间范围不属于所述目标监测任务空间范围时，确定所述监测对象与所述目标监测任务空间不耦合；或者，
当每个所述采集单元对应的空间范围属于所述目标监测任务空间范围时，确定所述监测对象与所述目标监测任务空间耦合；或者，
当所述至少存在一个所述采集单元对应的空间范围属于所述目标监测任务时空间范围，确定所述监测对象与所述目标监测任务的部分空间耦合。
在一个实施例中，处理器1001在基于空间耦合关系设置监测对象的计算标签和任务标签时，具体执行以下操作：
当监测对象与目标监测任务空间耦合时，获取监测对象的任务标签；
将目标监测任务添加至监测对象的任务标签；或者，
当所述监测对象与所述目标监测任务的部分空间耦合时，获取所述监测对象中与所述目标监测任务耦合部分所对应的采集单元集合，并生成目标监测对象；
在一个实施例中，获取所述监测对象中与所述目标监测任务耦合部分所对应的采集单元集合，并生成目标监测对象具体执行时可以是获取所述监测对象中与所述目标监测任务耦合部分所对应的采集单元集合，将对耦合部分所对应的采集单元集合生成目标监测对象，或者是对耦合部分所对应的采集单元集合执行拷贝动作并生成目标监测对象。
将所述目标监测对象的任务标签设置为所述目标监测任务的任务标签，并更新所述目标监测对象所对应的采样单元的计算标签。
在一个实施例中，处理器1001在当接收到监测任务创建指令时，基于创建指令创建目标监测任务时，具体执行以下操作：
当接收到监测任务创建指令时，提取监测任务创建指令中包含的多个参数；
获取预先设定的监测任务定义模板；
将多个参数与监测任务定义模板内的标识进行关联，生成目标监测任务；其中，监测任务定义模板为tsk＝<id，(t bgn，t end)，Ω mo.type，TSD>，id唯一标识一个监测任务tsk，(t bgn，t end)分别是任务的开始时间和结束时间，定义了任务 的生命周期；Ω mo.type是任务定义的监测对象的类别。
在本申请实施例中，交通数据仓库的构建装置首先当接收到监测任务创建指令时，基于创建指令创建目标监测任务，再加载目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取监测对象的采集单元集合，然后获取目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围，其次计算采集单元集合中每个采集单元的空间范围与目标监测任务空间范围之间的空间归属关系，再根据空间归属关系确定监测对象与目标监测任务的空间耦合关系，再基于空间耦合关系设置监测对象的计算标签和任务标签，生成设置标签后的监测对象，再将设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果，最后将指标计算结果配置到所述设置标签后的监测对象中，并将配置后的监测对象分发至目标监测任务对应的任务数据库中。由于本申请基于标签化方法来降低路网运行管理业务中的耦合关系，从而可以在后台数据层面灵活地满足不同监测任务对监测指标数据的计算要求，解决了监测数据计算过程中耦合难题，提升了***服务效率。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序指令相关硬件来完成，程序可存储于计算机可读取存储介质中，该程序在执行时，可包括如上述各方法的实施例的流程。其中，程序的存储介质可为磁碟、光盘、只读存储记忆体或随机存储记忆体等。
以上所揭露的仅为本申请较佳实施例而已，当然不能以此来限定本申请之权利范围，因此依本申请权利要求所作的等同变化，仍属本申请所涵盖的范围。

Claims (18)

  1. 一种交通数据仓库的构建方法，其特征在于，所述方法包括：
    当接收到监测任务创建指令时，基于所述创建指令创建目标监测任务；
    加载所述目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取所述监测对象的采集单元集合；
    获取所述目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围；
    计算所述采集单元集合中每个采集单元的空间范围与所述目标监测任务空间范围之间的空间归属关系；
    根据所述空间归属关系确定所述监测对象与所述目标监测任务的空间耦合关系；
    基于所述空间耦合关系设置所述监测对象的计算标签和任务标签，生成设置标签后的监测对象；
    将所述设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果；
    将所述指标计算结果配置到所述设置标签后的监测对象中，并将所述配置后的监测对象分发至所述目标监测任务对应的任务数据库中。
  2. 根据权利要求1所述的方法，其特征在于，所述计算所述采集单元集合中每个采集单元的空间范围与所述目标监测任务空间范围之间的空间归属关系，包括：
    获取所述目标监测任务空间范围的第一空间属性描述；
    获取所述采集单元集合中每个采集单元的第二空间属性描述；
    当所述第二空间属性描述属于所述第一空间属性描述时，将所述每个采集单元标记为属于所述目标监测任务。
  3. 根据权利要求1所述的方法，其特征在于，所述计算所述采集单元集合中每个采集单元的空间范围与所述目标监测任务空间范围之间的空间归属关系，包括：
    获取所述目标监测任务空间范围的第一空间属性描述；
    当所述目标监测任务空间范围的第一空间属性描述为第一几何图形时，获取所述采集单元集合中每个采集单元的第二空间属性描述；其中，所述第二空间属性描述包括第二几何图形；其中，所述几何图形包括点、线和面；
    将所述第一几何图形和所述第二几何图形输入预先设定的相关性判断函数中，输出判断结果；
    当所述判断结果为true时，将所述每个采集单元标记为属于所述目标监测任务。
  4. 根据权利要求1所述的方法，其特征在于，所述根据所述空间归属关系 确定所述监测对象与所述目标监测任务的空间耦合关系，包括：
    当每个所述采集单元对应的空间范围不属于所述目标监测任务空间范围时，确定所述监测对象与所述目标监测任务空间不耦合；或者，
    当每个所述采集单元对应的空间范围属于所述目标监测任务空间范围时，确定所述监测对象与所述目标监测任务空间耦合；或者，
    当至少存在一个所述采集单元对应的空间范围属于所述目标监测任务时空间范围，确定所述监测对象与所述目标监测任务的部分空间耦合。
  5. 根据权利要求1所述的方法，其特征在于，所述基于所述空间耦合关系设置所述监测对象的计算标签和任务标签，包括：
    当所述监测对象与所述目标监测任务空间耦合时，获取所述监测对象的任务标签；
    将所述目标监测任务添加至所述监测对象的任务标签；
    或者，
    当所述监测对象与所述目标监测任务的部分空间耦合时，获取所述监测对象中与所述目标监测任务耦合部分所对应的采集单元集合，并生成目标监测对象；
    将所述目标监测对象的任务标签设置为所述目标监测任务的任务标签，并更新所述目标监测对象所对应的采样单元的计算标签。
  6. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    获取所述目标监测任务中设定的生命周期；其中，所述生命周期包括任务开始时间和任务结束时间；
    当所述结束时间和当前时刻一致时，清除所述配置后的监测对象中任务标签内的任务标签。
  7. 根据权利要求1所述的方法，其特征在于，所述当接收到监测任务创建指令时，基于所述创建指令创建目标监测任务，包括：
    当接收到监测任务创建指令时，提取所述监测任务创建指令中包含的多个参数；
    获取预先设定的监测任务定义模板；
    将所述多个参数与所述监测任务定义模板内的标识进行关联，生成目标监测任务；其中，所述监测任务定义模板为tsk＝<id,(t bgn,t end),Ω mo.type,TSD>，id唯一标识一个监测任务tsk，(t bgn,t end)分别是任务的开始时间和结束时间，定义了任务的生命周期；Ω mo.type是任务定义的监测对象的类别，TSD是空间范围参数。
  8. 根据权利要求1所述的方法，其特征在于，所述监测对象为mo＝<id,type,name,SD,MI,TT>，其中，id唯一标识一个监测对象；type为 所述监测对象的类型；name为所述监测对象的名称；
    其中，SD＝(admin,road,coord,…)为所述监测对象的空间属性描述集合，admin是该对象所属于行政区划的描述；road是该对象所在的道路的名称；coord是该对象的GIS属性的描述；
    其中，MI＝(δ 1,δ 2,…,δ k)为所述监测对象的监测指标集合，每一类监测对象都有固定的指标集；
    其中，TT＝(tsk 1,tsk 2,…,tsk m)为所述监测对象所属的任务标签。
  9. 根据权利要求1所述的方法，其特征在于，所述监测任务创建指令是输入到客户端的指令，该指令中包含创建监测任务的多个参数。
  10. 根据权利要求9所述的方法，其特征在于，所述创建监测任务的多个参数包括监测任务标识id、监测任务的生命周期参数、监测任务中监测对象的类别参数以及监测任务的空间范围参数。
  11. 根据权利要求10所述的方法，其特征在于，所述监测对象都被存储在监测对象库中。
  12. 根据权利要求1所述的方法，其特征在于，所述监测对象的类型包括拥堵传感器或流量传感器。
  13. 根据权利要求7所述的方法，其特征在于，所述监测任务配置有任务数据库，所述任务数据库中存储有每一个所述监测任务所对应的监测对象指标数据。
  14. 根据权利要求8所述的方法，其特征在于，所述监测对象对应的采集单元集合为Ω mo，Ω mo中每个采集单元su的空间范围表示为su.SD；目标监测任务空间范围表示为tsk.TSD。
  15. 根据权利要求1所述的方法，其特征在于，所述监测业务计算函数为
    Figure PCTCN2021135717-appb-100001
    mo.type为监测对象的类型；su.type为采集单元的类型；Ω mo为监测对象mo的采集单元集合；δ k为监测对象的监测指标集合。
  16. 一种交通数据仓库的构建装置，其特征在于，所述装置包括：
    监测任务创建模块，用于当接收到监测任务创建指令时，基于所述创建指令创建目标监测任务；
    采集单元获取模块，用于加载所述目标监测任务中设定的监测对象类别参数所对应的监测对象，并获取所述监测对象的采集单元集合；
    目标监测任务空间范围获取模块，用于获取所述目标监测任务中设定的监测任务空间范围参数对应的目标监测任务空间范围；
    空间归属关系计算模块，用于计算所述采集单元集合中每个采集单元的空间范围与所述目标监测任务空间范围之间的空间归属关系；
    空间耦合关系确定模块，用于根据所述空间归属关系确定所述监测对象与所述目标监测任务的空间耦合关系；
    监测对象生成模块，用于基于所述空间耦合关系设置所述监测对象的计算标签和任务标签，生成设置标签后的监测对象；
    监测指标计算结果输出模块，用于将所述设置标签后的监测对象输入预设监测业务计算函数中，输出监测指标计算结果；
    数据发送模块，用于将所述指标计算结果配置到所述设置标签后的监测对象中，并将所述配置后的监测对象分发至所述目标监测任务对应的任务数据库中。
  17. 一种计算机存储介质，其特征在于，所述计算机存储介质存储有多条指令，所述指令适于由处理器加载并执行如权利要求1-15任意一项的方法步骤。
  18. 一种终端，其特征在于，包括：处理器和存储器；其中，所述存储器存储有计算机程序，所述计算机程序适于由所述处理器加载并执行如权利要求1-15任意一项的方法步骤。
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