Regional economic activeness analysis method based on highway ETC data

Abstract

The invention discloses a regional economic activeness analysis method based on highway ETC data, and belongs to the technical field of traffic control systems of road vehicles, and the method comprises the following steps: dividing a region needing economic activeness analysis to obtain each economic block, and carrying out the statistics of the highway ETC data of each economic block in a preset period; analyzing to obtain the highway traffic active index of each economic block, and synchronously judging to obtain the highway traffic active attribute label of each economic block; obtaining an economic block group corresponding to each traffic active attribute tag; a traffic influence parameter set of the economic block group is collected and analyzed, branch economic block clusters corresponding to the traffic active attribute labels are obtained through integration, and highway ETC data of the branch economic block clusters in a preset period are classified, output and displayed. The problems of low accuracy and poor real-time performance of economic activity assessment in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic control systems for road vehicles, and in particular to a method for analyzing regional economic activity based on expressway ETC data. Background Art

[0002] With the continuous development of the economy, highway ETC is used more and more frequently, and highway ETC data reflects the economic activity of a region.

[0003] There is currently no fast and flexible economic activity prediction and evaluation plan for regional economic activity. Therefore, there is an urgent need for a prediction and evaluation method for regional economic activity in different regions to provide effective support for regional economic activity analysis.

[0004] For example, the traffic state estimation method and device based on ETC data announced by the invention patent with announcement number: CN113034904B include: dividing the expressway network into a number of cells according to the entrance and exit ramp positions, ETC gantry positions and lane number change positions; based on the divided cells, a macro traffic flow model of the expressway network is established with traffic flow density as the traffic state variable; target cells with ETC gantries at both entrances and exits are obtained, and the actual vehicle density value of the target cell is calculated; a state observer and a Kalman filter are constructed respectively according to the macro traffic flow model, and the vehicle density estimation value of each cell is calculated, and the pre-estimated value of the Kalman filter is calculated at the same time; the vehicle density estimation value and the pre-estimated value of the Kalman filter are fused and calculated to obtain a fused pre-estimated value; the fused pre-estimated value of the Kalman filter is corrected in combination with the measurement value of the traffic sensor to obtain a new estimation value to determine the traffic state of the expressway network.

[0005] For example, the invention patent with announcement number: CN115953904B discloses a method for analyzing the stability of high-speed traffic flow speed, an electronic device and a storage medium thereof, comprising: collecting ETC transaction data of vehicles, dividing the ETC transaction data at intervals of 15 minutes into time slice data, and then cleaning the ETC transaction data after data division to obtain the ETC transaction data in time slices, and then calculating the section running speed between highway gantries, calculating the time fluctuation index and the space fluctuation index of the section running speed between highway gantries, calculating the lower limit values ​​of the time and space fluctuation index of the section running speed between highway gantries, calculating the time instability level and the space instability level of the section running speed between highway gantries, and finally outputting the result of the instability of the high-speed traffic flow speed.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: In the existing technology, although highway ETC data can be used for regional economic analysis, it is limited to basic statistics. Because highways involve different regions and the environment in each region is highly discrete, simple technical statistics cannot analyze the data one by one, so it is difficult to provide efficient and reasonable data support for economic activity assessment. Summary of the invention

[0007] The embodiment of the present application solves the problems of low accuracy and poor real-time performance of economic activity assessment in the prior art by providing a regional economic activity analysis method based on highway ETC data, thereby achieving accuracy and real-time performance in regional economic activity assessment.

[0008] The embodiment of the present application provides a method for analyzing regional economic activity based on highway ETC data, comprising the following steps: obtaining economic blocks by dividing the area that needs to be analyzed for economic activity, and counting the highway ETC data of each economic block in a preset period; obtaining the highway traffic activity index of each economic block based on the highway ETC data of each economic block, and simultaneously determining and obtaining the highway traffic activity attribute label of each economic block; obtaining the economic block group corresponding to each traffic activity attribute label based on the highway traffic activity attribute label of each economic block by aggregation and classification; obtaining the economic block group corresponding to each traffic activity attribute label based on the economic block group corresponding to each traffic activity attribute label, and collecting the traffic impact parameter set of the economic block group for analysis, integrating to obtain each branch economic block cluster corresponding to each traffic activity attribute label, and classifying and outputting the highway ETC data of each branch economic block cluster in the preset period, thereby achieving the accuracy and real-time performance of regional economic activity assessment.

[0009] Furthermore, the statistics of highway ETC data of each economic block specifically include the number of each type of vehicles, the total number of vehicles, the average vehicle speed and the average vehicle driving time in a preset period.

[0010] Furthermore, the highway ETC data of each economic block is analyzed to obtain the highway traffic activity index of each economic block. The specific method is: average the number of each type of vehicles and the total number of vehicles in each economic block to obtain the average number of each type of vehicles; obtain the maximum average vehicle speed and the maximum average vehicle driving time of the economic block in a preset period, and combine them with the average number of each type of vehicles as ETC reference data; based on the highway ETC data of each economic block, analyze it with the ETC reference data to obtain the highway traffic activity index of each economic block.

[0011] Furthermore, the highway traffic activity index of each economic block is obtained by: ; In the formula, represents the highway traffic activity index of the i-th economic block, i represents the number of the economic block, , I represents the total number of economic blocks, j represents the number of vehicle types, , Indicates the total number of vehicle types, represents the number of vehicles of type j in the i-th economic block, represents the average number of vehicles of type j, e represents a natural constant, represents the total number of vehicles in the i-th economic block, represents the average speed of vehicles in the i-th economic block, Indicates the maximum average speed of the vehicle. represents the average driving time of vehicles in the i-th economic block, Indicates the maximum average driving time of the vehicle, Indicates the number of vehicle types that influence the weight, Indicates the total number of vehicles affecting the weight, Indicates the influence weight of the average vehicle speed, Indicates the impact weight of the average vehicle driving time.

[0012] Furthermore, the synchronous determination obtains the highway traffic activity attribute label of each economic block, and the specific method is: obtain the first traffic activity threshold and the second traffic activity threshold preset in the database, and compare them with the highway traffic activity index of each economic block, if the highway traffic activity index of a certain economic block is greater than the first traffic activity threshold, then the highway traffic activity attribute label of the economic block is a high activity label, if the highway traffic activity index of a certain economic block is below the first traffic activity threshold and greater than the second traffic activity threshold, then the highway traffic activity attribute label of the economic block is a medium activity label, if the highway traffic activity index of a certain economic block is below the second traffic activity threshold, then the highway traffic activity attribute label of the economic block is a low activity label.

[0013] Furthermore, the highway traffic activity attribute label based on each economic block is aggregated and classified to obtain the economic block group corresponding to each traffic activity attribute label. The specific method is: the economic blocks with the same highway traffic activity attribute label are classified to obtain the economic blocks corresponding to each traffic activity attribute label, and the economic blocks corresponding to the same traffic activity attribute label are aggregated to obtain the economic block group corresponding to each traffic activity attribute label.

[0014] Furthermore, the traffic impact parameter set of the economic block group is collected for analysis, specifically including: based on the economic block group corresponding to each traffic active attribute label, and recording several economic blocks covered in the economic block group as branch economic blocks; collecting the traffic impact parameter set of the economic block group, including the population density, permanent population, public transportation coverage rate, total number of highway entrances and exits, and total number of road intersections of each branch economic block; constructing a traffic complexity index correction factor for each branch economic block, and analyzing based on the traffic impact parameter set of the economic block group to obtain the traffic complexity index of each branch economic block.

[0015] Furthermore, the branch economic block clusters corresponding to each traffic activity attribute label are obtained by: obtaining the first threshold value of the traffic complexity index and the second threshold value of the traffic complexity index preset in the database, and comparing them with the traffic complexity index of each branch economic block respectively; if the traffic complexity index of a branch economic block is greater than the first threshold value of the traffic complexity index, then the traffic complexity index of the branch economic block belongs to the first branch economic block cluster, and the traffic activity attribute label corresponding to the traffic complexity index of the branch economic block is divided into the first branch economic block cluster; if the traffic complexity index of a branch economic block is below the first threshold value of the traffic complexity index and greater than the second threshold value of the traffic complexity index, then the traffic complexity index of the branch economic block belongs to the second branch economic block cluster. If there is a branch economic block cluster, the traffic activity attribute label corresponding to the traffic complexity index of the branch economic block is divided into the second branch economic block cluster; if the traffic complexity index of a branch economic block is below the first threshold of the traffic complexity index, the traffic complexity index of the branch economic block belongs to the third branch economic block cluster, and the traffic activity attribute label corresponding to the traffic complexity index of the branch economic block is divided into the third branch economic block cluster; count the branch economic block clusters and traffic activity attribute labels corresponding to each branch economic block, and aggregate the branch economic blocks belonging to the same traffic activity attribute label and the same branch economic block cluster into a branch economic block cluster, thereby obtaining the branch economic block clusters corresponding to each traffic activity attribute label one by one.

[0016] Furthermore, the construction of the traffic complexity index correction factor of each branch economic block specifically includes the following steps: obtaining the historical traffic impact parameter set of each branch economic block and analyzing it to obtain the traffic change index of each branch economic block; obtaining each traffic change index interval preset in the database and the traffic complexity index correction factor corresponding to each traffic change index interval; if the traffic change index of a branch economic block is within a preset traffic change index interval, then obtaining the traffic complexity index correction factor corresponding to the traffic change index interval as the traffic complexity index correction factor of the branch economic block; the traffic change index of each branch economic block is used to characterize the degree of change of the traffic and historical traffic of each branch economic block.

[0017] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. The regional economic activity analysis method based on highway ETC data provided by the present invention obtains the highway ETC data of each economic block and analyzes it to obtain the highway traffic activity index and traffic activity attribute label of each economic block, thereby improving the accuracy and real-time performance of regional economic activity assessment, and effectively solving the problems of low accuracy and poor real-time performance of economic activity assessment in the prior art.

[0018] 2. The present invention collects and analyzes the traffic impact parameter sets of each branch economic block cluster and combines them with the classification of traffic complexity indicators, thereby achieving a fine division of branch economic block clusters, thereby improving the precise matching of traffic complexity and economic activity.

[0019] 3. By formatting and storing the classified output data, generating query indexes, and setting up an automatic update mechanism, the efficiency of data storage and query is improved, thereby achieving efficient management and real-time updating of economic activity analysis data. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flow chart of a method for analyzing regional economic activity based on highway ETC data provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The embodiment of the present application solves the problems of low accuracy and poor real-time performance of economic activity assessment in the prior art by providing a regional economic activity analysis method based on highway ETC data. The method divides the area that needs to be analyzed for economic activity into economic blocks, and counts the highway ETC data of each economic block in a preset period; based on the highway ETC data of each economic block, analyzes and obtains the highway traffic activity index of each economic block, and simultaneously determines and obtains the highway traffic activity attribute label of each economic block; based on the highway traffic activity attribute label of each economic block, aggregates and classifies to obtain economic block groups corresponding to each traffic activity attribute label; based on the economic block groups corresponding to each traffic activity attribute label, collects and analyzes the traffic impact parameter sets of the economic block groups, integrates to obtain each branch economic block cluster corresponding to each traffic activity attribute label, and classifies the highway ETC data of each branch economic block cluster in the preset period, thereby achieving accuracy and real-time performance in regional economic activity assessment.

[0022] The technical solution in the embodiment of the present application is to solve the above-mentioned problems of low accuracy and poor real-time performance in economic activity assessment. The overall idea is as follows: the area that needs to be analyzed for economic activity is divided into economic blocks, and the highway ETC data of each economic block is counted in a preset period; based on the highway ETC data of each economic block, the highway traffic activity index of each economic block is obtained by analysis, and the highway traffic activity attribute label of each economic block is obtained by simultaneous determination; based on the highway traffic activity attribute label of each economic block, aggregation and classification are performed to obtain economic block groups corresponding to each traffic activity attribute label; based on the economic block groups corresponding to each traffic activity attribute label, the traffic impact parameter set of the economic block group is collected and analyzed, and each branch economic block cluster corresponding to each traffic activity attribute label is obtained by integration, and the highway ETC data of each branch economic block cluster in the preset period is classified and output for display, thereby achieving the accuracy and real-time performance of regional economic activity assessment.

[0023] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0024] like Figure 1 As shown, it is a flow chart of the regional economic activity analysis method based on highway ETC data provided in an embodiment of the present application, and the method includes the following steps: dividing the area that needs to be analyzed for economic activity to obtain various economic blocks, and counting the highway ETC data of each economic block in a preset period; according to the highway ETC data of each economic block, analyzing to obtain the highway traffic activity index of each economic block, and simultaneously determining to obtain the highway traffic activity attribute label of each economic block; based on the highway traffic activity attribute label of each economic block, performing aggregation and classification to obtain the economic block group corresponding to each traffic activity attribute label; according to the economic block group corresponding to each traffic activity attribute label, collecting the traffic impact parameter set of the economic block group for analysis, integrating to obtain each branch economic block cluster corresponding to each traffic activity attribute label, and classifying the highway ETC data of each branch economic block cluster in the preset period for output and display.

[0025] In this embodiment, it should be noted that the existing economic growth forecasts, such as GDP data statistics, are cyclical forecasts with obvious time lags. There is currently no fast and flexible economic activity forecasting and evaluation scheme for regional economic activity. Therefore, there is an urgent need for a forecasting and evaluation method for regional economic activity in different regions to characterize the local regional economic activity in the current time period. Therefore, a regional economic activity analysis method for highway ETC data is proposed. The regional economic activity analysis method for highway ETC data can characterize the economic activity level of a preset region to a certain extent. If the regional economic activity of highway ETC data is high, the economic activity level in the region is relatively high.

[0026] By dividing the area where economic activity analysis is required into economic blocks, the ETC data of highways can be more refinedly counted and managed. Block processing makes data collection and analysis more accurate, and can also evaluate the traffic activity in different areas in a targeted manner, avoiding the possible deviation problem in the global analysis. By counting the ETC data of highways within a preset period, the dynamic change law of traffic flow in the region can be captured. The periodic statistical method not only helps the comparative analysis of data, but also provides the activity trend of continuous time periods, providing a reliable basis for subsequent traffic planning and optimization. By analyzing the ETC data of highways in each economic block and calculating the traffic activity index, the traffic activity can be quantitatively evaluated, and the traffic activity attribute label (such as very active, medium active, low active) can be determined for each economic block simultaneously, which can quickly classify regional characteristics. Different activity labels can be used as the basis for regional priority development, resource allocation or traffic control to improve management efficiency.

[0027] When performing aggregation classification, economic blocks need to be merged into economic block groups based on the similarity of traffic active attribute labels. During the aggregation process, boundary blocks (i.e., multi-label cross-blocks) need to be specially processed, such as prioritizing classification according to the main active attribute labels to ensure the uniqueness and consistency of the classification results. When collecting traffic impact parameters of economic block groups, not only the overall average value of the group is collected, but also the standard deviation of the parameters of each block needs to be recorded to evaluate the differences within each block. The integrated parameter set can not only characterize the overall characteristics of the block group, but also reveal the level of traffic complexity within the block. The highway ETC data of each branch economic block cluster is classified and output for display, which can intuitively display the traffic characteristics of each branch block, such as the trend of traffic flow changes and the proportion of vehicle types. It helps the transportation planning department to quickly grasp the regional traffic conditions and formulate precise control strategies.

[0028] It should be noted that the highway ETC data of each branch economic block cluster in the preset period are classified and output and displayed, specifically including: summarizing the branch economic block clusters, obtaining the highway ETC data corresponding to each branch economic block cluster in the preset period, and outputting and displaying the highway ETC data in the preset period in the form of a bar chart.

[0029] Furthermore, statistics are collected on the highway ETC data of each economic zone, including the number of vehicles of each type, the total number of vehicles, the average vehicle speed and the average vehicle driving time in a preset period.

[0030] Furthermore, based on the ETC data of highways in each economic block, the highway traffic activity index of each economic block is obtained through analysis. The specific method is as follows: the number of each type of vehicles and the total number of vehicles in each economic block are averaged to obtain the average number of each type of vehicles; the maximum average vehicle speed and the maximum average vehicle driving time of the economic block in a preset period are obtained, and combined with the average number of each type of vehicles as ETC reference data; based on the ETC data of highways in each economic block, the highway traffic activity index of each economic block is obtained through analysis with the ETC reference data.

[0031] In this embodiment, the highway ETC data of each economic block is processed by averaging, which can eliminate the impact of short-term fluctuations and outliers in the data on the analysis results, and ensure that the statistics of the number of vehicles of each type and the total number of vehicles are more representative. The stability of the data after averaging helps to make horizontal and vertical comparisons of the traffic activity of economic blocks in different time periods. By combining multi-dimensional ETC data with reference data for analysis, the traffic activity of each economic block can be accurately quantified. This not only provides a scientific basis for regional traffic planning and management, but also provides support for early warning of abnormal events (such as congestion and accidents).

[0032] Furthermore, the highway traffic activity index of each economic zone is obtained. The specific method is as follows: ; In the formula, represents the highway traffic activity index of the i-th economic block, i represents the number of the economic block, , I represents the total number of economic blocks, j represents the number of vehicle types, , Indicates the total number of vehicle types, represents the number of vehicles of type j in the i-th economic block, represents the average number of vehicles of type j, e represents a natural constant, represents the total number of vehicles in the i-th economic block, represents the average speed of vehicles in the i-th economic block, Indicates the maximum average speed of the vehicle. represents the average driving time of vehicles in the i-th economic block, Indicates the maximum average driving time of the vehicle, Indicates the weight of the number of vehicle types, Indicates the total number of vehicles affecting the weight, Indicates the influence weight of the average vehicle speed, Indicates the impact weight of the average driving time of vehicles.

[0033] In this embodiment, it should be noted that the number of vehicles of each type, the total number of vehicles, the average vehicle speed and the average vehicle driving time can be obtained through statistics in the background of the highway ETC toll collection system.

[0034] The highway traffic activity index of each economic zone is obtained by analyzing the number of each type of vehicles, the total number of vehicles, the average vehicle speed and the average vehicle driving time. This is based on the mutual influence between these parameters. For example, the number of each type of vehicles (such as buses and trucks) directly affects the total number of vehicles. An increase in vehicles can lead to an increase in traffic flow density. When traffic density increases, the average vehicle speed will decrease. At the same time, changes in vehicle speed will affect the driving time: when the speed is low, the vehicle stays on the road longer, thereby increasing the average vehicle driving time. Conversely, when the driving speed increases, the driving time will be shortened accordingly. In addition, the traffic ratio of trucks and buses will also affect the speed. For example, trucks usually occupy more road resources, and their increase may more significantly reduce the speed and increase the driving time, while buses have a relatively small impact on the speed.

[0035] The weights affecting the number of vehicle types, the weights affecting the total number of vehicles, the weights affecting the average vehicle speed and the weights affecting the average vehicle driving time can be obtained through a database. For example, the weights affecting the number of vehicle types can be obtained by inputting the number of vehicles of each type into the database to obtain the proportion of each type of vehicle in the total number, and the weights affecting the number of vehicle types can be obtained by mapping the proportion one-to-one with the proportion preset in the database. The weights affecting the total number of vehicles, the weights affecting the average vehicle speed and the weights affecting the average vehicle driving time can be obtained by inputting the total number of vehicles, the average vehicle speed and the average vehicle driving time into the database. If the total number of vehicles, the average vehicle speed and the average vehicle driving time are within a preset range in the database, the weights affecting the preset range are obtained as the weights affecting the total number of vehicles, the weights affecting the average vehicle speed and the weights affecting the average vehicle driving time, respectively.

[0036] Furthermore, the highway traffic activity attribute label of each economic block is synchronously determined. The specific method is: obtain the first traffic activity threshold and the second traffic activity threshold preset in the database, and compare them with the highway traffic activity index of each economic block. If the highway traffic activity index of an economic block is greater than the first traffic activity threshold, then the highway traffic activity attribute label of the economic block is a high-activity label. If the highway traffic activity index of an economic block is below the first traffic activity threshold and greater than the second traffic activity threshold, then the highway traffic activity attribute label of the economic block is a medium-activity label. If the highway traffic activity index of an economic block is below the second traffic activity threshold, then the highway traffic activity attribute label of the economic block is a low-activity label.

[0037] In this embodiment, by synchronously determining and assigning traffic activity attribute labels (such as very active, medium active, and low active) to each economic block, rapid classification of regional traffic activity status can be achieved, which is not only convenient for subsequent aggregate classification and optimization analysis, but also intuitively reveals the differences in traffic activity in different regions, which helps to allocate resources and formulate strategies in a targeted manner. The setting of active attribute labels is to manage the degree of traffic activity in a hierarchical manner. Highly active labels correspond to traffic-intensive areas, and traffic relief measures can be planned first; medium-active labels reflect normal traffic areas, providing a basis for resource allocation; and low-active labels point to areas that need to optimize traffic facilities or increase economic activity.

[0038] Furthermore, based on the highway traffic activity attribute label of each economic block, aggregation and classification are performed to obtain the economic block group corresponding to each traffic activity attribute label. The specific method is: the economic blocks with the same highway traffic activity attribute label are classified to obtain the economic blocks corresponding to each traffic activity attribute label, and the economic blocks corresponding to the same traffic activity attribute label are aggregated to obtain the economic block group corresponding to each traffic activity attribute label.

[0039] In this embodiment, a dynamic aggregation mechanism is introduced during the aggregation and classification. For example, during holidays or peak hours, the classification of economic block groups is dynamically adjusted according to the active attribute tags updated in real time, which can provide support for the flexible deployment of traffic resources.

[0040] Furthermore, the traffic impact parameter set of the economic block group is collected for analysis, specifically including: based on the economic block group corresponding to each traffic active attribute label, and recording several economic blocks covered in the economic block group as branch economic blocks; collecting the traffic impact parameter set of the economic block group, including the population density, permanent population, public transportation coverage rate, total number of highway entrances and exits, and total number of road intersections of each branch economic block; constructing the traffic complexity index correction factor of each branch economic block, and analyzing based on the traffic impact parameter set of the economic block group to obtain the traffic complexity index of each branch economic block.

[0041] In this embodiment, the economic block group corresponding to the traffic active attribute label is further divided into several branch economic blocks, which helps to analyze the traffic characteristics in different areas more accurately. The division of branch economic blocks fully considers the heterogeneity of traffic attributes between regions. The collected traffic impact parameters (such as population density, permanent population, public transportation coverage, total number of highway entrances and exits, and total number of road intersections) can reflect the traffic characteristics of branch economic blocks from multiple dimensions. Through diversified data dimensions, the analysis results of traffic complexity indicators are ensured to be more comprehensive and accurate. The mean processing of the traffic impact parameter set of the economic block group can reduce the analysis deviation caused by data fluctuations. At the same time, the parameter reference set obtained after the mean processing can not only reflect the overall traffic characteristics of the economic block group, but also provide a benchmark for anomaly detection of branch economic blocks.

[0042] The traffic complexity index of each branch economic block comprehensively considers the relationship between the traffic impact parameters and the reference set, and quantifies the traffic complexity of the branch economic block. The branch economic block clusters are divided into the first, second and third clusters, which can intuitively display the traffic complexity of each area. Among them, the first cluster usually corresponds to areas with heavy traffic burdens, which need to give priority to traffic resource allocation or improvement; the second cluster reflects the medium traffic complexity area, which can be used as the object of normal management; the third cluster represents the area with low traffic complexity.

[0043] Furthermore, each branch economic block cluster corresponding to each traffic activity attribute label is obtained. The specific method is: obtain the first threshold value of the traffic complexity index and the second threshold value of the traffic complexity index preset in the database, and compare them with the traffic complexity index of each branch economic block respectively. If the traffic complexity index of a branch economic block is greater than the first threshold value of the traffic complexity index, then the traffic complexity index of the branch economic block belongs to the first branch economic block cluster, and the traffic activity attribute label corresponding to the traffic complexity index of the branch economic block is divided into the first branch economic block cluster. If the traffic complexity index of a branch economic block is below the first threshold value of the traffic complexity index and greater than the second threshold value of the traffic complexity index, then the traffic complexity index of the branch economic block belongs to the second branch economic block cluster. economic block cluster, the traffic activity attribute label corresponding to the traffic complexity index of the branch economic block is divided into the second branch economic block cluster; if the traffic complexity index of a branch economic block is below the first threshold of the traffic complexity index, the traffic complexity index of the branch economic block belongs to the third branch economic block cluster, and the traffic activity attribute label corresponding to the traffic complexity index of the branch economic block is divided into the third branch economic block cluster; count the branch economic block clusters and traffic activity attribute labels corresponding to each branch economic block, and aggregate the branch economic blocks belonging to the same traffic activity attribute label and the same branch economic block cluster into a branch economic block cluster, thereby obtaining the branch economic block clusters corresponding to each traffic activity attribute label one by one.

[0044] In this embodiment, the traffic complexity index of each branch economic block is obtained by: ; In the formula, represents the traffic complexity index of the kth branch economic block, e represents the natural constant, k represents the number of each economic block, , Indicates the total number of economic blocks, represents the population density of the k-th branch economic block, represents the number of permanent residents in the k-th branch economic block, represents the public transportation coverage rate of the k-th branch economic block, represents the total number of highway entrances and exits of the k-th branch economic block, represents the total number of road intersections in the k-th branch economic block, represents the traffic complexity correction factor of the kth economic block, represents the weight of population density, Indicates the influence weight of the permanent population, represents the impact weight of public transportation coverage, Indicates the total number of highway entrances and exits affecting the weight, Indicates the influence weight of the total number of road intersections.

[0045] The method of obtaining the influence weights, the influence weights of population density, permanent population, public transportation coverage, total number of highway entrances and exits, and total number of road intersections can be obtained through a database, for example: by inputting the population density, permanent population, public transportation coverage, total number of highway entrances and exits, and total number of road intersections into the database; if the input population density, permanent population, public transportation coverage, total number of highway entrances and exits, and total number of road intersections fall within a certain interval preset in the database, then the influence weight corresponding to the interval is obtained as the influence weight corresponding to the input population density, permanent population, public transportation coverage, total number of highway entrances and exits, and total number of road intersections data.

[0046] It should be noted that the public transportation coverage rate indicates the ratio of the geographical area covered by public transportation lines to the total area of ​​the region. The geographical area covered by public transportation lines and the total area of ​​the region can be obtained by querying the back-end relationship system of the public transportation bureau.

[0047] It should be noted that the historical traffic impact parameter set of each branch economic block includes: the historical population density, historical permanent population, historical public transportation coverage, total number of historical highway entrances and exits, and total number of historical road intersections of each branch economic block.

[0048] It should be noted that the historical population density, historical permanent population, and historical public transportation coverage of each branch economic block can be obtained by obtaining the most recent historical statistical data from census data reports, urban planning reports, transportation department reports, etc. The total number of historical highway entrances and exits and the total number of historical road intersections can be obtained from the most recent historical statistical report on the official website of the local transportation department.

[0049] The traffic change index of each branch economic block is obtained by: ; In the formula, represents the traffic change index of the k-th branch economic block, e represents the natural constant, k represents the number of each economic block, , Indicates the total number of economic blocks, represents the historical population density of the k-th branch economic block, represents the historical permanent population of the k-th branch economic block, represents the historical public transportation coverage rate of the k-th branch economic block, represents the total number of historical highway entrances and exits of the k-th branch economic block, represents the total number of historical road intersections of the k-th branch economic block, represents the impact weight of historical population density, Indicates the impact weight of the historical permanent population, represents the impact weight of historical public transportation coverage, Indicates the impact weight of the total number of historical highway entrances and exits, Indicates the influence weight of the total number of historical road intersections.

[0050] Population density and permanent population reflect the living conditions of the area. An increase in population density will lead to an increase in permanent population, and the demand for public transportation will gradually increase, thereby increasing the public transportation coverage rate. An increase in public transportation coverage may lead to an increase in the number of vehicles of all types, thereby increasing the frequency of use of highway entrances and exits and the traffic pressure at road intersections. The change in the total number of highway entrances and exits is related to the construction of the regional transportation network. The increase in entrances and exits will improve traffic accessibility and increase traffic flow, thereby increasing the complexity of the total road intersections. The more total road intersections, the greater the traffic difficulty.

[0051] The impact weights of historical population density, historical permanent population, historical public transportation coverage, historical total number of highway entrances and exits, and historical total number of road intersections can be obtained through a database. For example, the historical population density, historical permanent population, historical public transportation coverage, total number of historical highway entrances and exits, and total number of historical road intersections are input into the database. If the input historical population density, historical permanent population, historical public transportation coverage, total number of historical highway entrances and exits, and total number of historical road intersections are within a preset numerical range in the database, the impact weights corresponding to the numerical range are obtained as the impact weight of historical population density, historical permanent population, historical public transportation coverage, total number of historical highway entrances and exits, and total number of historical road intersections.

[0052] Furthermore, a traffic complexity index correction factor for each branch economic block is constructed. The specific steps include: obtaining the historical traffic impact parameter set of each branch economic block and analyzing it to obtain the traffic change index of each branch economic block; obtaining each traffic change index interval preset in the database and the traffic complexity index correction factor corresponding to each traffic change index interval. If the traffic change index of a branch economic block is within a preset traffic change index interval, then the traffic complexity index correction factor corresponding to the traffic change index interval is obtained as the traffic complexity index correction factor of the branch economic block; the traffic change index of each branch economic block is used to characterize the degree of change between the traffic and historical traffic of each branch economic block.

[0053] In this embodiment, by introducing the first threshold of traffic complexity index and the first threshold of traffic complexity index, it is helpful to tailor reasonable economic development promotion measures for each economic block and improve the overall activity of regional economy. Compared with the traditional simple division method, the refined classification based on traffic complexity in this scheme can effectively improve the accuracy of economic activity analysis and reflect the close relationship between traffic and economic activity.

[0054] Furthermore, it also includes: storing the data displayed by the classified output, and the specific process is: According to each branch economic block cluster corresponding to each traffic activity attribute label, and based on the traffic complexity index of each branch economic block, the average traffic complexity index of each branch economic block cluster corresponding to each traffic activity attribute label is statistically obtained; based on the data storage execution compression ratio of each branch economic block cluster corresponding to each traffic activity attribute label in each average traffic complexity index interval preset in the database, the data storage execution compression ratio of the interval where the average traffic complexity index of each branch economic block cluster corresponding to each traffic activity attribute label is located is screened, and recorded as the target data storage execution compression ratio of each branch economic block cluster corresponding to each traffic activity attribute label, and the highway ET0 data of each branch economic block cluster corresponding to each traffic activity attribute label is compressed and stored at the corresponding target data storage execution compression ratio.

[0055] In this embodiment, by storing and formatting the data displayed by the classified output, the data from each branch economic block cluster can be effectively organized and managed. Storing the processed data in the storage unit corresponding to the database helps to improve the queryability and persistence of the data and avoids the loss or confusion of information that may exist during the processing of the original data. Setting up an automatic update mechanism can ensure that the data is updated in real time as time passes or as economic activities continue to change, and can automatically synchronize the data and analysis results in the database to ensure the timeliness of the analysis report and decision-making basis.

[0056] By formatting the classified output data, the data structure can be consistent, which is convenient for storage and subsequent operations, helps reduce redundancy when storing data, and ensures data standardization and consistency. After the stored data is automatically updated and the query index is generated, the user's query request can be quickly responded to, further improving the real-time and interactivity of the data analysis system. Users or decision makers can quickly obtain historical data, current status, and future forecasts of different branch economic block clusters as needed.

[0057] Outputting data in a visual way can more intuitively show the economic activity and traffic flow trends of each branch economic block. Visualization charts such as maps, charts and trend charts can help users understand complex data more quickly and discover potential economic development hotspots, thereby providing a clearer perspective for strategic decision-making.

[0058] To sum up, this embodiment obtains and analyzes the highway ETC data of each economic block to obtain the highway traffic activity index and traffic activity attribute label of each economic block, thereby improving the accuracy and real-time performance of regional economic activity assessment, and effectively solving the problems of low accuracy and poor real-time performance of economic activity assessment in the prior art.

[0059] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0060] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0061] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0062] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0063] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0064] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for analyzing regional economic activity based on highway ETC data, characterized in that: The following steps are involved: The area that needs to be analyzed for economic activity is divided into economic blocks, and the highway ETC data of each economic block is counted in a preset period; According to the ETC data of highways in each economic block, the highway traffic activity index of each economic block is obtained through analysis, and the highway traffic activity attribute label of each economic block is obtained through simultaneous determination; Based on the highway traffic activity attribute labels of each economic block, aggregate classification is performed to obtain the economic block groups corresponding to each traffic activity attribute label; According to the economic block groups corresponding to each traffic active attribute label, the traffic impact parameter set of the economic block group is collected for analysis, and the branch economic block clusters corresponding to each traffic active attribute label are integrated, and the highway ETC data of each branch economic block cluster in the preset period are classified, output and displayed.

2. The method for analyzing regional economic activity based on highway ETC data as claimed in claim 1, characterized in that: The statistics of highway ETC data of each economic block specifically include the number of vehicles of each type, the total number of vehicles, the average vehicle speed and the average vehicle driving time in a preset period.

3. The method for analyzing regional economic activity based on highway ETC data as claimed in claim 1, characterized in that: The highway ETC data of each economic block is analyzed to obtain the highway traffic activity index of each economic block. The specific method is as follows: The number of each type of vehicles and the total number of vehicles in each economic block are averaged to obtain the average number of each type of vehicles; Obtain the maximum average vehicle speed and the maximum average vehicle driving time in the economic block in the preset period, and combine them with the average number of each type of vehicle as ETC reference data; Based on the ETC data of highways in each economic block and analyzed with the ETC reference data, the highway traffic activity index of each economic block is obtained.

4. The regional economic activity analysis method based on highway ETC data as claimed in claim 1 is characterized by: The specific method for obtaining the highway traffic activity index of each economic block is as follows: ； In the formula, represents the highway traffic activity index of the i-th economic block, i represents the number of the economic block, , I represents the total number of economic blocks, j represents the number of vehicle types, , Indicates the total number of vehicle types, represents the number of vehicles of type j in the i-th economic block, represents the average number of vehicles of type j, e represents a natural constant, represents the total number of vehicles in the i-th economic block, represents the average speed of vehicles in the i-th economic block, Indicates the maximum average speed of the vehicle. represents the average driving time of vehicles in the i-th economic block, Indicates the maximum average driving time of the vehicle, Indicates the number of vehicle types that influence the weight, Indicates the total number of vehicles affecting the weight, Indicates the influence weight of the average vehicle speed, Indicates the impact weight of the average vehicle driving time.

5. The method for analyzing regional economic activity based on highway ETC data as claimed in claim 1, characterized in that: The synchronous determination obtains the highway traffic activity attribute label of each economic block, and the specific method is as follows: The first traffic activity threshold and the second traffic activity threshold preset in the database are obtained, and compared with the highway traffic activity index of each economic block. If the highway traffic activity index of an economic block is greater than the first traffic activity threshold, the highway traffic activity attribute label of the economic block is a high-activity label. If the highway traffic activity index of an economic block is below the first traffic activity threshold and greater than the second traffic activity threshold, the highway traffic activity attribute label of the economic block is a medium-activity label. If the highway traffic activity index of an economic block is below the second traffic activity threshold, the highway traffic activity attribute label of the economic block is a low-activity label.

6. The method for analyzing regional economic activity based on highway ETC data as claimed in claim 1, characterized in that: The above-mentioned method of performing aggregation classification based on the highway traffic activity attribute labels of each economic block to obtain the economic block groups corresponding to each traffic activity attribute label is as follows: The economic blocks with the same highway traffic activity attribute label are classified to obtain the economic blocks corresponding to each traffic activity attribute label, and the economic blocks corresponding to the same traffic activity attribute label are aggregated to obtain the economic block groups corresponding to each traffic activity attribute label.

7. The method for analyzing regional economic activity based on highway ETC data as claimed in claim 1, characterized in that: The collection of traffic impact parameter sets of economic block groups for analysis specifically includes: Based on the economic block group corresponding to each traffic active attribute label, several economic blocks covered in the economic block group are recorded as branch economic blocks; Collect the traffic impact parameter set of the economic block group, including the population density, permanent population, public transportation coverage, total number of highway entrances and exits, and total number of road intersections of each branch economic block; The traffic complexity index correction factor of each branch economic block is constructed, and the traffic complexity index of each branch economic block is obtained based on the traffic impact parameter set of the economic block group.

8. The method for analyzing regional economic activity based on highway ETC data as claimed in claim 7, characterized in that: The specific method for obtaining each branch economic block cluster corresponding to each traffic active attribute label is as follows: Obtain the first threshold value and the second threshold value of the traffic complexity index preset in the database, and compare them with the traffic complexity index of each branch economic block respectively; if the traffic complexity index of a branch economic block is greater than the first threshold value of the traffic complexity index, the traffic complexity index of the branch economic block belongs to the first branch economic block cluster, and the traffic activity attribute label corresponding to the traffic complexity index of the branch economic block is divided into the first branch economic block cluster; if the traffic complexity index of a branch economic block is below the first threshold value of the traffic complexity index and greater than the second threshold value of the traffic complexity index, the traffic complexity index of the branch economic block belongs to the second branch economic block cluster, and the traffic activity attribute label corresponding to the traffic complexity index of the branch economic block is divided into the second branch economic block cluster; if the traffic complexity index of a branch economic block is below the first threshold value of the traffic complexity index, the traffic complexity index of the branch economic block belongs to the third branch economic block cluster, and the traffic activity attribute label corresponding to the traffic complexity index of the branch economic block is divided into the third branch economic block cluster; The branch economic block clusters and traffic activity attribute labels corresponding to each branch economic block are counted, and the branch economic blocks belonging to the same traffic activity attribute label and the same branch economic block cluster are aggregated into branch economic block clusters, thereby obtaining the branch economic block clusters corresponding to each traffic activity attribute label by counting them one by one.

9. The method for analyzing regional economic activity based on highway ETC data as claimed in claim 7, characterized in that: The specific steps of constructing the traffic complexity index correction factor of each branch economic block include: Obtain and analyze the historical traffic impact parameter set of each branch economic block to obtain the traffic change index of each branch economic block; Obtain each traffic change index interval preset in the database and the traffic complexity index correction factor corresponding to each traffic change index interval. If the traffic change index of a branch economic block is within a preset traffic change index interval, obtain the traffic complexity index correction factor corresponding to the traffic change index interval as the traffic complexity index correction factor of the branch economic block; The traffic change index of each branch economic block is used to characterize the degree of change of the traffic of each branch economic block compared with the historical traffic.

10. The method for analyzing regional economic activity based on highway ETC data according to claim 1, characterized in that: Also includes: The data displayed by the classification output is stored in data format. The specific process is as follows: According to each branch economic block cluster corresponding to each traffic activity attribute label, and based on the traffic complexity index of each branch economic block, the average traffic complexity index of each branch economic block cluster corresponding to each traffic activity attribute label is obtained from the statistics; Based on the data storage execution compression ratio of each branch economic block cluster corresponding to each traffic activity attribute label preset in the database in each average traffic complexity index interval, the data storage execution compression ratio of the interval where the average traffic complexity index of each branch economic block cluster corresponding to each traffic activity attribute label is located is screened out, and recorded as the target data storage execution compression ratio of each branch economic block cluster corresponding to each traffic activity attribute label, and the highway ET0 data of each branch economic block cluster corresponding to each traffic activity attribute label is compressed and stored at the corresponding target data storage execution compression ratio.

Images