A city-county traffic data analysis method, device, equipment and storage medium

Abstract

The present application relates to the technical field of traffic network analysis, and particularly relates to a city-county traffic data analysis method, device, equipment and storage medium; traffic basic data is collected according to a preset target city-county specified period; feature extraction is performed on the traffic basic data according to a preset spatial feature extraction method to obtain a traffic data coordinate set; topology analysis is performed on the traffic data coordinate set based on a preset polyline geometry structure and a preset topology adjustment method to obtain a collated status road network; the collated status road network is optimized based on a preset Arcmap tool, a preset straight line intersection mathematical principle and a preset geographic information system to obtain a visualized traffic road network; by extracting the traffic data coordinate set and regularizing and optimizing the road network, relying on algorithm matching of traffic flow information, visualized display of traffic situation is realized, manpower cost is saved, data analysis accuracy is improved, and strong decision basis can be provided for regional traffic planning, road network optimization and traffic control.

Description

Technical Field

[0001] This invention relates to the field of traffic network analysis technology, and in particular to a method, apparatus, equipment and storage medium for analyzing traffic data in cities and counties. Background Technology

[0002] Currently, in the field of urban and rural traffic network assessment and traffic flow analysis, data processing methods are disorganized, making it difficult to quickly extract effective spatial coordinate information, resulting in low utilization of raw data. During the construction of the road network, there is a lack of topology correction processes, leading to problems such as disordered nodes, disconnected lines, and chaotic topological relationships. Spatial matching accuracy is low, and traffic flow statistics often rely on rough estimation methods, resulting in significant discrepancies between traffic distribution results and actual traffic conditions. Furthermore, most analysis results are presented only in text and table formats, lacking sufficient visualization and failing to intuitively reflect the characteristics of traffic flow distribution in the road network. This makes it difficult to efficiently support various traffic operations such as traffic planning, congestion management, and road network layout optimization. Summary of the Invention

[0003] In order to overcome the shortcomings of the prior art, the purpose of this invention is to provide a method, apparatus, equipment and storage medium for analyzing traffic data in cities and counties.

[0004] The first aspect of this invention provides a method for analyzing traffic data in cities and counties, comprising: collecting basic traffic data according to a preset target city or county and a specified time period; extracting features from the basic traffic data according to a preset spatial feature extraction method to obtain a traffic data coordinate set; performing topological analysis on the traffic data coordinate set based on a preset polyline geometry and a preset topology adjustment method to obtain an organized current road network; and optimizing the organized current road network based on a preset ArcMap tool, a preset mathematical principle of line intersection, and a preset geographic information system to obtain a visualized traffic flow road network.

[0005] Furthermore, the step of extracting features from traffic baseline data according to a preset spatial feature extraction method to obtain a traffic data coordinate set includes: verifying the traffic baseline data according to a preset spatial verification range and a preset outlier detection method to obtain basic valid results; assigning values ​​to the basic valid results according to a preset Dpop field to obtain basic traffic information; and extracting features from the traffic baseline information according to the spatial feature extraction method to obtain a traffic data coordinate set.

[0006] Furthermore, the optimization of the existing road network based on preset ArcMap tools, preset mathematical principles of line intersection, and preset geographic information systems to obtain a visualized traffic flow road network includes: optimizing the existing road network based on ArcMap tools, preset length parameters, and preset filtering conditions to obtain an optimized city and county road network; configuring the optimized city and county road network based on the mathematical principles of line intersection and preset spatial connection tools to obtain a traffic flow road network; and rendering the traffic flow road network based on a geographic information system to obtain a visualized traffic flow road network.

[0007] Furthermore, the optimization of the existing road network based on ArcMap, preset length parameters, and preset filtering conditions to obtain an optimized city and county road network includes: splitting the existing road network using ArcMap to obtain multiple inter-node road segments; performing midpoint coordinate analysis on the multiple inter-node road segments to obtain multiple midpoint coordinates; generating multiple perpendicular bisectors based on the length parameters and multiple midpoint coordinates; filtering all perpendicular bisectors based on the filtering conditions to obtain a set of perpendicular bisectors; and generating an optimized city and county road network based on the set of perpendicular bisectors and the multiple inter-node road segments.

[0008] Furthermore, the configuration of the optimized city and county road network based on the mathematical principle of straight line intersection and the preset spatial connection tool to obtain the traffic flow road network includes: performing spatial intersection analysis on the existing road network and the optimized city and county road network based on the mathematical principle of straight line intersection to obtain the intersection analysis results; extracting traffic flow characteristics from the existing road network based on the intersection analysis results; and configuring the optimized city and county road network based on the spatial connection tool and the traffic flow characteristics to obtain the traffic flow road network.

[0009] Furthermore, the step of rendering the traffic flow network based on a geographic information system to obtain a visualized traffic flow network includes: performing a deductive analysis of the traffic flow network according to a preset time-series traffic flow model to obtain traffic flow deductive characteristics; performing a hierarchical analysis of the traffic flow network according to the traffic flow deductive characteristics and a preset traffic flow hierarchical analysis method to obtain markers for ultra-high traffic flow sections, bottleneck sections, and abnormal change sections; and rendering the traffic flow network based on the geographic information system, ultra-high traffic flow section markers, bottleneck section markers, and abnormal change section markers to obtain a visualized traffic flow network.

[0010] Furthermore, the step of performing topological analysis on the traffic data coordinate set based on a preset polyline geometry and a preset topology adjustment method to obtain a reorganized existing road network includes: performing coordinate transformation on the traffic data coordinate set based on a preset coordinate transformation algorithm and a preset geodetic coordinate system to obtain a correction coordinate set; organizing and constructing the correction coordinate set based on the polyline geometry to obtain the existing road network; and performing topological adjustment on the existing road network according to the topology adjustment method and preset topology adjustment conditions to obtain a reorganized existing road network.

[0011] Furthermore, a city / county traffic data analysis device includes: a data acquisition module for collecting basic traffic data according to a preset target city / county and a specified time period; a feature extraction module for extracting features from the basic traffic data according to a preset spatial feature extraction method to obtain a traffic data coordinate set; a topology analysis module for performing topology analysis on the traffic data coordinate set based on a preset polyline geometry and a preset topology adjustment method to obtain an organized current road network; and an optimization processing module for optimizing the organized current road network based on a preset ArcMap tool, a preset mathematical principle of line intersection, and a preset geographic information system to obtain a visualized traffic flow road network.

[0012] Furthermore, a city / county traffic data analysis device includes: a memory and at least one processor, wherein the memory stores instructions; the at least one processor invokes the instructions in the memory to cause the city / county traffic data analysis device to execute the various steps of the city / county traffic data analysis method described above.

[0013] Furthermore, a computer-readable storage medium stores instructions that, when executed by a processor, implement the various steps of the city and county traffic data analysis method described above.

[0014] In the technical solution of this invention, basic traffic data is collected based on the target city / county and a specified time period using the Gaode Map interface. This method is efficient, timely, and reduces labor costs, while providing raw regional travel data. A spatial feature extraction method is used to extract features from the basic traffic data to obtain a traffic data coordinate set, simplifying subsequent data processing. Then, a polyline geometry structure and topology adjustment techniques are used to regulate the road network morphology, correct topological defects, and streamline road network connectivity, improving the standardization of road network data. Using ArcMap and the mathematical principle of line intersection, road network optimization and traffic flow matching are completed. Finally, a geographic information system is used to visualize the traffic flow data, providing a clear view of the overall traffic status and offering comprehensive and intuitive data and visualization support for city / county traffic planning, congestion management, road network optimization, and traffic management decisions. Attached Figure Description

[0015] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a first flowchart of a method for analyzing traffic data in cities and counties provided in an embodiment of the present invention; Figure 2 This is a second flowchart of a method for analyzing traffic data in cities and counties provided in an embodiment of the present invention; Figure 3 This is a third flowchart of a method for analyzing traffic data in cities and counties provided in an embodiment of the present invention; Figure 4 This is a fourth flowchart of a method for analyzing traffic data in cities and counties provided in an embodiment of the present invention; Figure 5 A fifth flowchart of a method for analyzing traffic data in cities and counties provided in an embodiment of the present invention; Figure 6 The sixth flowchart of a method for analyzing traffic data in cities and counties provided in this embodiment of the invention; Figure 7 A seventh flowchart of a method for analyzing traffic data in cities and counties provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of a city and county traffic data analysis device provided in an embodiment of the present invention; Figure 9 This is a schematic diagram of the structure of a city and county traffic data analysis device provided in an embodiment of the present invention. Detailed Implementation

[0016] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1 One embodiment of a city and county traffic data analysis method according to the present invention includes: 101. Collect basic traffic data according to the preset target cities and counties and the specified time periods; In this embodiment, basic traffic data is collected based on the specified time period of the target city / county. Data acquisition is completed using the Gaode Map route planning API. By configuring the corresponding input parameters, multiple types of traffic-related data can be collected quickly. The collection method is convenient and efficient, and the data acquisition is timely. It can match the collection needs of time period and region, quickly collect standardized travel data, reduce manual collection costs, ensure stable and reliable data sources, and provide sufficient and timely data support for subsequent traffic data analysis and judgment. 102. Extract features from the traffic baseline data according to the preset spatial feature extraction method to obtain the traffic data coordinate set; In this embodiment, a preset spatial feature extraction method is used to perform in-depth analysis on the quality-verified traffic basic data, extracting spatial location information, removing irrelevant and redundant fields, and focusing on core geographic coordinate data. This method can efficiently filter out latitude and longitude point information in traffic basic data, and orderly integrate them into a standardized traffic data coordinate set. This solves the problem of spatial information and business information being mixed in traffic data, improves data regularity, provides a high-quality data source for subsequent spatial operations such as coordinate transformation and road network construction, ensures the smooth progress of subsequent related operations, simplifies the data processing flow, improves overall work efficiency, and lays a solid foundation for traffic data analysis. 103. Based on the preset polyline geometry and preset topology adjustment method, perform topology analysis on the traffic data coordinate set to obtain the current road network. In this embodiment, by employing a pre-defined polyline geometry and topology adjustment method, a system topology analysis is conducted on the traffic data coordinate set. This effectively standardizes the traffic data coordinates, corrects road network topology defects, and optimizes the road network structure. Through standardized topology adjustment, the problems of chaotic traffic data coordinates and unclear road network structure are resolved, improving the standardization and usability of road network data. Simultaneously, it further clarifies the road network relationships, solidifying the foundation for subsequent traffic flow statistics and road network optimization, effectively improving data processing efficiency, providing reliable road network support for traffic analysis and planning decisions, and contributing to enhancing the effectiveness of traffic management and planning. 104. Based on the preset ArcMap tool, the preset mathematical principle of line intersection, and the preset geographic information system, the existing road network is optimized to obtain a visualized traffic road network; In this embodiment, ArcMap is used to achieve refined optimization of the road network. The mathematical principle of straight line intersection is used to determine the correlation between lines to ensure the accuracy of traffic flow matching. Then, a geographic information system is used to complete the visualization rendering. The whole process is standardized and efficient, effectively improving the quality of road network optimization and the accuracy of traffic flow calculation. It transforms abstract road network and traffic flow data into intuitive visualization results, which facilitates quick understanding of the road network operation status and provides intuitive support for traffic analysis and planning optimization in cities and counties. In this embodiment, basic traffic data is collected based on the specified time period of the target city / county using the Gaode Map interface. This method is efficient, timely, and reduces labor costs, providing raw regional travel data. Spatial feature extraction methods are used to extract features from the basic traffic data to obtain a traffic data coordinate set, simplifying subsequent data processing. Then, polyline geometry and topology adjustment techniques are employed to regulate the road network morphology, correct topological defects, and streamline road network connectivity, improving the standardization of road network data. ArcMap is used in conjunction with the mathematical principle of line intersection to complete road network optimization and traffic flow matching. Finally, a geographic information system (GIS) is used to visualize the traffic flow data, providing a clear view of the overall traffic status and offering comprehensive and intuitive data and visualization support for city / county traffic planning, congestion management, road network optimization, and traffic management decisions.

[0018] Please see Figure 2 The second embodiment of a city and county traffic data analysis method according to the present invention specifically includes: 201. Verify the traffic baseline data according to the preset spatial verification range and the preset outlier detection method to obtain basic valid results; In this embodiment, the basic traffic data mainly includes travel-related data such as traffic origin-destination (OD) travel data. The traffic OD travel data verified in this study was collected through the Gaode Maps route planning interface. The data is presented as an array of coordinate pairs, consisting of multiple sets of latitude and longitude points in an orderly combination, which can completely represent the origin and destination points and travel path information. The spatial verification range is the pre-defined geographical coordinate boundary of the entire target city / county, clearly defining the reasonable range of latitude and longitude values ​​and delineating the geographical control area for effective data collection and statistics. The outlier detection method is an anomaly identification method based on spatial coordinate distance deviation judgment, which compares the point coordinates with the normal path. The offset difference of coordinates is used to quickly identify abnormal points that deviate from the normal traffic path; after completing the unified and standardized preprocessing and cleaning work, the data compliance space boundary is defined according to the pre-defined spatial inspection range. At the same time, the established outlier detection method is used to carry out abnormal data screening, and invalid data that exceeds the spatial range or has abnormal point logic is removed. The overall verification process uses manual random sampling verification as the final verification method to further confirm that the data point layout is reasonable and the coordinate sequence is coherent. After completing the entire verification process, the data is officially entered into the database, and finally a clean, standardized, and non-abnormal deviation basic effective result is formed, ensuring that the overall quality of the original traffic data entered into the database meets the standards. 202. Assign values ​​to the basic valid results according to the preset Dpop field to obtain basic traffic information; In this embodiment, the Dpop field is a pre-defined dedicated business identifier field. By retrieving the content of the Dpop field inherent in the basic valid results, the field content is filled and assigned to the corresponding position in the specified data structure table according to the established data table structure rules. Various data fields are arranged in accordance with business storage standards, and a compliant and complete data storage architecture is built in a unified manner. The data field arrangement and information binding work are completed, and standardized basic traffic information with complete fields, complete information, and unified format is successfully generated, thus improving the configuration of data business attributes. 203. Extract features from basic traffic information using spatial feature extraction methods to obtain a traffic data coordinate set; In this embodiment, the spatial feature extraction method is a spatial point filtering and parsing method for road network travel data. It uses geospatial location information as the core extraction method, organizes the data hierarchy according to the path travel logic, selectively filters and removes non-spatial redundant information within the travel data, and retains elements with geolocation functions. The relied-upon path planning API is a general service interface built on the HTTP communication protocol, which can stably provide query services for various travel modes such as driving, walking, and public transportation, while also supporting mileage calculation. The interface routinely returns data in two standardized formats: JSON and XML, enabling efficient automated path planning development and application. Based on a mature spatial feature extraction method, deep feature analysis is performed on the configured basic traffic information. Continuous latitude and longitude coordinates corresponding to each travel trajectory are sequentially extracted according to the path direction. Irrelevant and redundant business fields such as travel time, travel type, and traffic flow remarks are removed, retaining only the spatial point data required for the path direction. Points are sorted and integrated according to the actual travel sequence, and then orderly integrated into a coherent and regular coordinate point sequence. Finally, a clear and complete traffic data coordinate set is formed, providing the original data source for subsequent coordinate transformation, road network construction, and other spatial calculations. In this embodiment, by defining the spatial inspection range, combining the coordinate deviation outlier detection method with manual sampling verification, invalid traffic OD data outside the range and with abnormal trajectories can be efficiently screened out, controlling the quality of raw travel data and ensuring data authenticity and compliance. The pre-Dpop field is used to directly complete standardized assignment and normalization, quickly building a standardized data table structure and conveniently improving data business attributes. Relying on professional spatial feature extraction methods, continuous latitude and longitude coordinates are systematically extracted and integrated into a standard traffic data coordinate set. The entire data preprocessing process is clear, highly automated, simplifies the initial data organization work, effectively improves data normalization efficiency, and provides clean, standardized, and uniformly formatted high-quality raw data support for subsequent coordinate correction, road network construction, traffic flow matching, and other traffic data analysis and calculations.

[0019] Please see Figure 3The third embodiment of a city and county traffic data analysis method in this invention specifically includes: 301. Based on ArcMap tools, preset length parameters, and preset filtering conditions, optimize the existing road network to obtain an optimized city and county road network; In this embodiment, ArcMap is used to organize and decompose the existing road network. By combining the set length parameters, perpendicular lines are generated for each road segment. Short and invalid perpendicular lines at intersections and turns are then removed using preset filtering conditions, simplifying redundant data. The entire optimization process is standardized and orderly, ensuring reasonable road network segmentation and standardized auxiliary line layout. It also reduces unnecessary calculations, lowers the system load, and effectively improves the efficiency of subsequent spatial intersection determination and traffic flow statistics. The optimized city and county road network structure is concise and regular with stronger geometric adaptability, laying a solid and reliable foundation for subsequent traffic flow matching and data analysis. 302. Based on the mathematical principle of intersecting straight lines and the preset spatial connection tool, the city and county road network is configured to obtain the traffic flow road network; In this embodiment, the spatial relationship of routes is determined based on the mathematical principle of straight line intersection, and a matching correspondence is established between the current road network and the optimized city and county road network, effectively avoiding the problems of route mismatch and omission. With the help of spatial connection tools, traffic data is collected in batches and accumulated iteratively, and the Dpop traffic value is automatically matched to the corresponding road network segment, efficiently completing the assignment of traffic statistics across the entire region. This method has a rigorous data matching logic, and the traffic allocation is in line with the actual traffic patterns, improving the accuracy of traffic calculation and the efficiency of data processing. It can quickly generate a traffic flow road network with complete business attributes, providing reliable support for subsequent traffic assessment and data analysis. 303. Render the traffic flow network based on the geographic information system to obtain a visualized traffic flow network; In this embodiment, a traffic flow road network visualization rendering is completed by relying on a geographic information system. It can combine various attribute data such as road network traffic flow and traffic mode, and use multiple visualization methods such as hierarchical color and hierarchical scale to intuitively present the road network operation status. At the same time, it standardizes the configuration of cartographic elements such as traffic flow legends, north arrows and scale lines to form standard and standardized thematic analysis maps. This method can transform abstract traffic flow data into intuitive geographic graphics, clearly distinguish road segments with different traffic conditions, facilitate personnel to quickly grasp the overall traffic flow distribution, effectively improve the efficiency of traffic operation analysis, and provide intuitive and reliable visual decision-making basis for traffic planning, congestion management and road network optimization. In this embodiment, ArcMap is used to optimize the existing road network by combining length parameters and filtering conditions. Road segments are rationally divided and invalid vertical lines are removed, reducing data volume, computational pressure, and improving the efficiency of subsequent data analysis, thus creating a structurally sound and optimized city and county road network. The principle of straight line intersection is used to establish line matching relationships, and spatial connection tools are used to achieve Dpop traffic aggregation and accumulation, effectively avoiding line matching errors and ensuring that traffic statistics accurately reflect actual traffic conditions, efficiently completing the construction of the traffic flow road network. Finally, a geographic information system is used for visualization rendering, presenting traffic flow conditions in a hierarchical display manner, and equipping various standard mapping elements to transform complex traffic data into intuitive thematic maps. This facilitates staff in quickly assessing road network traffic trends and provides data support and intuitive decision-making references for city and county traffic management, road network planning, and travel control.

[0020] Please see Figure 4 The fourth embodiment of a city and county traffic data analysis method in this invention specifically includes: 401. Based on the ArcMap tool, the existing road network is broken down to obtain multiple road segments between nodes; In this embodiment, ArcMap, a professional geographic information processing tool, is used to perform node splitting on the overall connected road network. The natural intersection nodes and road forking nodes of the road network are used as the splitting boundaries to segment and break the continuous and complete road network lines. The long-distance connected road network is uniformly decomposed into independent line units with each pair of nodes corresponding to each other. Then, the regular connection layout is completed according to the actual road direction. This breaks the limitations of the original overall road network that is not segmented and has no independent units. The independent road segments between each pair of road nodes are divided, realizing the fine segmentation of the entire road network. This lays the foundation for the segmented road network for subsequent location of the center position of road segments and batch generation of corresponding perpendicular bisectors, ensuring that each road segment can independently complete the subsequent geometric calculation processing. 402. Perform midpoint coordinate analysis on road segments between multiple nodes to obtain multiple midpoint coordinates; In this embodiment, for each independent road segment after splitting, the spatial coordinates of the two ends of the road segment are extracted based on the GIS geometric coordinate calculation principle. The center point of a single road segment is obtained by solving the coordinate mean calculation formula. The midpoint coordinates of all road segments are calculated and collected in batches in sequence, and then summarized to form multiple standard midpoint coordinates corresponding to the entire road network. The spatial point of the geometric center of each road segment is clarified, which provides the center reference point for the subsequent standardized drawing of the perpendicular bisector, ensuring that the generated position of the perpendicular bisector conforms to the actual geometric shape of the road. 403. Generate multiple perpendicular bisectors based on the length parameter and the coordinates of multiple midpoints; In this embodiment, the coordinates of the midpoint of the road segment obtained by measurement are used as the reference point. The extension span and extension range of the perpendicular bisector are determined by combining the pre-set length parameters. The line segment is extended and drawn simultaneously to both sides of the road, perpendicular to the direction of the road segment between the corresponding nodes. According to the unified generation rules, a unique perpendicular bisector is generated for each road segment of the road network. The perpendicular bisector layout of all segments of the entire road network is completed in batches, and a spatial geometric layout structure in which the road network and the perpendicular bisector correspond to each other is constructed. The auxiliary geometric line system required for traffic space matching is built. 404. Filter all perpendicular lines according to the filtering conditions to obtain a set of perpendicular lines; In this embodiment, the preset filtering conditions are mainly based on the actual length of the line segment. Short and redundant perpendicular bisectors generated in areas such as road intersections and road turns are uniformly screened and removed. Invalid short perpendicular bisectors that have no actual matching effect or whose length does not meet the standard are removed. Only valid perpendicular bisectors that meet the standard length and have spatial matching value are retained. The overall geometric calculation data volume is reduced, invalid lines are reduced to participate in subsequent calculation processes, the overall system calculation load is reduced, and the overall calculation efficiency of subsequent spatial intersection determination and flow summarization is improved. 405. Generate an optimized city and county road network based on the set of perpendicular lines and road segments between multiple nodes; In this embodiment, the set of effective perpendicular lines after screening is spatially fused and matched with the segmented road segments between nodes. The road segments between nodes are used as the main framework of the road network, and the compliant and effective perpendicular lines are used as spatially related auxiliary lines. The overall integration and layout are completed according to the actual distribution pattern of the roads, the spatial correspondence between the main lines of the road network and the auxiliary perpendicular lines is straightened out, redundant geometric elements are eliminated, and an optimized city and county road network with a simplified structure, reasonable layout and stronger computational adaptability is formed, thus completing the simplification and optimization of the road network structure and the standardization of the geometric system. In this embodiment, ArcMap is used to decompose the road network nodes, dividing the overall existing road network into independent road segments between nodes, realizing the unitization of the road network and providing a regular basis for geometric calculation. The coordinates of the midpoint of each road segment are obtained by the coordinate mean algorithm. The perpendicular bisector is generated based on the midpoint and the preset length parameters, ensuring that the auxiliary lines are laid out in a regular and uniform manner. Invalid short perpendicular lines at intersections and turns are removed by length filtering rules, which simplifies the amount of computational data, effectively reduces the data processing pressure, and improves the efficiency of spatial matching and traffic flow calculation. Finally, the effective perpendicular bisector and the segmented road network are integrated to construct an optimized city and county road network, straightening out the spatial correspondence and making the road network structure more in line with the computational needs. This entire processing flow is standardized and logical, ensuring that the position of the perpendicular bisector is compliant, improving the computational accuracy and smoothness of subsequent spatial intersection analysis and traffic flow collection statistics, and providing high-quality geometric data support for city and county traffic flow analysis.

[0021] Please see Figure 5The fifth embodiment of a city and county traffic data analysis method in this invention specifically includes: 501. Based on the mathematical principle of straight line intersection, spatial intersection analysis is performed on the existing road network and the optimized city and county road network to obtain the intersection point analysis results; In this embodiment, the mathematical principle of straight line intersection is implemented based on the operational logic of planar line segment position determination. A linear operational relationship is established based on the coordinates of the endpoints of the line segments. By solving the equations of the two line segments simultaneously, it is determined whether two line segments intersect, thereby completing the spatial position relationship determination. This step is mainly used to determine whether there is an intersection relationship between the vertical lines laid out in the current road network and the optimized city and county road network. Standardized mathematical operations are used to complete the pairwise position verification of the entire road network, screen out the paths and road network segments with spatial correlation, and output the intersection analysis results including the intersection position, the associated line number, and the matching correspondence. This defines a clear correspondence for the subsequent traffic collection and matching, and ensures that the road network matching process is rigorous and orderly from the operational logic level, avoiding problems such as line mismatch and missed matching. 502. Traffic flow characteristics are extracted from the current road network based on the intersection analysis results; In this embodiment, based on the established intersection matching relationship of the routes, the intersection analysis results are used as the screening criteria to lock each existing road network segment that generates an intersection relationship. Simultaneously, the traffic flow identification information of all travel paths corresponding to the road segment is retrieved. From this, standardized Dpop traffic flow values, travel time attributes, travel mode attributes, and other traffic flow characteristics are uniformly extracted. This completes the binding and sorting of traffic flow data with the physical road network segments, classifies and integrates the scattered traffic flow information in various travel paths, clarifies the traffic flow source and basic traffic flow value corresponding to a single road segment, and provides a complete and effective feature data source for subsequent batch traffic aggregation and collection. 503. Based on spatial connectivity tools and traffic flow characteristics, optimize the configuration of city and county road networks to obtain traffic flow road networks; In this embodiment, ArcMap's built-in professional spatial connection tool is used as the data collection carrier. According to the established intersection matching correspondence, the extracted traffic flow features and corresponding Dpop traffic values ​​are uniformly collected and assigned to the corresponding road segments of the optimized city and county road network that intersect and match with them. Iterative calculations are completed by traversing each route and accumulating each matching group. The traffic flow data of all related paths are continuously summarized and superimposed onto the corresponding existing road network segments until the matching and assignment of all travel routes and road network segments in the entire region are completed. Finally, each physical road network segment carries the corresponding cumulative traffic flow and various traffic business attributes, and a standardized traffic flow road network with complete traffic flow attributes and business classification attributes is fully generated, completing the data upgrade from an empty road network to a weighted traffic flow road network. In this embodiment, the problems of matching traffic flow with the road network and efficiently aggregating it are effectively solved by using the mathematical principle of line intersection, traffic flow feature extraction, and spatial connection configuration. Based on line intersection operations, the spatial relationship between the vertical lines in the current road network and the optimized city and county road network is determined, and standardized intersection analysis results are output, avoiding potential route mismatches and omissions, thus laying a rigorous logical foundation for traffic aggregation. Features such as Dpop traffic and travel time periods are extracted through the intersection analysis results, enabling the classification and integration of scattered traffic data and ensuring the integrity and effectiveness of the traffic data source. Iterative assignment and traffic accumulation are completed using ArcMap spatial connection tools, realizing the allocation of traffic flow from the entire travel path to the physical road network, generating a standardized traffic flow road network with complete attributes, and upgrading the empty road network to a weighted road network. This improves the accuracy and efficiency of traffic statistics, providing reliable data support for subsequent traffic analysis and visualization rendering.

[0022] Please see Figure 6 The sixth embodiment of a city and county traffic data analysis method according to the present invention specifically includes: 601. Based on the preset time series traffic flow model, perform traffic flow network extrapolation and analysis to obtain traffic flow extrapolation characteristics; In this embodiment, the time-series traffic flow model is built upon the original LSTM (Long Short-Term Memory) time-series prediction model. This model fully utilizes three types of gating structures—input gate, forget gate, and output gate—along with cell state memory units to retain and update time-series information. It effectively preserves historical traffic flow time-series data features. Based on the pre-built time-series traffic flow model, it performs time-series extrapolation calculations on the traffic flow road network with completed traffic attribute assignments. Historical time-period road segment traffic flow, time-period travel characteristics, road grade, and road network carrying capacity data are uniformly input into the model. The gating structure is used to complete time-series feature selection and long-term travel pattern memory fitting. By combining traffic patterns, travel distribution patterns, and basic road network conditions at different times, this study deeply mines multiple traffic operation indicators such as road segment saturation, road congestion index, and actual road traffic efficiency. Based on the temporal variation patterns, it analyzes the dynamic change trend of road network traffic, the peak traffic aggregation pattern, and the characteristics of traffic distribution during off-peak hours. It extracts traffic flow temporal variation patterns, traffic fluctuation amplitude, and time-period traffic difference characteristics of the overall road network and individual road segments. This provides complete and time-series reference data for subsequent traffic flow classification and abnormal road segment identification. Based on the parsable model internal structure and temporal inference logic, it achieves in-depth mining and prediction of the dynamic evolution pattern of traffic flow. 602. Based on the traffic flow projection characteristics and the preset traffic flow classification analysis method, perform a classification analysis of the traffic flow road network to obtain the markings of ultra-high traffic flow sections, bottleneck sections, and abnormal change sections. In this embodiment, the traffic flow classification analysis method is a hierarchical comparison and judgment method based on road network carrying capacity threshold and time-series fluctuation characteristics. Its analysis principle is to use the road design capacity and the rated carrying capacity of different levels of road networks as basic benchmark values, and to establish a multi-level quantitative judgment system by combining the traffic flow change amplitude and time-period traffic flow difference obtained from time-series projections. Simultaneously, it conducts joint verification of multiple operating parameters such as road segment saturation, congestion index, and actual traffic efficiency to achieve a comprehensive identification combining qualitative and quantitative methods. Based on the extracted traffic flow projection characteristics, and combined with pre-set traffic flow classification judgment standards and traffic flow classification analysis methods, the overall traffic flow is analyzed. The road network underwent hierarchical classification and anomaly identification. By comparing different traffic flow range thresholds, the traffic flow levels of road segments were classified, and road segments with extremely high traffic flow exceeding the normal carrying capacity were screened out. Bottleneck road segments with insufficient traffic capacity that are prone to causing traffic congestion were identified. At the same time, by comparing the time-series traffic flow fluctuation difference, abnormal road segments with short-term sharp increases or cliff-like drops in traffic flow were quickly identified. The corresponding types of road segments were marked in turn, clearly distinguishing between normal traffic segments, high-load traffic segments, and abnormal traffic segments. The specific spatial location and degree of traffic abnormality of each type of problem road segment were clarified, providing a classification and labeling basis for subsequent differentiated visualization rendering. 603. Based on geographic information systems, ultra-high traffic flow segment markers, bottleneck segment markers, and abnormal change segment markers, the traffic flow network is rendered to obtain a visualized traffic flow network; In this embodiment, a geographic information system (GIS) is used to complete the entire process of visualization rendering. Based on the business attribute data such as road network traffic flow, travel modes, and road function categories that have been assigned values ​​to the traffic flow road network, a variety of visualization methods built into the GIS, such as hierarchical color rendering and hierarchical scale symbol rendering, are used. Different display styles are set for road segments with different marking types to intuitively distinguish the operating status of various road segments. At the same time, the corresponding legends for traffic flow classification are configured according to standard mapping specifications, and a map north arrow and standard scale lines are added simultaneously to improve the basic elements of thematic mapping. Finally, a standardized road network traffic flow analysis map result with a neat layout, clear hierarchy, and intuitive understanding is generated. It can not only intuitively show the overall situation of traffic flow distribution in the entire road network, but also locate various road segments with traffic problems, improving the intuitive display effect and ease of use of traffic flow data. In this embodiment, a time-series traffic flow model is used to extrapolate road network traffic flow, comprehensively acquiring operational indicators such as road segment saturation, congestion index, and traffic efficiency, and grasping the dynamic characteristics of traffic flow changes. Combined with standardized traffic flow classification analysis, various special road segments are marked, achieving refined differentiation of road network traffic conditions. Furthermore, relying on a geographic information system, professional rendering methods such as hierarchical color and scale are used to complete road network visualization. Thematic map production is improved by combining legends, north arrows, and scale lines, transforming abstract traffic flow data into intuitive and visual thematic maps that clearly present different road traffic conditions. This facilitates staff in quickly assessing road network traffic pressure, identifying potential traffic congestion hazards, and effectively improving the efficiency of traffic operation analysis in cities and counties.

[0023] Please see Figure 7 The seventh embodiment of a city and county traffic data analysis method according to the present invention specifically includes: 701. Based on a preset coordinate transformation algorithm and a preset geodetic coordinate system, perform coordinate transformation on the traffic data coordinate set to obtain a correction coordinate set; In this embodiment, the traffic data coordinate set originates from the raw path coordinates returned by the Gaode Maps route planning interface. The raw coordinates default to the Mars coordinate system (GCJ-02), which is inconsistent with the city and county land spatial data, planning results, and statutory surveying benchmarks. Direct use of this system would lead to spatial offsets in the road network, misalignment with the existing road network, and insufficient spatial matching, failing to meet the benchmark unification requirements for city and county traffic analysis and planning applications. Therefore, a systematic spatial coordinate correction process needs to be performed on the traffic data coordinate set based on a preset coordinate transformation algorithm and the preset National Geodetic Coordinate System 2000 (CGCS2000). The principle of the method is as follows: Based on the differences in ellipsoidal and projection parameters between the Mars coordinate system (GCJ-02) and the National Geodetic Coordinate System 2000 (CGCS2000), the encryption offset of the Mars coordinate system is eliminated through coordinate forward and inverse operations. The original discrete coordinate points are substituted one by one into the coordinate transformation formula to complete the conversion of latitude and longitude coordinates, realize the correction of the spatial position of road network elements, and obtain a set of corrected coordinates with unified spatial benchmark and compliant position. This provides a spatial data foundation that conforms to the statutory surveying and mapping standards for subsequent road network construction, topology processing, spatial matching and traffic correlation, and ensures the consistency between the city and county road network analysis results and the national land spatial data benchmark. 702. Based on the polyline geometry, organize and construct the correction coordinate set to obtain the current road network; In this embodiment, the correction coordinate set is a discrete and ordered sequence of latitude and longitude points. It does not possess the linear geometric features that GIS can recognize and cannot directly participate in road network topology construction, spatial intersection, and traffic flow analysis. It needs to be standardized and constructed based on the GIS polyline geometric structure. The polyline geometric object consists of attributes such as paths, spatial reference identifiers (wkid), and attribute fields. During the construction process, the correction coordinate set is encapsulated in the Paths attribute as an ordered array. Spatial reference information matching the National Geodetic Coordinate System 2000 is configured simultaneously to complete the structured transformation of discrete coordinate points into continuous polyline elements. Through sequential splicing of coordinate sequences, encapsulation of geometric objects, and binding of spatial references, road network line elements in GIS standard format are generated, forming a preliminary existing road network. This realizes the transformation from discrete coordinates to continuous road network geometric entities, providing a compliant linear spatial data carrier for subsequent topology adjustments, road network optimization, and traffic flow correlation analysis. 703. Perform topology adjustments on the existing road network according to the topology adjustment method and preset topology adjustment conditions to obtain a reorganized existing road network; In this embodiment, the topology adjustment method is a road network vector topology regularization and correction method implemented based on a GIS platform, which can complete road network defect identification, geometric correction, and connectivity reconstruction. The topology adjustment conditions are pre-set vector compliance constraint standards such as road network connectivity, no overlap, no gaps, and no hanging nodes. Based on the preset topology adjustment method and topology adjustment conditions, systematic topology correction processing is carried out on the existing road network. The topology adjustment steps include: 1) Topology defect detection, traversing road network line elements to identify abnormal topology features such as line segment overlap, unconnected endpoints, gaps at intersections, and hanging endpoints; 2) GIS topology editing and correction, through line segments... Operations such as merging, endpoint snapping, gap closure, duplicate segment deletion, and dangling node trimming eliminate various topological defects; 3) Topological compliance verification verifies the connectivity, non-overlapping, seamless, and dangling node status of road network elements to ensure the integrity, continuity, and consistency of the road network topology; through full-process topological adjustment, geometric generation errors and splicing defects are reduced to obtain a compliant topological structure, standardized geometric shape, and complete connectivity of the current road network, ensuring the accuracy, stability, and reliability of subsequent road network splitting, perpendicular bisector generation, spatial intersection analysis, and traffic aggregation calculation, laying a high-quality road network data foundation for the visualization analysis of traffic in city and county road networks; In this embodiment, the Gaode Mars Coordinate System (GCJ-02) is converted to the National Geodetic Coordinate System 2000 (CGCS2000) using a preset coordinate transformation algorithm. This solves problems such as road network location offset and misalignment, ensuring that the road network data is consistent with the basic data of municipal and county land space and the benchmark of planning results, and conforms to the statutory surveying and mapping standards, providing spatial data support for subsequent analysis. Secondly, relying on the polyline geometric structure, a correction coordinate set is organized to transform discrete coordinate points into continuous road network line elements that can be identified by GIS, constructing a preliminary existing road network. This effectively solves the problem that discrete coordinates cannot be directly used in topology construction and traffic flow analysis, realizing the transformation of discrete data into standardized geometric entities. The resulting standardized existing road network structure after topology adjustment conforms to the actual road layout in terms of spatial logic, avoiding problems such as spatial matching deviation and traffic flow statistics distortion caused by road network topology disorder. This improves the operational stability of subsequent road segment splitting, perpendicular bisector construction, spatial intersection calculation, and traffic flow aggregation and accounting, consolidating the data foundation for road network traffic data analysis and enhancing the practical value of municipal and county traffic road network data analysis results.

[0024] The above describes a method for analyzing urban and county traffic data in an embodiment of the present invention. The following describes a device for analyzing urban and county traffic data in an embodiment of the present invention. Please refer to [link / reference]. Figure 8 One embodiment of the city and county traffic data analysis device of the present invention includes: Data acquisition module 1 is used to collect basic traffic data according to the preset target city / county and specified time period. Feature extraction module 2 is used to extract features from traffic basic data according to a preset spatial feature extraction method to obtain a traffic data coordinate set; Topology analysis module 3 is used to perform topology analysis on traffic data coordinate sets based on preset polyline geometry and preset topology adjustment methods to obtain the current road network. The optimization processing module 4 is used to optimize the existing road network based on the preset Arcmap tool, the preset mathematical principle of line intersection, and the preset geographic information system to obtain a visualized traffic road network. In this embodiment, basic traffic data is collected based on the specified time period of the target city / county using the Gaode Map interface. This method is efficient, timely, and reduces labor costs, providing raw regional travel data. Spatial feature extraction methods are used to extract features from the basic traffic data to obtain a traffic data coordinate set, simplifying subsequent data processing. Then, polyline geometry and topology adjustment techniques are employed to regulate the road network morphology, correct topological defects, and streamline road network connectivity, improving the standardization of road network data. ArcMap is used in conjunction with the mathematical principle of line intersection to complete road network optimization and traffic flow matching. Finally, a geographic information system (GIS) is used to visualize the traffic flow data, providing a clear view of the overall traffic status and offering comprehensive and intuitive data and visualization support for city / county traffic planning, congestion management, road network optimization, and traffic management decisions.

[0025] Figure 9 This is a schematic diagram of the structure of a city / county traffic data analysis device 900 provided in an embodiment of the present invention. This city / county traffic data analysis device 900 can vary significantly due to different configurations or performance. It may include one or more central processing units (CPUs) 910 (e.g., one or more processors) and a memory 920, and one or more storage media 930 (e.g., one or more mass storage devices) for storing application programs 933 or data 932. The memory 920 and storage media 930 can be temporary or persistent storage. The program stored in the storage media 930 may include one or more modules (not shown in the diagram), each module may include a series of instruction operations on the city / county traffic data analysis device 900. Furthermore, the processor 910 may be configured to communicate with the storage media 930 and execute a series of instruction operations in the storage media 930 on the city / county traffic data analysis device 900 to implement the steps of the city / county traffic data analysis method provided in the above-described method embodiments.

[0026] A city / county traffic data analysis device 900 may further include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input / output interfaces 960, and / or one or more operating systems 931, such as Windows Server, MacOSX, Unix, Linux, FreeBSD, etc. Those skilled in the art will understand that... Figure 9 The illustrated structure of a city and county traffic data analysis device does not constitute a limitation on a city and county traffic data analysis device. It may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0027] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of a city and county traffic data analysis method.

[0028] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system, device, or unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0029] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0030] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for analyzing traffic data in cities and counties, characterized in that, include: Basic traffic data was collected based on the pre-defined target cities and counties and the specified time periods. Based on the preset spatial feature extraction method, feature extraction is performed on the basic traffic data to obtain the traffic data coordinate set; Based on a preset polyline geometry and a preset topology adjustment method, a topology analysis is performed on the traffic data coordinate set to obtain a revised current road network. Based on the preset ArcMap tool, the preset mathematical principle of line intersection, and the preset geographic information system, the existing road network is optimized to obtain a visualized traffic road network.

2. The method for analyzing urban and county traffic data as described in claim 1, characterized in that, The step of extracting features from traffic baseline data according to a preset spatial feature extraction method to obtain a traffic data coordinate set includes: The traffic baseline data is verified based on the preset spatial verification range and the preset outlier verification method to obtain basic and valid results. The basic valid results are assigned values ​​according to the preset Dpop field to obtain basic traffic information; Based on spatial feature extraction methods, features are extracted from basic traffic information to obtain a traffic data coordinate set.

3. The method for analyzing urban and county traffic data as described in claim 1, characterized in that, The optimization of the existing road network based on the preset ArcMap tool, the preset mathematical principle of line intersection, and the preset geographic information system to obtain a visualized traffic road network includes: The existing road network is optimized using ArcMap tools, preset length parameters, and preset filtering conditions to obtain an optimized city and county road network. Based on the mathematical principle of straight line intersection and the preset spatial connection tool, the configuration of the city and county road network is optimized to obtain the traffic flow road network; The traffic flow network is rendered using a geographic information system to obtain a visualized traffic flow network.

4. The method for analyzing urban and county traffic data as described in claim 3, characterized in that, The optimization process, based on ArcMap tools, preset length parameters, and preset filtering conditions, optimizes the existing road network to obtain an optimized city and county road network, including: The existing road network is broken down using ArcMap to obtain multiple road segments between nodes; Midpoint coordinate analysis is performed on road segments between multiple nodes to obtain multiple midpoint coordinates; Generate multiple perpendicular bisectors based on the length parameter and the coordinates of multiple midpoints; All perpendicular lines are filtered according to the filtering conditions to obtain a set of perpendicular lines; Optimize the city and county road network based on the set of vertical lines and the road segments between multiple nodes.

5. The method for analyzing urban and county traffic data as described in claim 3, characterized in that, The configuration of the optimized city and county road network based on the mathematical principle of straight line intersection and a preset spatial connection tool to obtain the traffic flow road network includes: Based on the mathematical principle of straight line intersection, spatial intersection analysis is performed on the existing road network and the optimized city and county road network to obtain the intersection point analysis results; Traffic flow characteristics are extracted from the current road network based on the intersection analysis results. The configuration of city and county road networks is optimized based on spatial connectivity tools and traffic flow characteristics to obtain a traffic flow road network.

6. The method for analyzing urban and county traffic data as described in claim 3, characterized in that, The rendering process of the traffic flow road network based on the geographic information system to obtain a visualized traffic flow road network includes: Traffic flow network is extrapolated and analyzed based on a pre-set time series traffic flow model to obtain traffic flow extrapolation characteristics; Based on the traffic flow projection characteristics and the preset traffic flow classification analysis method, the traffic flow road network is classified and analyzed to obtain the markings of ultra-high traffic flow sections, bottleneck sections, and abnormal change sections. The traffic flow network is rendered based on geographic information systems, ultra-high traffic flow segment markers, bottleneck segment markers, and abnormal change segment markers to obtain a visualized traffic flow network.

7. The method for analyzing urban and county traffic data as described in claim 1, characterized in that, The method of performing topological analysis on the traffic data coordinate set based on a preset polyline geometry and a preset topology adjustment method to obtain a revised existing road network includes: Based on a preset coordinate transformation algorithm and a preset geodetic coordinate system, the coordinate set of traffic data is transformed to obtain a correction coordinate set; The coordinate set for correction is organized and constructed based on the polyline geometry to obtain the current road network; The existing road network is adjusted according to the topology adjustment method and the preset topology adjustment conditions to obtain a sorted existing road network.

8. A city and county traffic data analysis device, characterized in that, include: The data acquisition module is used to collect basic traffic data according to the preset target cities and counties and the specified time period. The feature extraction module is used to extract features from traffic baseline data according to a preset spatial feature extraction method to obtain a traffic data coordinate set; The topology analysis module is used to perform topology analysis on traffic data coordinate sets based on preset polyline geometry and preset topology adjustment methods to obtain a revised current road network. The optimization module is used to optimize the existing road network based on the preset ArcMap tool, the preset mathematical principle of line intersection, and the preset geographic information system to obtain a visualized traffic road network.

9. A city and county traffic data analysis device, characterized in that, include: A memory and at least one processor, wherein the memory stores instructions; At least one of the processors invokes the instructions in the memory to cause the municipal and county traffic data analysis device to perform the various steps of the municipal and county traffic data analysis method as described in any one of claims 1-7.

10. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement the various steps of the city and county traffic data analysis method as described in any one of claims 1-7.

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