Total factor index-based traffic data analysis system
By introducing full-factor indicators and multi-module collaborative working methods in the traffic data analysis system, the problem of insufficient data processing standards and data fusion efficiency in the existing system is solved, and more accurate and real-time traffic data analysis is achieved, improving traffic operation efficiency and safety level.
Patent Information
- Application Number
- CN202510021295.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-07
- Publication Date
- 2025-05-06
AI Technical Summary
The existing traffic data analysis system lacks unified data processing standards and efficient data fusion technology, resulting in insufficient accurate and real-time data analysis results.
A traffic data analysis system based on all-factor indicators is proposed, including data acquisition, preprocessing, storage, fusion, analysis, decision support, visualization and security management modules, and comprehensively manage and efficiently utilize traffic data through data mining and machine learning algorithms.
The comprehensive management and efficient use of traffic data has been achieved, the efficiency of traffic operation has been improved, the level of traffic safety has been improved, and the construction of smart cities has been promoted.
Smart Images
Figure CN119942785A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of traffic data analysis systems, and in particular to a traffic data analysis system based on all-factor indicators. Background Art
[0002] Traffic data refers to data related to traffic flow, traffic facilities and traffic participants, including but not limited to: Traffic flow data: including vehicle quantity, speed, and direction information.
[0003] Traffic facility data: including the status and maintenance records of roads, bridges, and traffic signal facilities.
[0004] Traffic participant data: includes information about vehicles, public transportation, and pedestrian participants.
[0005] These data come from various sources, such as sensors, cameras, GPS devices, and traffic lights, and constitute the cornerstone of urban traffic big data.
[0006] Although the existing traffic data analysis system has achieved certain results, it still lacks unified data processing standards and efficient data fusion technology, resulting in inaccurate and in-real-time data analysis results.
[0007] In order to solve the above problems, this application proposes a traffic data analysis system based on all-factor indicators. Summary of the invention
[0008] 1. Purpose of the invention In order to solve the technical problems existing in the background technology, the present invention proposes a traffic data analysis system based on all-factor indicators, which has the advantages of improving traffic operation efficiency, enhancing traffic safety level and promoting smart city construction.
[0009] (II) Technical solution To solve the above problems, the present invention provides a traffic data analysis system based on all-factor indicators, comprising: Data collection module, used to collect real-time traffic data through sensor networks, cameras, and GPS devices; Data preprocessing module, used to clean, convert, and normalize data; The data collection module is connected to a data storage module, and the data storage module is used to directly transmit the collected real-time traffic data to the data storage module for storage; The data acquisition module is connected to a data preprocessing module, which is used to reduce the pressure of the data storage module or realize real-time data processing; The data preprocessing module is connected to the data storage module, and the preprocessed data needs to be stored in the data storage module; The data preprocessing module is connected to the data fusion module for preprocessing data from different sources; The data storage module is connected to a data fusion module for fusing and generating comprehensive traffic information; the data in the storage module is the basis of data fusion, and the fusion algorithm needs to access this data to generate comprehensive traffic information; The data storage module is connected to the data analysis module, and the analysis module needs to read data from the storage module; The data storage module is connected to a decision support module and a data visualization module, and the decision support module and the data visualization module are used to obtain data from the storage module to generate decision suggestions and visualization charts; The data fusion module is connected with the data analysis module to provide traffic information with the fused data; The data analysis module is connected to the decision support module and is used to use the output results as part of the input of the decision support module; The data visualization module is connected to the data storage module and is used to obtain data from the storage module or the analysis module to generate charts and graphs; Data security management module is used for security during data collection, storage, processing and application.
[0010] Preferably, the data acquisition module includes: Sensor network units, including geomagnetic induction sensors, microwave radar sensors and video image sensors, are used to collect data on the number, speed and type of vehicles on a road section or intersection in real time; GPS device unit, used for GPS receiver to obtain vehicle location information; Camera unit, used for high-definition camera to capture traffic dynamics on the road; Data access unit ensures the real-time and integrity of data.
[0011] Preferably, the data preprocessing module includes: Data cleaning unit, used to remove duplication, denoise, and fill missing values from the collected data to ensure data accuracy and consistency; Data conversion unit, used to convert data in different formats and from different sources into a unified format and standard; The data normalization unit is used to normalize the data and eliminate the influence of different dimensions on the data.
[0012] Preferably, the data storage module includes: Database management unit, which enables reliable storage and fast access to massive data; The data backup and recovery unit is used to back up data regularly and quickly restore data when it is lost or damaged.
[0013] Preferably, the data fusion module includes: Data integration unit, used to integrate data from different sources and formats to form a unified traffic data set; Data association unit, used to associate different data through time and space dimensions to form more comprehensive traffic information; The data fusion algorithm unit is used to fuse data from different sources using a data fusion algorithm based on big data technology.
[0014] Preferably, the data analysis module includes: Data mining unit, used to mine valuable information and patterns from data; The machine learning unit uses machine learning algorithms to conduct traffic flow prediction and safety risk warning analysis; The data analysis report generation unit is used to generate a detailed analysis report based on the analysis results and provide data support for the decision support module.
[0015] Preferably, the decision support module includes: The decision algorithm unit generates optimization suggestions or strategies based on data analysis results using intelligent decision algorithms; A decision suggestion generation unit generates specific decision suggestions based on the output results of the decision algorithm; The decision-making effect evaluation unit evaluates the implementation effect of decision-making recommendations and provides a basis for subsequent decision optimization.
[0016] Preferably, the data visualization module includes: A chart generation unit is used to generate line charts, bar charts, and scatter charts based on data analysis results to intuitively display the changing trend and distribution of data; Interactive interface design unit, used for user-friendly interactive interface, enabling users to browse, query and analyze data conveniently; The visual report generation unit is used to integrate charts and interactive interfaces into visual reports to provide users with a comprehensive display of data analysis results.
[0017] Preferably, the data security management module includes: A data encryption unit, used for encrypting the stored and transmitted data; Access control unit, used to set user permissions and access control policies; Audit log recording unit, used to record user access to data and operation logs.
[0018] The above technical solution of the present invention has the following beneficial technical effects: Through data collection, preprocessing, storage, fusion, analysis, decision support, visualization and safety management modules, we can achieve comprehensive management and efficient use of traffic data. By using data mining and machine learning algorithms, we can mine valuable information from massive data and provide strong support for intelligent transportation. At the same time, through data visualization technology, we can show the analysis results to users in an intuitive way, helping users to better understand and analyze data and make scientific decisions. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] Figure 1 This is a structural schematic diagram of a traffic data analysis system based on all-factor indicators proposed by the present invention. DETAILED DESCRIPTION
[0020] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, the description of well-known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.
[0021] like Figure 1 As shown, the present invention proposes a traffic data analysis system based on all-factor indicators, including: Data collection module, used to collect real-time traffic data through sensor networks, cameras, and GPS devices; Use WebSocket and Kafka technologies to achieve efficient data access; Data preprocessing module, used to clean, convert, and normalize data; Data missing value processing and outlier processing.
[0022] The data acquisition module is connected to a data storage module, which is used to directly transmit the collected real-time traffic data to the data storage module for storage, so as to facilitate subsequent analysis and processing; The data acquisition module is connected to a data preprocessing module, which is used to reduce the pressure of the data storage module or realize real-time data processing. The collected data may be cleaned and converted by the data preprocessing module before being stored; The data preprocessing module is connected to the data storage module, and the preprocessed data needs to be stored in the data storage module for subsequent data analysis; The data preprocessing module is connected to the data fusion module, which may be used to preprocess the data from different sources before data fusion to ensure the consistency and comparability of the data; The data storage module is connected to a data fusion module for fusing and generating comprehensive traffic information; the data in the storage module is the basis of data fusion, and the fusion algorithm needs to access this data to generate comprehensive traffic information; The data storage module is connected to the data analysis module, and the analysis module needs to read data from the storage module to perform traffic flow prediction and safety risk warning analysis; The data storage module is connected to a decision support module and a data visualization module, and the decision support module and the data visualization module are used to obtain data from the storage module to generate decision suggestions and visualization charts; The data fusion module is connected with the data analysis module to provide more comprehensive traffic information for the fused data, which will be used for more in-depth analysis; The data analysis module is connected to the decision support module to use the output results (such as prediction model, risk score) as part of the input of the decision support module; The data visualization module is connected to the data storage module and is used to obtain data from the storage module or the analysis module to generate charts and graphs; The data security management module is used for security during data collection, storage, processing and application. This includes data encryption, access control, and audit log functions, which need to interact with each module in the system.
[0023] Preferably, the data acquisition module includes: Sensor network units, including geomagnetic induction sensors, microwave radar sensors and video image sensors, are used to collect data on the number, speed and type of vehicles on a road section or intersection in real time; GPS device unit, used for GPS receiver to obtain vehicle location information and upload it to the background system in combination with wireless communication network; Camera unit, which uses high-definition cameras to capture traffic dynamics on the road, including vehicle violations, traffic accidents, and pedestrian crossings; The data access unit uses WebSocket and Kafka technologies to achieve efficient data access and ensure the real-time and integrity of the data.
[0024] Preferably, the data preprocessing module includes: Data cleaning unit, used to remove duplication, denoise, and fill missing values from the collected data to ensure data accuracy and consistency; Data conversion unit, used to convert data of different formats and sources into a unified format and standard to facilitate subsequent processing and analysis; The data normalization unit is used to normalize the data, eliminate the impact of different dimensions on the data, and improve the accuracy and efficiency of data analysis.
[0025] Preferably, the data storage module includes: Database management unit, using high-performance database technologies, such as distributed databases and data warehouses, to achieve reliable storage and fast access to massive amounts of data; The data backup and recovery unit is used to regularly back up data to ensure data reliability and security. In case of data loss or damage, data can be quickly restored.
[0026] Preferably, the data fusion module includes: Data integration unit, used to integrate data from different sources and formats to form a unified traffic data set; Data association unit, used to associate different data through time and space dimensions to form more comprehensive traffic information; The data fusion algorithm unit is used to use the data fusion algorithm based on big data technology to fuse data from different sources and improve the accuracy and completeness of the data.
[0027] Preferably, the data analysis module includes: The data mining unit uses data mining technology to extract valuable information and patterns from massive data.
[0028] The machine learning unit uses machine learning algorithms, such as logistic regression models, support vector machines, and ARIMA models, to conduct traffic flow forecasting and safety risk warning analysis; The data analysis report generation unit is used to generate a detailed analysis report based on the analysis results and provide data support for the decision support module.
[0029] The traffic flow prediction algorithm is the ARIMA model: ; where ϕ(B) and θ(B) are regression parameters, d is the difference order, σ is the standard deviation of the white noise sequence, and ωt is the white noise sequence Preferably, the decision support module includes: The decision algorithm unit uses intelligent decision-making algorithms to generate optimization suggestions or strategies based on data analysis results.
[0030] The decision suggestion generation unit generates specific decision suggestions, such as traffic signal control optimization and public transportation scheduling optimization, based on the output results of the decision algorithm.
[0031] The decision-making effect evaluation unit evaluates the implementation effect of decision-making recommendations and provides a basis for subsequent decision optimization.
[0032] Preferably, the data visualization module includes: A chart generation unit is used to generate line charts, bar charts, and scatter charts based on data analysis results to intuitively display the changing trend and distribution of data; Interactive interface design unit, used for user-friendly interactive interface, enabling users to browse, query and analyze data conveniently; The visual report generation unit is used to integrate charts and interactive interfaces into visual reports to provide users with a comprehensive display of data analysis results.
[0033] Preferably, the data security management module includes: Data encryption unit, used to encrypt stored and transmitted data to ensure data confidentiality and security; Access control unit, used to set user permissions and access control policies to prevent unauthorized access and operation; The audit log recording unit is used to record user access and operation logs to data for easy tracking and auditing.
[0034] Security risk warning: Algorithm: Support Vector Machine ; in: N is the number of training samples, \alphan is the Lagrange multiplier, K(xn,x) is the kernel function, and b is the bias term.
[0035] In the present invention, comprehensive management and efficient use of traffic data are achieved through modules such as data collection, preprocessing, storage, fusion, analysis, decision support, visualization and safety management. By using algorithms such as data mining and machine learning, valuable information can be mined from massive data to provide strong support for intelligent transportation. At the same time, through data visualization technology, the analysis results are displayed to users in an intuitive way, helping users to better understand and analyze data and make scientific decisions.
[0036] It should be understood that the above specific embodiments of the present invention are only used to illustrate or explain the principles of the present invention, and do not constitute a limitation of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. In addition, the appended claims of the present invention are intended to cover all changes and modifications that fall within the scope and boundaries of the appended claims, or the equivalent forms of such scope and boundaries.
Claims
1. A traffic data analysis system based on all-factor indicators, characterized in that: include: Data collection module, used to collect real-time traffic data through sensor networks, cameras, and GPS devices; Data preprocessing module, used to clean, convert, and normalize data; The data collection module is connected to a data storage module, and the data storage module is used to directly transmit the collected real-time traffic data to the data storage module for storage; The data acquisition module is connected to a data preprocessing module, which is used to reduce the pressure of the data storage module or realize real-time data processing; The data preprocessing module is connected to the data storage module, and the preprocessed data needs to be stored in the data storage module; The data preprocessing module is connected to the data fusion module for preprocessing data from different sources; The data storage module is connected to a data fusion module for fusing and generating comprehensive traffic information; the data in the storage module is the basis of data fusion, and the fusion algorithm needs to access this data to generate comprehensive traffic information; The data storage module is connected to the data analysis module, and the analysis module needs to read data from the storage module; The data storage module is connected to a decision support module and a data visualization module, and the decision support module and the data visualization module are used to obtain data from the storage module to generate decision suggestions and visualization charts; The data fusion module is connected with the data analysis module to provide traffic information with the fused data; The data analysis module is connected to the decision support module and is used to use the output results as part of the input of the decision support module; The data visualization module is connected to the data storage module and is used to obtain data from the storage module or the analysis module to generate charts and graphs; Data security management module is used for security during data collection, storage, processing and application.
2. A traffic data analysis system based on all-factor indicators according to claim 1, characterized in that: The data acquisition module includes: Sensor network units, including geomagnetic induction sensors, microwave radar sensors and video image sensors, are used to collect data on the number, speed and type of vehicles on a road section or intersection in real time; GPS device unit, used for GPS receiver to obtain vehicle location information; Camera unit, used for high-definition camera to capture traffic dynamics on the road; Data access unit ensures the real-time and integrity of data.
3. A traffic data analysis system based on all-factor indicators according to claim 2, characterized in that: The data preprocessing module includes: Data cleaning unit, used to remove duplication, denoise, and fill missing values from the collected data to ensure data accuracy and consistency; Data conversion unit, used to convert data in different formats and from different sources into a unified format and standard; The data normalization unit is used to normalize the data and eliminate the influence of different dimensions on the data.
4. A traffic data analysis system based on all-factor indicators according to claim 3, characterized in that: The data storage module includes: Database management unit, which enables reliable storage and fast access to massive data; The data backup and recovery unit is used to back up data regularly and quickly restore data when it is lost or damaged.
5. A traffic data analysis system based on all-factor indicators according to claim 4, characterized in that: The data fusion module includes: Data integration unit, used to integrate data from different sources and formats to form a unified traffic data set; Data association unit, used to associate different data through time and space dimensions to form more comprehensive traffic information; The data fusion algorithm unit is used to fuse data from different sources using a data fusion algorithm based on big data technology.
6. A traffic data analysis system based on all-factor indicators according to claim 5, characterized in that: Data analysis modules include: Data mining unit, used to mine valuable information and patterns from data; The machine learning unit uses machine learning algorithms to conduct traffic flow prediction and safety risk warning analysis; The data analysis report generation unit is used to generate a detailed analysis report based on the analysis results and provide data support for the decision support module.
7. A traffic data analysis system based on all-factor indicators according to claim 6, characterized in that: The decision support modules include: The decision algorithm unit generates optimization suggestions or strategies based on data analysis results using intelligent decision algorithms; A decision suggestion generation unit generates specific decision suggestions based on the output results of the decision algorithm; The decision-making effect evaluation unit evaluates the implementation effect of decision-making recommendations and provides a basis for subsequent decision optimization.
8. A traffic data analysis system based on all-factor indicators according to claim 7, characterized in that: The data visualization module includes: A chart generation unit is used to generate line charts, bar charts, and scatter charts based on data analysis results to intuitively display the changing trend and distribution of data; Interactive interface design unit, used for user-friendly interactive interface, enabling users to browse, query and analyze data conveniently; The visual report generation unit is used to integrate charts and interactive interfaces into visual reports to provide users with a comprehensive display of data analysis results.
9. A traffic data analysis system based on all-factor indicators according to claim 8, characterized in that: The data security management module includes: A data encryption unit, used for encrypting the stored and transmitted data; Access control unit, used to set user permissions and access control policies; Audit log recording unit, used to record user access to data and operation logs.