Big data system for traffic management

Abstract

The invention provides a big data system for traffic management, including a data integration module, a data standardization and index code system building module, a data modeling module, a data organization module and a big data analysis and judgment module. The data integration module is used for integrating internal data and social data of traffic management, and has a reserved data access interface. The data standardization and index code system building module is used for building a data standardization and index code system, cleaning and filtering original data and describing the original data. The data modeling module is used for building a data model for vehicle behavior analysis. The data organization module is used for effectively organizing thematic data according to the business application scene. The big data analysis and judgment module is used for integrating traffic management data resources and realizing comprehensive data analysis and judgment. A unified traffic dataresource management center can be built to gather all kinds of traffic data, carry out data analysis, deep mining and collision analysis on big data and discover internal rules.

Description

technical field [0001] The present invention relates to the field of computers, in particular to a traffic management big data system, which builds a unified traffic data resource management center, gathers various traffic data from different sources, performs data analysis, deep mining, and collision analysis to discover internal laws. Background technique [0002] In recent years, all parts of the country have vigorously promoted the construction of traffic management technology informatization. Through the application of new technologies and information management, the intelligent level of urban traffic management has been effectively improved. However, there are some problems in the development and construction of intelligent information transportation at present. The specific problems are as follows: 1. The traffic data of various departments is scattered and there is a lack of information sharing. Traffic data is scattered in the hands of government departments and ent...

AI Technical Summary

Problems solved by technology

2. Data query statistical analysis function is lacking

The utilization rate of existing data, especially dynamic data is low, the compatibility of traffic information data between various departments is poor, and the real-time data acquisition ability of important indicators such as traffic accidents, violations, traffic hotspots, road water, icing, road network weather, etc. Low, affecting data query statistical analysis

3. Lack of data modeling for a certain topic direction, and generate an analysis report

Because there is no effective data cleaning, fusion, sharing and exchange, the collision ability of multi-dimensional data is weak, which cannot meet the needs of traffic managers to conduct portrait analysis of pedestrian-vehicle roads, analysis and judgment of human-vehicle behavior patterns, and illegal accident information. With multi-angle big data mining, it is impossible to generate a traffic management analysis report for a certain method of combat

4. Lack of practical applications based on big data

Due to the lack of data fusion analysis and decision support capabilities, there are no functions such as traffic quantitative analysis, fusion data analysis, and traffic management decision-making. The traffic operation analysis index system has not been established, and practical applications based on big data cannot be realized.