Traffic flow data sampling and analysis based on network limited moving object database

Abstract

The utility model provides a network constrained moving object database-based traffic flow data acquisition and analysis method; wherein, the time and space trace is acquired and stored by means of the technology of network restricted mobile object database, the acquired data is online counted in denomination of atomic driving section and by the technology of time and space statistics and analysis, then a plurality of traffic parameters of the traffic network are acquired on a real-time basis, and the temporal data of the traffic parameter changing is stored. The acquired data reflects the integral time and space trace of the mobile object, simplifies the complexity of the statistics and analysis, enhances the processing efficiency, and provides more sufficient information for data analysis and intensifies the precision of the data processing. Moreover, message delay is eliminated because the process of traffic parameter refreshing can be triggered by updating the positions of the mobile objects on a real-time basis. Compared with the prior traffic flow statistics and analysis method, the utility model has the advantages of high efficiency, high precision and real-time availability..

Description

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AI Technical Summary

Benefits of technology

This patented system allows for accurate tracking over an area without constantly sending out updated positioning information from each vehicle's sensor or base station device. It uses this tracked movement instead of continuously reporting its own current locations on topography maps that are used to calculate their route based upon these coordinates. By doing away with periodic updates, it reduces costs associated with collecting detailed map-based navigation data while still being able to locate objects within certain areas around them effectively.

Problems solved by technology

Technological Problem addressed in this patents relates to improving the efficiency and effectiveness of analyzing traffic flows for efficient management purposes while reducing costs associated therewith. Current methods require expensive infrastructure investments due to factors like heavy usage levels at roads, increased demand from mobile phone networks, and lack of accurate location tracking capabilities during peak hours. Additionally, current systems rely heavily upon GPS signals to gather raw data, leading to higher communication costs over longer periods.

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