A detection method for expressway congestion interval based on multi-source traffic data fusion

Abstract

The invention proposes a detection method for expressway congestion intervals based on multi-source traffic data fusion. The present invention performs data preprocessing on the identification data of the expressway path identification system, the flow data of the toll station of the networked toll collection system, and the GPS track data of two passengers and one critical vehicle, and performs multi-level road network on the expressway road network Division; use the preprocessed three types of traffic source data and the divided road network to match the data on the first-level road network, the second-level road network and the third-level road network; use the three-level matching Data, using the hierarchical congestion interval detection framework to calculate the traffic status of each basic section of the multi-level expressway. The invention makes the detection result of the congestion interval more reliable, can detect and obtain multi-level congestion interval distribution results, can reduce the amount of data calculation, and improve the detection speed.

Description

technical field [0001] The invention belongs to the technical field of multi-source traffic data mining, and relates to a detection method for expressway congestion intervals with multi-source traffic data fusion. Background technique [0002] With the development of my country's economy and urbanization, the connection between cities is becoming more and more close. As the lifeline between cities, the importance of expressways is self-evident. Due to many factors such as weather, road conditions and emergencies, there will also be traffic congestion problems in the expressway. In order to facilitate better supervision of the expressway, it is necessary to obtain traffic status information on the expressway, so it is necessary to use the available data to identify the traffic status on the expressway to obtain relevant information. At present, the research on expressway congestion events can be divided into two aspects: one is to define, simulate and analyze the influencing...

AI Technical Summary

Problems solved by technology

[0003] Most of the current methods use a single source of traffic data to detect expressway congestion. To detect highway congestion events, the advantages of integrating multi-source traffic data to make the detection results more reliable still need to be explored and explored

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