A traffic state detection method for expressway sections based on heterogeneous data

Abstract

The invention relates to the technical field of traffic monitoring, in particular to a traffic state detection method for expressway sections, comprising the following steps of 1) extracting the traffic parameters based on toll data; 2) constructing an average travel speed prediction model of that expressway; 3) realizing the prediction of the average travel speed of the time interval; 4) extracting spatial occupancy characteristic parameters base on that video data; 5) obtaining that average space occupancy rate of each section on the road section by using the space occupancy rate of each section; 6) dividing the traffic state by adopting a clustering method based on the predicted average travel speed and the space occupancy rate of the section. The method of the invention solves the problem that the charging data is difficult to express the traffic state in real time, and solves the problem that how to express the traffic state of the road section by the cross-section information combined with the cross-section traffic flow information extracted by the video data. At the same time, the data are fused at the feature level, which reduces the false alarm rate of a single data sourceand realizes the purpose of real-time detection of the traffic state of the road section.

Description

technical field [0001] The invention relates to the technical field of traffic monitoring, in particular to a method for detecting the traffic state of an expressway section. Background technique [0002] In recent years, with the rapid development of the transportation industry, there are more and more vehicles driving on the expressway, which leads to more and more serious road congestion on the expressway. [0003] Traffic status detection can provide decision-making and support for traffic management departments to carry out traffic control, the core content of intelligent transportation systems and an important basis for traffic information services, traffic control and guidance. At the same time, it can also provide effective route guidance services for travelers. Therefore, researching the theory and method of traffic status detection, and accurately and quickly detecting and distinguishing road traffic status from the obtained information is an urgent need for the d...

AI Technical Summary

Problems solved by technology

[0005] The existing technology mainly has the following shortcomings: the average travel speed and vehicle speed variance obtained based on toll data reflect the state of the off-road vehicle on the road, which has a time lag problem, and it is difficult to meet the needs of real-time identification of traffic conditions

The cross-sectional traffic status detected by cross-section detectors such as vehicle detectors and cameras is difficult to reflect the traffic status of road sections. At the same time, the occupancy rate of traffic parameters detected by cameras is a static feature. Once a large truck appears, the occupancy rate will become larger in a non-congested state. situation, resulting in false positives

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