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 method for detecting the traffic state of an expressway section. The method includes the following steps: 1) extracting traffic parameters based on toll data; 2) constructing a prediction model of the average travel speed of expressways; 3) realizing the prediction of average travel speed during a time period; 4) extracting space occupancy characteristic parameters based on video data; The average space occupancy rate of the road section is obtained from the space occupancy rate of each section above. 6) Based on the predicted average travel speed and the occupancy rate of the road section, the traffic state is divided by clustering method. The invention solves the problem that the toll data is difficult to represent the traffic state in real time, and solves the problem of how to represent the road section traffic state with the cross-section information in combination with the section traffic flow information extracted from the video data. At the same time, the data is fused at the feature level, which reduces the false alarm rate of a single data source and realizes the purpose of real-time detection of road traffic conditions.

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 a highway section. Background technique [0002] In recent years, with the rapid development of the transportation industry, more and more vehicles are driving on the expressway, resulting in more serious road congestion on the expressway. [0003] Traffic status detection can provide decision-making and support for traffic management departments to conduct traffic control, the core content of intelligent transportation system 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, studying the theory and method of traffic state detection, and accurately and quickly detecting and discriminating the road traffic state from the obtained information is an urgent need for the development of the current...

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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