Urban road traffic identification method and system based on elastic coefficients

Abstract

The invention provides an urban road traffic identification method and system based on elastic coefficients. The method comprises the steps that a traffic flow parameter model is built, a traffic flow elastic coefficient threshold value is preset, the traffic flow states are divided according to the elastic coefficient threshold value, real-time identification or predication of the traffic states of a target road is achieved through comparison of the traffic flow information and the traffic flow parameter threshold value, and therefore the interactive relation between traffic state parameters can be described in an quantized mode, the dependency relation between the traffic state changes and the changes of the influence factors of the traffic state changes is weighed, the method can be suitable for different roads and traffic conditions, the identification result facilitates accurate and reasonable decision making by a traffic signal control system.

Description

technical field [0001] The invention relates to the technical field of traffic state identification, in particular to an urban road traffic identification method and system based on elastic coefficients. Background technique [0002] With the continuous development of urban traffic and the rapid increase of vehicles, the problem of traffic congestion has become increasingly prominent. For a long time, obtaining real-time and reliable dynamic traffic data has been a major bottleneck in the development of urban traffic in my country. However, with the emergence of various new traffic detection technologies, the accuracy, breadth and content of traffic data have also been continuously improved, and traffic management departments can already obtain a large amount of accurate real-time traffic data. In practical application, how to quickly and accurately identify the traffic state is not only related to whether the real traffic state can be recognized, but also whether the traffi...

AI Technical Summary

Problems solved by technology

[0003] At present, the identification methods of road traffic status are mainly divided into two categories: one is the service level classification and judgment method represented by the American HCM manual. This method has a relatively stable status classification standard, and its calculation process is relatively simple, but The judgment result does not consider the actual road and traffic conditions, and the adaptability is not strong; the other is the traffic state recognition method based on the measured traffic data and different research purposes. This method usually uses the traffic volume, speed, Take the occupancy rate as input variables, and then apply various analysis and calculation methods, such as fuzzy clustering, Kalman filter, etc., to obtain the characteristic values ​​of traffic flow in each traffic state, and then carry out traffic state identification

At present, this method is still in the research and experimental stage. Due to the complexity of the calculation process and the ambiguity of the state judgment, there are still many problems in the direct application of the traffic signal control system.

There is no quantitative explanation for the interactive relationship between traffic flow parameters and the transition of traffic state caused by parameter changes, especially the abnormal fluctuation of traffic state caused by the fluctuation of traffic flow parameters near the traffic state threshold, and there is no clear explanation. know

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