Estimation Method of Traffic State at Expressway Location Based on Feature Parameters Weighted GEFCM Algorithm

Abstract

The invention belongs to the technical field of a road traffic control system, and discloses an expressway site traffic state estimation method based on a feature parameter weighted GEFCM algorithm. The method comprises the following steps that (1) historical data of three feature parameters including the vehicle flow rate, the average vehicle speed and the average occupation rate are obtained through collection of an expressway microwave vehicle detector, and a sample matrix is formed; (2) the data obtained in the first step is subjected to preprocessing, and the preprocessing includes wrong data recognition and deletion, data restoration and data filtering processing; (3) the weight of the three kinds of feature parameters during clustering analysis is determined; (4) the historical data is subjected to clustering analysis; (5) when the traffic flow parameter of the current cross section is obtained, the traffic state is estimated in real time. The method has the advantages that the imbalance in the historical traffic data sample during the clustering is considered, and the difference of different traffic flow parameters on the clustering is considered, so that a provided feature parameter weighted GEFCM model has a better clustering effect, and further, a better effect and higher reliability are also realized on the traffic state estimation.

Description

technical field [0001] The invention belongs to the technical field of road traffic control systems, in particular to a method for estimating traffic states at expressway locations. Background technique [0002] With the increasing importance of expressway in my country's transportation, traffic congestion, traffic accidents, environmental pollution and other problems are becoming more and more serious. Whether it is traffic managers or travelers, the demand for traffic information management is gradually increasing. Therefore, how to use existing detection equipment to estimate the traffic status of expressways as effectively and accurately as possible, and grasp the current road conditions in real time and accurately. Traffic conditions are the premise of efficient management and service, and have important theoretical research and practical application significance. [0003] Various devices for traffic data acquisition, such as fixed detectors, video detectors, floating ...

AI Technical Summary

Problems solved by technology

Cluster analysis is mainly the analysis of historical sample data, so that the correlation between data under the same category attribute is large, and the data correlation between different categories is small. However, through the analysis of historical samples, it can be found that the spatial distribution of samples There is an imbalance, that is, there are differences in the sample size of different state categories, and the traditional FCM is sensitive to the number of samples when clustering, which will cause misjudgment when clustering this type of data

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