Automatic Quantification Extraction Method of Traffic Congestion Propagation Features for Continuous Flow Traffic Facilities

Abstract

The invention relates to a method for automatically quantifying and extracting traffic congestion propagation features for continuous flow traffic facilities. The proposed method takes the route as the analysis object, first constructs the traffic spatio-temporal contour map according to the collected traffic flow state parameters, and uses k The ‑means algorithm clusters the average speed data of historical traffic flow, and automatically determines the threshold for dividing congested and non-congested traffic states according to the boundary speed of the cluster; then, uses the graph connectivity clustering algorithm to identify independent Then, according to the space-time range corresponding to each independent space-time congestion area, combined with the traffic flow state parameters in the space-time range, analyze and extract the traffic congestion propagation related parameters from the traffic time-space contour map. It realizes the rapid automatic identification and quantitative extraction of traffic congestion bottlenecks and traffic congestion propagation characteristics of continuous flow traffic facilities.

Description

technical field [0001] The invention relates to a method for analyzing and quantitatively extracting the spatio-temporal propagation characteristics of traffic jams occurring in continuous flow traffic facilities by means of computer automatic analysis techniques, specifically an automatic quantitative extraction method for traffic jam propagation characteristics oriented to continuous flow traffic facilities, which belongs to road Intelligent traffic monitoring and information management. Background technique [0002] Traffic congestion has brought a series of negative impacts to countries all over the world, such as significantly increasing economic losses and travel costs, leading to severe exhaust and noise pollution. An important prerequisite for alleviating and managing traffic congestion is the need for intelligent monitoring of traffic congestion on the road, rapid identification of road traffic congestion bottlenecks, and scientific quantification of traffic congest...

AI Technical Summary

Problems solved by technology

There are two main deficiencies in the method based on local analysis: one is that the traffic flow state parameter threshold method (such as speed difference threshold method, occupancy difference threshold method) is usually used when judging whether a road section has traffic congestion

However, the main disadvantage of this type of method is that it needs to rely on manual identification of traffic congestion bottlenecks and extraction of traffic congestion propagation characteristics from the traffic space-time contour map. The accuracy of congestion bottleneck identification and congestion propagation feature index extraction is not high, and the analysis efficiency is low. while increasing labor costs

In addition, some traffic congestion feature indicators, such as vehicle delays, cannot be directly extracted by human observation, which largely limits the universality and practicability of such methods

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