Road traffic hierarchical early warning method based on dynamic traffic information

Abstract

The invention belongs to the technical field of urban traffic big data mining, and specifically relates to a road traffic hierarchical early warning method based on dynamic traffic information. The method comprises the following steps: acquiring a road average speed; fusing the road average speed; numbering, sequencing and storing the fused road average speed according to a timestamp of a sampling cycle; forecasting a road average speed of next sampling cycle based on a time sequence; and acquiring a road traffic congestion index of next sampling cycle. By adopting the traffic operation hierarchical early warning method for traffic early warning analysis, users can conveniently select and timely change a more appropriate travel route, and traffic managers simultaneously can carry out some traffic regularity studies on meso and macro levels via relevant information to formulate some specific policies. The method is compact in calculation, strong in objectiveness, flexible in calculation, wide in application and high in accuracy of traffic state judgment.

Description

technical field [0001] The invention belongs to the technical field of urban traffic big data mining, and in particular relates to a road traffic classification early warning method based on dynamic traffic information. Background technique [0002] With the continuous development of the city, the contradiction of urban traffic is mainly manifested in the fact that the urban traffic supply cannot meet the growing traffic demand, the problem of traffic congestion on urban roads is becoming more and more serious, and even gradually becomes a global social problem that restricts the harmonious development of cities . Urban arterial roads are the arteries of urban traffic. Timely and accurate prediction and identification of traffic congestion on urban arterial roads in advance, and targeted measures such as traffic control and guidance for congested points can alleviate traffic bottlenecks on arterial roads and reduce traffic congestion. Negative effects of congestion. As far...

AI Technical Summary

Problems solved by technology

As far as the current domestic and foreign environments are concerned, the research on traffic congestion prediction is more at the theoretical level, and less technology is used in the actual engineering application process. Judging urban road traffic congestion, there are many shortcomings such as low early warning efficiency, poor accuracy and even no early warning

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