Traffic congestion prediction method and system based on traffic congestion propagation model

Abstract

The invention discloses a traffic congestion prediction method and system based on a traffic congestion propagation model. The method comprises: a historical track of a vehicle is obtained and a passing speed of the vehicle when passing through a first road section is calculated; according to the passing speed, a vehicle driving threshold is calculated; if an instantaneous driving speed of the current vehicle is lower than the vehicle driving threshold, traffic congestion is determined; and a road section with the monthly traffic congestion occurrence frequency larger than a predetermined frequency is determined to be a frequent traffic congestion section, a congestion sub graph is generated based on the frequent traffic congestion section, and the congestion sub graph is calibrated based on the probability of concurrence of traffic congestion of all connected sections and then a traffic congestion probability graph model is generated to predict a traffic congestion situation. Therefore, the accurate road traffic state can be extracted by using multi-source track big data, thereby completing the urban traffic congestion propagation analysis and discovering a traffic congestion source. Therefore, traffic congestion occurrence is reduced and the trip cost of the vehicle owner is saved.

Description

technical field [0001] The invention relates to the technical field of intelligent transportation, in particular to a traffic congestion prediction method and system based on a traffic congestion propagation model. Background technique [0002] At present, the number of motor vehicles in the city continues to increase, the traffic pressure increases sharply, and traffic congestion often occurs in some areas, which brings great challenges to the smooth operation of urban traffic and exacerbates energy and environmental problems related to transportation. Clarifying the source and transmission mechanism of traffic congestion can relieve traffic congestion and ensure the smooth flow of urban traffic. Traditional traffic congestion propagation analysis methods generally use the experience of traffic experts to analyze, extract and predict possible traffic congestion based on the structure of the road network. Due to the lack of a reliable traffic congestion propagation model, i...

AI Technical Summary

Problems solved by technology

[0004] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a traffic jam prediction method and system based on a traffic jam propagation model, aiming at solving the problem of traffic jam prediction in the prior art generally relying on people's subjective experience, traffic jam analysis The results are inaccurate, and it is only possible to implement congestion prediction analysis in a small area. The efficiency of traffic congestion prediction is low, the travel time of car owners increases, and the technical problems of high travel costs

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