Congestion degree prediction model, system and method for continuous traffic nodes based on queuing theory

Abstract

The present invention discloses a queuing theory-based continuous traffic node congestion degree prediction model, a system and a method. The model comprises a plurality of continuous traffic nodes. The length distribution of queues is adopted as an index for evaluating the traffic node congestion condition. The queue length distribution of each traffic node is constructed based on the queuing theory and the flow of the self-similarity. According to the invention, the method is directed to the prediction of the continuous traffic node congestion degree. Based on the method, firstly, the traffic congestion degree of each single node is predicted based on the flow that reaches the above single traffic node. Secondly, the traffic congestion degrees of multiple continuous traffic nodes connected with a current traffic node are predicted according to the flow of the current traffic node. Therefore, the traffic system is reasonably adjusted by related government departments according to the congestion degree information of the system.

Description

technical field [0001] The invention belongs to the field of intelligent traffic systems, and in particular relates to a queuing theory-based continuous traffic node congestion degree prediction model, system and method. Background technique [0002] At present, with the development of economy and the growth of population, the problem of traffic congestion is becoming more and more serious in cities. Traffic congestion has brought about a series of problems in economic, social and ecological aspects, resulting in serious losses in these aspects. Many countries have begun to vigorously develop public transport based on urban public transport, but they still cannot solve the common problems of traffic accidents, traffic congestion, and traffic pollution. So countries began to look for solutions, one of the important research direction is intelligent transportation system (ITS). Intelligent transportation system is the effective comprehensive application of advanced science a...

AI Technical Summary

Problems solved by technology

[0003] In the existing literature, researchers have proposed many models to alleviate traffic congestion, but many solutions are static

These static solutions are only to analyze and evaluate the traffic system, rather than to dynamically dispatch the traffic system, and traffic congestion cannot be predicted

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