Traffic state prediction method based on clustering analysis and Markov model

A Markov model, traffic state technology, applied in traffic flow detection, traffic control system of road vehicles, traffic control system, etc., can solve problems such as large amount of calculation and complex selection of evaluation indicators.

Inactive Publication Date: 2019-08-02
CHINA HIGHWAY ENG CONSULTING GRP CO LTD
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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 state prediction method based on cluster analysis

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  • Traffic state prediction method based on clustering analysis and Markov model
  • Traffic state prediction method based on clustering analysis and Markov model
  • Traffic state prediction method based on clustering analysis and Markov model

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Embodiment Construction

[0054] In order to make the object, technical solution and effect of the present invention better and clearer, the present invention will be further described in detail below. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0055] The present invention provides the flow chart of the implementation of the traffic state prediction method based on cluster analysis and Markov model, as figure 2 As shown, the methods include:

[0056] Select the index that is most sensitive to the intersection traffic state or the easiest to obtain as the discriminant index of the intersection traffic state;

[0057] Traffic volume refers to the number of participants who actually participate in traffic through a certain point or a certain section on the road within a unit of time. Also known as traffic flow or flow.

[0058] The traffic occupancy rate refers to the ratio of the time that ...

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Abstract

The invention relates to a traffic state prediction method based on clustering analysis and Markov models. The method comprises the steps of selecting the traffic volume and the traffic occupancy rateas evaluation indexes of the traffic state of urban crossroads; performing clustering analysis on the traffic volume and the traffic occupancy rate by a K means clustering method according to a largenumber of traffic flow data collected by a traffic control center; determining a weight set of the traffic volume and the traffic occupancy rate by a method combining an entropy evaluation method andan analytic hierarchy method; determining a membership degree function of the traffic volume and the traffic occupancy rate by a linear analysis method, and obtaining a membership degree matrix; calculating a fuzzy comprehensive evaluation matrix; evaluating the existing traffic state according to the maximum membership degree principle; and predicating the future traffic state on the basis of aMarkov model according to the existing traffic state. The traffic state prediction method is applicable to practical cases; and the prediction precision is improved.

Description

technical field [0001] The present invention designs the technical field of intelligent traffic, especially relates to traffic state prediction method based on cluster analysis and Markov model Background technique [0002] With the continuous development of economy and technology, people have higher and higher requirements for travel traffic information, such as knowing the current traffic status of the road before travel, so that they can choose the most effective traffic route and travel mode. Therefore, traffic control and guidance The system has become a popular core topic in the research of intelligent transportation systems, and the key issue in realizing traffic control and guidance systems is real-time and accurate traffic state prediction, that is, how to effectively use real-time traffic data to predict traffic conditions. Regarding the evaluation of traffic status based on traffic parameters, it is more common to use multiple traffic parameters such as traffic vo...

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Application Information

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IPC IPC(8): G08G1/01G06K9/62
CPCG08G1/0125G08G1/0133G06F18/23G06F18/295
Inventor 安泽萍朱弘戈张艳贺静裴月玲
Owner CHINA HIGHWAY ENG CONSULTING GRP CO LTD
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