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Method for predicting urban road overtaking based on deep recursive neural network

A technology of recurrent neural network and prediction method, which is applied in the field of urban road overtaking rate prediction based on deep recurrent neural network, can solve the problem that deep learning is not widely used in urban road prediction, and achieves the elimination of noise disturbance and strong robustness. Effect

Active Publication Date: 2019-02-15
SHANGHAI INST OF TECH
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Problems solved by technology

[0005] The application of deep learning in intelligent transportation construction is more and more extensive, but the application of deep learning in urban road prediction is not extensive

Method used

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  • Method for predicting urban road overtaking based on deep recursive neural network
  • Method for predicting urban road overtaking based on deep recursive neural network
  • Method for predicting urban road overtaking based on deep recursive neural network

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Embodiment Construction

[0039] To further illustrate the various embodiments, the present invention is provided with accompanying drawings. These drawings are a part of the disclosure of the present invention, which are mainly used to illustrate the embodiments, and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, those skilled in the art should understand other possible implementation modes and advantages of the present invention. Components in the figures are not drawn to scale, and like component symbols are generally used to denote similar components.

[0040] The present invention will be further described in conjunction with the accompanying drawings and specific embodiments.

[0041] refer to figure 1 As shown, the flow chart of the overtaking prediction model.

[0042] Data Sources:

[0043] The data source adopted by the present invention is based on the license plate rec...

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Abstract

The invention belongs to the field of machine learning, and in particular relates to a method for predicting the urban road overtaking based on a deep recursive neural network. By using a license plate recognition system such as an electronic police and a bayonet, the time comparison between the upstream and downstream license plate recognition can more accurately obtain an overtaking relationshipof vehicles within a road section. Compared with a traditional neural network, this model has an ability with higher precision and stronger generalization. The method for predicting the urban road overtaking based on the deep recursive neural network can more accurately predict an overtaking trend of urban roads, guarantees traffic safety to a certain extent, and provides a decision support for relevant management departments.

Description

technical field [0001] The invention belongs to the field of machine learning, in particular to a method for predicting the overtaking rate of urban roads based on a deep recursive neural network. Background technique [0002] Overtaking on urban roads has always been a common concern of the society, especially the phenomenon of large-scale overtaking, which not only buries potential safety hazards, but even endangers people's lives and property. Realizing the timely management and control of the overtaking problem on urban roads is an urgent problem to be solved at present. Accurately predicting the overtaking flow of specific road sections in the city will provide strong decision-making support for law enforcement agencies and greatly ensure the stability and safety of traffic order on urban roads. Overtaking on urban roads is the most common behavior in the driving process. Scholars at home and abroad have carried out extensive and in-depth research on overtaking. [00...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G08G1/017G06N3/04G06K9/00
CPCG08G1/0104G08G1/0125G08G1/0175G06V20/52G06V20/625G06N3/045
Inventor 王浩黄美鑫李晓丹鞠建敏武志薪
Owner SHANGHAI INST OF TECH
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