Traffic jam state propagation prediction and early warning system and method based on city portraits

A technology for urban traffic and traffic congestion, applied in the field of information, to solve problems such as loss of early input

Active Publication Date: 2020-10-13
BEIHANG UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the traditional recurrent neural network has a long-term dependence problem. As time goes by, the recurrent neural network gradually loses the memory of the early input, and the predictions made only refer to the latest input data. When there are more data, the data spanning The longer the time, the more obvious the long-term dependence becomes

Method used

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  • Traffic jam state propagation prediction and early warning system and method based on city portraits
  • Traffic jam state propagation prediction and early warning system and method based on city portraits
  • Traffic jam state propagation prediction and early warning system and method based on city portraits

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Embodiment Construction

[0037] The specific architecture and prediction method of the present invention will be further described below in conjunction with the accompanying drawings:

[0038] like figure 1 As shown, a kind of traffic congestion state prediction and early warning system based on city portrait of the present invention includes: data collection and processing module, deep learning module, historical record module, front-end display module and website back-end module;

[0039] Data collection and processing module: responsible for the collection and arrangement of urban traffic basic data, and real-time detection of passing vehicles using urban traffic cameras, statistics of corresponding real-time data, and sorting; urban basic data (including city maps, road lanes, etc.) quantity, road speed limit and other information) to the back-end module of the website, and the road dynamic data at each moment is sent to the trained deep learning algorithm module in the form of a sequence to build...

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Abstract

The invention discloses a traffic jam state prediction and early warning system and method based on city portraits. The system comprises the following modules: a data collection and processing module,a deep learning module, a historical record module and a front-end display module. Recording road condition information of each street and intersection in real time by utilizing data provided by a traffic camera; streets are abstracted into edges in an undirected graph, intersections are abstracted into points in the undirected graph, road condition information of the streets and the intersections is sorted into edge weights and point weights, the edge weights and the point weights are input into a deep learning model of a dynamic graph, a real-time city portrait is constructed, city trafficcongestion state propagation at the next moment is predicted, and early warning information is reported to a congestion area.

Description

technical field [0001] The invention relates to a system and method for forecasting and early warning of traffic congestion state based on city portraits, and belongs to the field of information technology. Background technique [0002] With the development of urbanization, by 2050, studies estimate that 6 billion people will live in cities, and urban transportation is closely related to social pain points such as people's livelihood, economy, education, and housing, and is closely related to the development and prosperity of a city , only a safe and efficient traffic environment can play a positive role in promoting the development of the city. At present, the main streets of the city are equipped with traffic supervision cameras, which can clearly record information such as vehicles and pedestrians passing through the streets. These data provide conditions for the further development of urban traffic supervision. Congestion is one of the most serious problems affecting ur...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G08G1/052G08G1/0968G08G1/097G06N3/04
CPCG08G1/0125G08G1/0137G08G1/052G08G1/096805G08G1/097G06N3/045
Inventor 盛浩窦鑫泽吕凯张洋吴玉彬
Owner BEIHANG UNIV
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