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Short-term speed prediction method for signal intersection road section

A speed prediction and intersection technology, which is applied in forecasting, traffic flow detection, neural learning methods, etc., can solve the problems of low prediction accuracy and achieve obvious advantages

Active Publication Date: 2020-02-21
ENJOYOR COMPANY LIMITED
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In order to overcome the shortcomings of the low prediction accuracy of existing short-term speed prediction methods, the present invention provides a short-term speed prediction method for road sections at signalized intersections with high prediction accuracy

Method used

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  • Short-term speed prediction method for signal intersection road section
  • Short-term speed prediction method for signal intersection road section
  • Short-term speed prediction method for signal intersection road section

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Embodiment Construction

[0043] The present invention will be further described below in conjunction with the accompanying drawings.

[0044] refer to Figure 1 to Figure 5 , a short-term speed prediction method for a road section at a signalized intersection, comprising the following steps:

[0045] 1) Data integration preprocessing

[0046] Match road section speed data and signal light operation data, and construct intersection traffic data set and road network traffic data set for intersection and road network respectively;

[0047] The intersection traffic dataset matrix size is N num_of_lane × T hi s ×C, where N num_of_lane Indicates the number of lanes at the current target intersection entrance; T hi s Indicates the length of the historical data period; C indicates the intersection-level feature dimension;

[0048] The size of the road network traffic dataset matrix is ​​N×C×T, where N represents the total number of intersections in the region; T represents the time dimension of historic...

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Abstract

The invention discloses a short-term speed prediction method for a signal intersection road section. The method comprises the following steps: (1) integrating and processing traffic data, matching road section speed data and signal lamp operation data, and respectively constructing an intersection traffic data set and a road network traffic data set aiming at an intersection and a road network; (2) carrying out input data space-time modeling, comprising a traffic space model and a traffic time sequence model; and (3) constructing a prediction model, and based on a depth graph convolutional network GCN and a recurrent neural network RNN, constructing a short-term speed prediction model of the signal intersection road section by utilizing a generative adversarial network GAN framework. The short-term speed prediction method for the signal intersection road section provided by the invention is high in prediction accuracy.

Description

technical field [0001] The invention relates to the field of urban traffic, in particular to the field of short-term speed prediction. Background technique [0002] Urban road traffic congestion has been a problem for a long time. In the past, the more common method was to improve the traffic supply capacity of the urban road network through the construction of roads and infrastructure. However, due to the limitation of urban land resources and cost input, it is impossible to expand indefinitely. Therefore, it is imperative to increase investment in road traffic infrastructure, formulate urban modern road traffic management plans, adopt advanced technical means, and realize scientific management and control. [0003] The development of intelligent transportation technology provides new ideas for solving urban road traffic problems. The Intelligent Transportation System (ITS) was born with the development of science and technology. Through the comprehensive application of ad...

Claims

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Application Information

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IPC IPC(8): G08G1/01G08G1/052G06Q10/04G06Q50/26G06N3/04G06N3/08
CPCG08G1/0125G08G1/052G06Q10/04G06Q50/26G06N3/088G06N3/045
Inventor 王建龙张彤金峻臣杨辉何伟钱小鸿
Owner ENJOYOR COMPANY LIMITED
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