Short-time traffic flow prediction method based on spatial-temporal correlativity

A technology of time-space correlation and traffic flow, applied in the field of intelligent transportation, it can solve the problems of slow prediction speed and complex model, and achieve the effect of less parameters, simple model structure and accurate prediction results.

Active Publication Date: 2019-09-10
QINGDAO UNIV OF SCI & TECH
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Problems solved by technology

[0005] The purpose of the present invention is to provide a short-term traffic flow prediction method based on spatio-temporal c...

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  • Short-time traffic flow prediction method based on spatial-temporal correlativity
  • Short-time traffic flow prediction method based on spatial-temporal correlativity
  • Short-time traffic flow prediction method based on spatial-temporal correlativity

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Embodiment Construction

[0040] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0041] figure 1 Shown is a flow chart of an embodiment of the short-term traffic flow prediction method based on the temporal-spatial correlation of the present invention.

[0042] Such as figure 1 As shown, this embodiment adopts following process to realize short-term traffic flow prediction:

[0043] Step 1: Use convolution and gated recurrent units to determine the spatiotemporal characteristics of traffic flow data, and use bidirectional gated recurrent units to determine the periodic characteristics of traffic flow data.

[0044] Convolution and gated recurrent units are used to determine the spatio-temporal characteristics of traffic flow data. For the specific execution process, see figure 2 A flowchart of a specific embodiment.

[004...

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Abstract

The invention discloses a short-time traffic flow prediction method based on spatial-temporal correlativity. The method comprises the following steps: determining an intraday traffic flow data matrixcontaining a target prediction point and a monitoring point; performing convolution processing and gating circular unit processing on the intraday traffic flow data matrix to acquire spatial-temporalcharacteristics of the traffic flow data; determining the previous day traffic flow data matrix and a last week traffic flow data matrix based on the traffic flow data of the target prediction point and the monitoring point at the same moment of the previous day and the same moment of the same day of the last week, and processing by adopting a bidirectional gating circular unit to acquire periodiccharacteristics of the traffic flow data; performing fusion on the spatial-temporal characteristics of the traffic flow data and the periodic characteristics of the traffic flow data, inputting intoa predictor, thereby predicting the traffic flow of the target prediction point. By applying the method disclosed by the invention, the problem that the short-time traffic flow prediction is complex in model and slow in prediction speed can be solved.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, in particular, relates to a traffic flow forecasting method, more specifically, relates to a short-term traffic flow forecasting method based on spatio-temporal correlation. Background technique [0002] Traffic flow forecasting refers to the prediction of traffic flow changes in the future based on historical traffic data. With the rapid development of urban intelligent transportation systems, as an important part of intelligent transportation systems, traffic flow forecasting, especially short-term traffic flow forecasting with small time series data intervals, can not only help people plan travel routes and save travel time , so as to reduce traffic congestion and unnecessary waste of resources, and also play a vital role in the future construction of smart cities with information perception, deep interconnection, collaborative sharing, intelligent processing, and open appli...

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Application Information

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IPC IPC(8): G08G1/01G06Q10/04G06Q50/26G06F17/16
CPCG06F17/16G06Q10/04G06Q50/26G08G1/0129
Inventor 孙丽珺闫杨于小洁
Owner QINGDAO UNIV OF SCI & TECH
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