A traffic flow forecasting method, forecasting model generation method and device

A traffic flow and forecasting model technology, applied in traffic flow detection, forecasting, traffic control systems, etc., can solve the problems of not being able to publish traffic flow data and predicting traffic flow data without technical solutions.

Active Publication Date: 2018-09-28
ALIBABA (CHINA) CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the way of releasing real-time traffic flow data is to publish the real-time traffic data (such as the driving speed of the road, etc.) The real-time traffic data is the real-time traffic situation of the road at the current moment, but it cannot release the traffic flow data for a certain period of time in the future
However, in real life, more and more users expect to know the traffic data of certain roads in advance in order to arrange their trip reasonably in advance. Therefore, the existing methods of publishing real-time traffic flow data cannot meet the needs of users.
[0003] Due to the strong nonlinearity and uncertainty of traffic flow data, it is difficult for humans to speculate which factors will affect the change of traffic flow in the next period. Therefore, there is no public and effective technical solution to accurately predict traffic flow data.

Method used

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  • A traffic flow forecasting method, forecasting model generation method and device
  • A traffic flow forecasting method, forecasting model generation method and device
  • A traffic flow forecasting method, forecasting model generation method and device

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Effect test

Embodiment 1

[0067] Embodiment 1 of the present invention provides a traffic flow forecasting method, the flow chart of which is as follows image 3 As shown, the method includes the following steps:

[0068] Step 301: For the road to be predicted, obtain the historical traffic flow data of the current time period of the road to be predicted;

[0069] The previous period of the current moment refers to a period including the current moment and the current moment forward. For example, if the current moment is tc, the previous period of the current moment is [t c-N+1 , t c ]. Generally, road traffic data is released every 2 minutes. Therefore, if the previous time period is half an hour, 15 traffic data are released in the previous time period. Assuming that the time interval for releasing traffic data is Tinterval, the number of traffic data released for one road throughout the day is (24*60) / Tinterval.

[0070] Step 302: Obtain the traffic flow prediction model corresponding to the roa...

Embodiment 2

[0109] In order to further enable those skilled in the art to understand the solution, a specific example is used below to describe it.

[0110] Assume that the road to be predicted is R0, the historical traffic flow data is published every 2 minutes, the selected historical traffic flow data is 150 historical traffic data from 9:02 to 14:00, and the preset initial BP neural network model The parameters are as follows:

[0111] The number of input data allowed by the input layer is N=15, the number of output data of the middle layer (hidden layer) is M=15, the number of output data of the output layer is L=15, and the first variance threshold E min = 0.02 and training learning rate η = 0.1;

[0112] The weight matrix V and W of the BP neural network model are as follows:

[0113]

[0114]

[0115] Since the input layer of the neural network model allows input traffic data N=15, 15 historical traffic data corresponding to every half hour can be used as a set of input da...

Embodiment 3

[0158] Based on the same inventive concept of the aforementioned traffic flow forecasting method, Embodiment 3 of the present invention provides a traffic flow forecasting device, the structural diagram of which is as follows Figure 5 As shown, include: training module 51, storage module 52, historical traffic data acquisition module 53, traffic flow prediction model acquisition module 54 and prediction module 55, wherein:

[0159] The training module 51 is used to train the preset neural network model according to the historical traffic flow data of the road in advance, so as to obtain the prediction method of the next period of the current moment of the road according to the historical traffic flow data of the previous period of the current moment of the road. Traffic flow forecasting models for traffic flow data;

[0160] A storage module 52, configured to store the correspondence between the road and its traffic flow prediction model obtained by the training module 51;

...

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Abstract

Disclosed are a traffic flow prediction method, and a prediction model generation method and device.The prediction method comprises: for a road to be predicted, acquiring historical traffic flow data of the road to be predicted within a time period prior to the current time (301); from a correlation between a pre-existing road and a traffic flow prediction model, acquiring the traffic flow prediction model corresponding to the road to be predicted (302); and inputting the historical traffic flow data within the time period prior to the current time into the traffic flow prediction model corresponding to the road to be predicted, to obtain traffic flow data within a time period after the current time (303). Since traffic flow data has high nonlinearity and uncertainty and a neural network model has a relatively high nonlinear prediction capability, the neural network model is trained according to historical traffic flow data of a road, so that a traffic flow prediction model obtained by training can relatively accurately predict the traffic flow data of the road within the time period after the current time according to the traffic flow data of the road within the time period prior to the current time.

Description

technical field [0001] The invention relates to the field of real-time traffic, in particular to a traffic flow forecasting method, a forecasting model generation method and a device. Background technique [0002] With the increasing popularity of intelligent transportation systems, the application of real-time traffic flow in intelligent transportation systems is becoming more and more extensive and in-depth. At present, the way of releasing real-time traffic flow data is to publish the real-time traffic data (such as the driving speed of the road, etc.) The real-time traffic data is the real-time traffic situation of the road at the current moment, but it cannot release the traffic flow data for a certain period in the future. However, in real life, more and more users expect to know the traffic data of certain roads in advance in order to arrange their trip reasonably in advance. Therefore, the existing methods of publishing real-time traffic flow data cannot meet the ne...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G08G1/065G06Q10/04G06Q50/30G06N3/04G06N3/08
CPCG08G1/01G06N3/02G16Z99/00
Inventor 吴跃进
Owner ALIBABA (CHINA) CO LTD
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