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Short-term traffic flow predicting method

A technology of short-term traffic flow and forecasting method, which is applied in the field of short-term traffic flow forecasting to achieve high forecasting accuracy, good robustness, and good forecasting effect

Active Publication Date: 2014-11-05
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there is no short-term traffic flow prediction method based on the deep network structure of stacked autoencoder

Method used

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Embodiment Construction

[0031] The present invention will be described in detail below in conjunction with the accompanying drawings. It should be noted that the described embodiments are only intended to facilitate the understanding of the present invention, rather than limiting it in any way.

[0032] The invention provides a short-term traffic flow prediction method. Such as figure 1 As shown, specifically, the method includes the following steps:

[0033] Step S1: Merge historically recorded traffic flow data at specified time intervals.

[0034] The traffic flow data of the historical record comes from the traffic data acquisition system, which can be obtained by coil detection, video detection and other means.

[0035] The historical traffic flow data obtained is the number of vehicles passing by a specific observation point or road section within a certain time interval. The specified time interval may be specified according to forecast demand (eg, 15 minutes).

[0036] Accumulate several ...

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Abstract

The invention discloses a short-term traffic flow predicting method based on a deep-layer network structure of stacked autoencoders. The method comprises the following steps that input historical traffic flow data are merged according to an appointed time interval; the historical traffic flow data are normalized; a predicting model of the deep-layer network structure of the stacked autoencoders is trained; the predicting model is called for prediction. The method takes the time-space relationship of traffic flow into consideration, deeply mines the characteristics of the traffic flow, and is high in prediction precision and good in robustness.

Description

technical field [0001] The invention belongs to the field of intelligent traffic systems, in particular to a short-term traffic flow prediction method. Background technique [0002] Accurate and timely traffic flow information is crucial to the successful application of intelligent transportation systems. It can help road users make better travel decisions, alleviate traffic congestion, reduce carbon emissions, and improve traffic operation efficiency. Nowadays, traffic data is increasingly abundant, and we have entered the era of traffic big data. Effective use of traffic big data for more accurate and timely traffic flow forecasting can help managers make better traffic control plans and provide strong support for traffic travelers' travel decisions. [0003] Existing traffic flow forecasting methods mainly use shallow traffic forecasting models, and the forecasting results are still somewhat unsatisfactory. As early as the 1970s, the ARIMA model was used to predict sho...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G06N3/02
Inventor 王飞跃吕宜生段艳杰亢文文朱凤华
Owner INST OF AUTOMATION CHINESE ACAD OF SCI