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Day-dimension regional traffic index prediction method considering influences of multiple factors

A technology of traffic index and forecasting method, which is applied in the direction of traffic flow detection, forecasting, and data processing applications, etc., which can solve the problem of few forecasting applications, inability to serve industry managers with a forward-looking overall grasp of road network operation conditions, and insufficient consideration of traffic flow operation Various factors of the state and other issues

Active Publication Date: 2018-01-19
BEIJING UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Medium and long-term forecasting applications are seldom used, and thus cannot serve industry managers' forward-looking overall grasp of road network operation status in a long period of time in the future
At the same time, the division of factors affecting road network status is not fine enough, and various factors that may affect the operation status of traffic flow have not been fully considered.

Method used

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  • Day-dimension regional traffic index prediction method considering influences of multiple factors
  • Day-dimension regional traffic index prediction method considering influences of multiple factors
  • Day-dimension regional traffic index prediction method considering influences of multiple factors

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Embodiment Construction

[0088] The present invention selects Beijing Guomao regional traffic index as the prediction object, uses the medium and long-term regional traffic index prediction method based on decision tree theory to predict the traffic index of this region on April 17-23, 2017, and calculates the morning and evening peak index Perform model accuracy verification.

[0089] The specific implementation steps are as follows:

[0090] Step 1, divide key areas of concern;

[0091] Comprehensively considering factors such as the nature of land use, administrative divisions, natural landforms, and road network structure, Beijing is divided into 1911 traffic districts without breaking administrative divisions and using natural partitions such as rivers and railways as the boundaries of traffic districts . Considering the large difference in traffic demand between the inner and outer ring areas of the city, the fineness of the division of traffic districts is also different. Therefore, the area ...

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Abstract

The invention discloses a day-dimension regional traffic index prediction method considering influences of multiple factors. The method comprises the steps that regions are divided and aggregated; regional traffic index original data preprocessing is carried out; the influences of multiple factors are considered, and regional traffic index prediction under the day dimension is carried out. According to the specific technical scheme of the method, on the basis of traffic cell division, traffic cells with the same aggregation property are aggregated, and regional traffic indexes are calculated;on the basis of road network operation early warning requirements, a prediction time period and a prediction cycle are determined; regional traffic data is extracted, made up for and removed, and preprocessing such as comprehensive building of a historical data factor attribute set from different angles is conducted on the data; on the basis of a decision tree theory, regional road network operation congestion state prediction is carried out; a final prediction result of the regional traffic indexes is determined by means of the square euclidean distance. By means of the method, on the one hand, monitoring and application of the urban road network operation state is deepened, and on the other hand, technical support is provided for early warning and forecasting work of the road network operation state.

Description

technical field [0001] The invention relates to a daily-dimension regional traffic index prediction method considering the influence of multiple factors, and belongs to the field of traffic data mining application and traffic information prediction. Background technique [0002] With the improvement of traffic informatization and intelligence, cities and regions have realized traffic operation monitoring of different scopes and contents, providing a strong support service for ensuring the safe, efficient and green operation of the traffic system. Under the premise of having a large amount of monitoring data, how to shift from passive monitoring of traffic operation status to more active early warning, prediction and corresponding control measures has become the core issue that industry authorities are paying more and more attention to. The urban road network is the blood of an urban traffic road system. If the road network operation efficiency is low, the normal operation of...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G06Q10/04
Inventor 翁剑成邸小建林鹏飞王晶晶付宇毛力增
Owner BEIJING UNIV OF TECH
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