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

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...

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.

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