A traffic flow prediction method and device

Abstract

The present application provides a traffic flow forecasting method and device, wherein, firstly, the traffic flow characteristic data of the target road section in each historical time period in multiple historical time periods is acquired; Filter the effective traffic flow characteristic data in the characteristic data, and determine the weight of the effective traffic flow characteristic data in each historical time period; finally, based on the determined effective traffic flow characteristic data and the corresponding weight, predict the vehicle traffic of the target road section flow. The above technical solution can predict accurate traffic flow by screening effective traffic flow characteristic data and combining the weight of effective traffic flow characteristic data, which overcomes the defect of large prediction deviation in the prior art.

Description

technical field [0001] The present application relates to the technical field of forecasting and calculation, and in particular, to a method and device for forecasting traffic flow. Background technique [0002] With the continuous development of the economy and the continuous improvement of people's living standards, people's travel is increasingly dependent on online car-hailing or self-driving travel. The ensuing problem is that traffic congestion is becoming more and more serious, which leads to a decline in travel efficiency. Therefore, timely and accurate acquisition of traffic flow information on the road is helpful for users to plan their itinerary in advance based on the traffic flow information, travel at off-peak times, and improve travel efficiency. [0003] Most of the current traffic flow prediction methods are based on linear models or tree models. Although the above methods can predict the traffic flow of a certain road section, they cannot reasonably integra...

AI Technical Summary

Problems solved by technology

[0003] At present, most of the traffic flow prediction methods are based on linear models or tree models. Although the above methods can predict the traffic flow of a certain road section, the deviation of the predicted traffic flow is large due to the inability to reasonably integrate context information.

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