Traffic feature prediction method, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a traffic feature prediction method, electronic equipment and a storage medium. The method comprises the following steps: acquiring a current index of a target road in a current time period; the current index comprises known traffic characteristics of the target road; similarity comparison is carried out on the current index and historical indexes in a historical time period, and the historical index with the maximum similarity with the current index is determined to serve as a target index; wherein the historical index and the historical index value corresponding to the historical index are pre-stored in a database in an associated manner, and the historical index comprises a first historical traffic feature of the target road; the historical index value comprises a second historical traffic feature of the target road within a set time period after the historical time period; and determining predicted traffic characteristics of the target road in the prediction time period based on the historical index value corresponding to the target index.

Description

technical field [0001] The present disclosure relates to the technical field of navigation, and in particular, to a traffic feature prediction method, an electronic device and a storage medium. Background technique [0002] With the continuous expansion of the scale of cities, the continuous increase in the number of private cars, and the continuous increase in people's travel needs, the application of location-based service systems is becoming more and more extensive. One of the important services of the location-based service system is the dynamic traffic service. The information provided by the dynamic traffic service includes whether the road is congested, the average traffic characteristics of vehicles and / or the average traffic speed of vehicles, etc. For example, an application with map navigation function usually plans a navigation route for the user based on the dynamic traffic service when the user initiates a route planning request, and calculates the estimated tr...

AI Technical Summary

Problems solved by technology

In the prior art, the average vehicle speed and / or the average vehicle time on the current road are estimated by using the speed or time of the same period in history, but the road conditions in the same period in history are very different from the current road conditions, and the road conditions will be affected by external factors every year. If the speed or time of the same period in history is used to estimate the average passing speed and / or the average passing time of vehicles, it is easy to introduce historical noise errors, resulting in inaccurate predicted road condition information

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