Passing time determination method and device, terminal and storage medium

Abstract

The embodiment of the invention discloses a passing time determining method and device, a terminal and a storage medium, and belongs to the technical field of computers. The method comprises the stepsof obtaining a to-be-passed target route; starting from a first road section in a plurality of road sections, for a first road section and a second road section which are adjacent at any two positions, according to the first state data of the first road section, based on the passing time selection model and the state data prediction model, determining the passing time of the first road section, and under the first state data, according to the passing time, determining second state data of the second road section after passing through the first road section; and according to the second state data, continuously determining the passing time of the second road section based on the passing time selection model and the state data prediction model until the passing time of each road section in the plurality of road sections is determined, so that the passing time and the state data can be predicted by taking the road sections as units, the local information of the route is fully considered,and the prediction accuracy is improved.

Description

technical field [0001] The embodiments of the present invention relate to the field of computer technology, and in particular to a method, device, terminal and storage medium for determining a passing time. Background technique [0002] With the development of Internet technology and the popularization of mobile terminals, navigation functions are widely used in daily life. When a user wants to pass a route, the navigation function of the mobile terminal can be used to predict the passage time of the route, thereby predicting the time when the user arrives at the destination. point, which brings a lot of convenience to the user's travel. [0003] In related technologies, a time point prediction model is usually used to determine the time point when the user arrives at the destination. In the model training phase, sample data of at least one sample route is obtained, the sample data includes route description data and historical traffic data corresponding to the sample route...

AI Technical Summary

Problems solved by technology

[0004] However, in the above scheme, the time-point prediction model is only trained based on the global information of the route, and the local information of the route is not considered, so the time-based prediction model can only determine the estimated time of arrival based on the global information of the route, and the prediction is not accurate enough

Images