Motion trajectory-based high-speed rail user identification method

Abstract

The invention discloses a high-speed rail user identification method based on motion trajectory, which belongs to the technical field of mobile user special scene identification, including data acquisition and name definition, and the name definition includes station area, high-speed rail area, public network area, time occupied by the first area, and occupied area. The time of the last cell, the total duration, and the duration of a single cell; station cells: waiting halls / platforms / occupied cells before and after high-speed rail enters and exits; high-speed rail cells: high-speed rail cells + non-high-speed rail cells in urban areas; public network cells: The first layer of the non-urban area; the time of occupying the first cell: the end time of the last XDR in this cell; the time of occupying the last cell: the start time of the first XDR in this cell. The present invention simplifies the recognition algorithm and improves the recognition accuracy by combining the screening of the station district, the high-speed rail private network district, the public network district near the high-speed railway, the occupied time of the district and the speed of the road section.

Description

technical field [0001] The invention relates to the technical field of special scene identification of mobile users, in particular to a high-speed rail user identification method based on motion trajectory. Background technique [0002] The existing high-speed rail user identification algorithms are limited by factors such as high-speed rail speed dynamics and unstable switching sequences, and the recognition effect is poor. The existing high-speed rail user identification algorithm is as follows: [0003] By collecting the signaling messages of the S1-MME interface, the cells occupied by the same user are sorted in chronological order. When the user occupies more than 3 high-speed rail private network cells, the comprehensive Identified as a high-speed rail user. Specific steps are as follows: [0004] Step 1: The full-volume user screening method counts within a time granularity (60 minutes), the same user has more than 3 users under different high-speed rail private ne...

AI Technical Summary

Problems solved by technology

[0008] Problems and shortcomings of the existing technology: the moving speed verification method in step 3, "by judging whether the moving speed is > 150km / h, improve the recognition accuracy" threshold is too strict, for example, the train is entering and leaving the station, and the train speed is average All are lower than 100km / h, and the time difference between each cell is calculated to calculate the speed. The algorithm logic is too complicated and difficult to implement