Mobile phone user trip mode identification method based on mobile phone signaling data and navigation route data

Abstract

The invention relates to a mobile phone user trip mode identification method based on mobile phone signaling data and navigation route data. The method comprises the following steps that firstly, the mobile phone signaling data of a mobile phone user within a time period is acquired, and a user trip trajectory sequence is formed; then, a user trip trajectory is effectively divided into effective trip sections by utilizing lingering points; then, starting points and terminal points of the effective trip sections are extracted, a linear distance between every two points and the time consumed from the starting points to the terminal points of the user are calculated; therefore, the user performs preliminary judgment on trip modes of the effective trip sections, and judgment results are high-speed trip modes and low-speed trip modes; afterwards, corresponding navigation routes are extracted according to the judgment results in the previous step, and matching analysis is conducted on the navigation routes and base station sequences of the effective trip sections of the user by utilizing a DBSCAN clustering algorithm, the navigation route having maximum matching degree is taken as the route to be adopted by the user, and the trip mode of the route is the trip mode corresponding to the navigation route. The mobile phone user trip mode identification method has the advantages of being simple to achieve and high in identification accuracy.

Description

technical field [0001] The invention belongs to the technical field of traffic planning and management methods, and relates to a mobile phone user travel mode identification method based on mobile phone signaling data and navigation route data. Background technique [0002] The travel ratio of various modes of transportation and the sharing rate of public transportation have always been important data concerned by transportation planning and traffic management departments. In traffic analysis, commonly used traffic information collection methods include coils, microwaves, and videos. Different information collection methods have their advantages and scope of application. [0003] Due to the limited use of traffic collection methods such as coils, microwaves, and videos, it is impossible to continuously and effectively track people's travel behavior, and it is even more difficult to obtain OD information of people's travel. The cost of these traffic information collection d...

AI Technical Summary

Problems solved by technology

Its disadvantage is that it does not give the average speed, travel distance and travel route acquisition method of the user's travel sub-chain

Moreover, based on the mobile phone signaling data, the existing path matching method cannot obtain the user's accurate travel route, and the travel distance and average speed of the user's travel sub-chain cannot be obtained, and thus the user's travel mode cannot be accurately identified

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