Road trip mode distinguishing method and system based on smart phone

Abstract

The invention provides a road trip mode distinguishing method and system based on a smart phone. The method includes the steps that an acceleration spectrum corresponding to acceleration frequency of vibration of an owner of the smart phone under various trip modes is divided into a plurality of subsections, and each subsection corresponds to one trip mode; a velocity spectrum of speed frequency characteristics of the owner of the smart phone under the various trip modes is divided into a plurality of subsections, and each subsection corresponds to one trip mode; acceleration information of vibration of the owner of the smart phone within a certain period of time is collected to obtain an acceleration data array within the period of time and further obtain a spectrum density average value according to data in the acceleration data array; longitude information and latitude information of the owner of the smart phone within a certain period of time are collected and the average speed of the owner of the smart phone can be obtained; the subsections of the acceleration spectrum which the spectrum density average value belongs to and the subsections of the velocity spectrum which the average speed belongs to are judged, and the specific trip mode can be obtained according to the two judging results.

Description

technical field [0001] The invention relates to a method for judging the current road traffic activity mode of a mobile phone holder through smart phone sensor (GPS sensor, acceleration sensor) data, belonging to the technical field of urban traffic management. Background technique [0002] The rapid development of smart phones provides new technical means for collecting urban traffic vehicle speed data. However, since mobile phone holders can take flexible travel methods, how to automatically identify mobile phone holders based on the data provided by mobile phone holders voluntarily? The travel mode has become a key technology for road vehicle operation data collection through smart phones. On the other hand, by automatically identifying the travel mode of the mobile phone holder through the data voluntarily provided by the mobile phone holder, a set of traffic travel data sets composed of multiple travel modes will be formed and generated from smartphone data, which will ...

AI Technical Summary

Problems solved by technology

The main problem of the existing discrimination methods is that they cannot effectively distinguish the low-speed travel states such as slow driving, walking, and bicycling. Therefore, a large proportion of sample data is misinterpreted, which not only causes a serious waste of data resources, but also makes the passing The accuracy of results from smartphone owners volunteering to provide data for analysis is severely reduced

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