A system, method, device and storage medium for recognizing driving behavior

Abstract

The invention discloses a driving behavior recognition system, method and device and a storage medium and mainly comprises a driving behavior identification system which comprises an acquisition module, a preposition rule determination module, a time determination module, a data processing module, a communication module and an identification module. The acquisition module is used for acquiring first motion data; wherein the preposition rule determining module is used for determining a preposition rule, and the preposition rule comprises a fluctuation variance threshold value; the time determination module is used for determining a time period based on the first motion data; the data processing module is used for acquiring the second motion data; the communication module is used for transmitting the second motion data and the time period; and the identification module is used for identifying dangerous driving behaviors based on the second motion data. The dangerous driving behavior canbe automatically recognized, and help is provided for the system to provide services such as safety warning and driving assistance.

Description

technical field [0001] The present invention relates to a device and a method for recognizing driving behavior, in particular to a device and a method for recognizing driving behavior based on motion data. Background technique [0002] With the development of Internet technology, on-demand services, such as online taxi services, have played an important role in people's daily life. For example, an on-demand ride-hailing service may be frequently used by a user (eg, a passenger). Through an online taxi-hailing platform, users can request services through an application installed in a smart device such as a mobile phone. According to the pre-dangerous driving rules, sensors installed in smartphones can generate driving data. By using the data generated by smartphones, online taxi-hailing platforms can analyze the driving behavior of transportation services. However, there are large differences in the accuracy and sensitivity of sensors used by different Android mobile phone ...

AI Technical Summary

Problems solved by technology

However, there are large differences in the accuracy and sensitivity of sensors used by different Android mobile phone brands and different models of the same mobile phone brand, which makes it difficult for the existing identification scheme of dangerous driving pre-rules to achieve the ideal recall rate on different Android models.

Based on the characteristics of Android data, if a set of more sensitive pre-trigger rules is adopted, it will make it difficult to achieve the effect of recognition accuracy of shaking data

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