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Driving model training method, driver identification method, driving model apparatus, driver identification apparatus, device and medium

A technology of driving model and training method, which is applied in the field of driver recognition method, driving model training method, device, equipment and media, can solve the problems of poor driving model recognition effect, save training time, enhance generalization, and ensure The effect of accuracy

Active Publication Date: 2018-02-09
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Embodiments of the present invention provide a driving model training method, a driver recognition method, device, equipment, and medium to solve the problem that the current driving model recognition effect is poor

Method used

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  • Driving model training method, driver identification method, driving model apparatus, driver identification apparatus, device and medium
  • Driving model training method, driver identification method, driving model apparatus, driver identification apparatus, device and medium
  • Driving model training method, driver identification method, driving model apparatus, driver identification apparatus, device and medium

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Experimental program
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Embodiment 1

[0042] figure 1 A flow chart of the driving model training method in this embodiment is shown. The driving model training method can be applied to terminal devices of insurance institutions or other institutions for training driving models so that the trained driving models can be used for recognition to achieve the effect of intelligent recognition. For example, the driving model training method can be applied to the terminal equipment of the insurance institution to train the driving model corresponding to the user, so as to use the trained driving model to identify the user who has applied for auto insurance at the insurance institution to determine whether it is the user I drive. Such as figure 1 As shown, the driving model training method comprises the following steps:

[0043] S11: Obtain training behavior data of the user, and the training behavior data is associated with the user identifier.

[0044] Wherein, the training behavior data refers to the behavior data o...

Embodiment 2

[0100] Figure 6 A functional block diagram of a driving model training device corresponding to the driving model training method in Embodiment 1 is shown. Such as Figure 6 As shown, the driving model training device includes a training behavior data acquisition module 11 , a training driving data acquisition module 12 , a positive and negative sample acquisition module 13 , an original driving model acquisition module 14 and a target driving model acquisition module 15 . Wherein, the implementation functions of the training behavior data acquisition module 11, the training driving data acquisition module 12, the positive and negative sample acquisition module 13, the original driving model acquisition module 14 and the target driving model acquisition module 15 are corresponding to the driving model training method in embodiment 1 The steps correspond to one by one, and to avoid redundant description, this embodiment does not describe them in detail one by one.

[0101] Th...

Embodiment 3

[0121] Figure 7 A flow chart of the driver identification method in this embodiment is shown. The driver identification method can be applied to terminal equipment of insurance agencies or other agencies, so as to identify the driver's driving behavior and achieve the effect of intelligent identification. Such as Figure 7 As shown, the driver identification method includes the following steps:

[0122] S21: Obtain the behavior data to be identified of the user, and the behavior data to be identified is associated with the user identifier.

[0123] Among them, the behavior data to be identified refers to the behavior data collected in real time when the user travels to identify whether the target user is driving. Behavior data includes, but is not limited to, at least one of data such as speed, acceleration, angle, and angular acceleration collected at any time when the user travels. In this embodiment, the behavior data to be identified is associated with the user identi...

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Abstract

The present invention discloses a driving model training method, a driver identification method, a driving model apparatus, a driver identification apparatus, a device, and a medium. The driving modeltraining method includes the following steps that: the training behavior data of a user are acquired, wherein the training behavior data are associated with a user identifier; training driving data associated with the user identifier are obtained on the basis of the training behavior data; positive and negative samples are obtained from the training driving data on the basis of the user identifier, and the positive and negative samples are divided into a training set and a test set; the training set is trained by using a bagging algorithm, so that an original driving model can be obtained; and the test set is adopted to test the original driving model, so that a target driving model can be obtained. With the driving model training method adopted, the generalization of the driving model can be effectively enhanced; the problem of poor recognition results of current driving recognition models can be solved; and the accuracy of identifying the driving of drivers is improved.

Description

technical field [0001] The present invention relates to the field of behavior recognition, in particular to a driving model training method, a driver recognition method, device, equipment and medium. Background technique [0002] With the development of the information age, artificial intelligence technology, as a core technology, is increasingly being used to solve specific problems in people's lives. At present, when judging whether it is the mobile phone user driving the car, a single model is generally used to identify the driver to confirm whether the mobile phone user is driving the car himself. This method of only using a single model for driver identification has limitations, and this single model The generalization ability of the mobile phone is weak, so that the obtained recognition results cannot better reflect whether the driver is the person driving, that is, the recognition result is poor, so that the current recognition accuracy of the mobile phone user drivin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/285G06F18/214B60W2040/0809B60W40/09G06N3/084G06N3/044G06F18/24133G06F18/23G06F18/25G06F18/24137
Inventor 金鑫吴壮伟张川赵媛媛黄度新梁永健霍丽
Owner PING AN TECH (SHENZHEN) CO LTD
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