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Driving risk assessment method and device based on driving behaviors

A driving risk and behavior technology, applied in the fields of instruments, finance, data processing, etc., can solve problems that cannot accurately reflect the actual danger, and cannot be provided by different customers of insurance companies.

Inactive Publication Date: 2017-07-14
南京人人保网络技术有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] With the rise of UBI Internet of Vehicles insurance and big data, there is an urgent need for a scientific method to evaluate the driver's driving risk. The evaluation results can be used as the support of the driving risk data of the test vehicle owner to remind and urge the owner to improve driving habits. , so as to improve the safety awareness of car owners, and can also provide a basis for insurance companies to formulate different levels of premiums. At present, the insurance evaluation of UBI at home and abroad is only after assigning appropriate weights to risk factors and doing simple fitting and calculation. But The evaluation results obtained by this method cannot accurately reflect the actual risk situation, nor can it provide a more accurate basis for insurance companies to target different customers.

Method used

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  • Driving risk assessment method and device based on driving behaviors
  • Driving risk assessment method and device based on driving behaviors
  • Driving risk assessment method and device based on driving behaviors

Examples

Experimental program
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no. 1 example

[0029] Please refer to figure 2 , figure 2 It is a flow chart of a driving behavior-based driving risk assessment method provided in the first embodiment of the present invention, and the method specifically includes the following steps:

[0030] Step S110: acquiring first driving behavior parameter data.

[0031]First obtain the first driving behavior parameter data, the first driving behavior parameter data may include vehicle mileage, night driving ratio, peak driving ratio, driving ratio on familiar road sections, maximum average speed of each section of journey, emergency braking per 100 kilometers The number of times, the number of rapid accelerations per 100 kilometers, the proportion of fatigue driving time, accident data and other data. Among them, the night driving time is defined as 21:00-24:00pm, the peak time is defined as 8:00-9:00am and 16:00-18:00pm, and the familiar road section is defined as the three most frequent stall points, The proportion of driving...

no. 2 example

[0043] Please refer to image 3 , image 3 It is a flowchart of a driving behavior-based driving risk assessment method provided by the second embodiment of the present invention, and the method specifically includes the following steps:

[0044] Step S210: Obtain a plurality of second driving behavior parameter data.

[0045] In order to build a risk prediction model and improve the accuracy of the evaluation results, it is necessary to obtain a plurality of second driving behavior parameter data, each of which includes vehicle mileage, night driving ratio, peak hour driving ratio, Data such as the proportion of drivers who are familiar with road sections, the average maximum speed of each mileage, the number of sudden brakes per 100 kilometers, the number of rapid accelerations per 100 kilometers, the proportion of fatigue driving time, and accident data. Amount of compensation, etc.

[0046] The plurality of second driving behavior parameter data can be obtained through ...

no. 3 example

[0071] Please refer to Figure 4 , Figure 4 It is a structural block diagram of a driving behavior-based driving risk assessment device 200 provided in the third embodiment of the present invention, and the device specifically includes:

[0072] The first acquiring module 210 is configured to acquire first driving behavior parameter data.

[0073] The risk prediction module 220 is configured to input the first driving behavior parameter data into a pre-acquired risk prediction model for risk prediction.

[0074] An evaluation result obtaining module 230, configured to obtain an evaluation result according to the first driving behavior parameter data and the risk prediction model.

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Abstract

An embodiment of the invention provides a driving risk assessment method and a driving risk assessment device based on driving behaviors, and the driving risk assessment method and the driving risk assessment device belong to the field of risk prediction. The driving risk assessment method comprises the steps of: acquiring first driving behavior parameter data; inputting the first driving behavior parameter data into a pre-acquired risk prediction model for risk prediction; and acquiring an assessment result according to the first driving behavior parameter data and the risk prediction model. According to the driving risk assessment method and the driving risk assessment device, the assessment result is high in precision, and can be identified by insurance companies through data output and used for screening driving risks, thereby reducing a combined ratio thereof, and realizing a win-win situation; meanwhile, the driving risk assessment method and the driving risk assessment device can provide technical support and data support for the innovative differential pricing in the car insurance industry, and can earn fairer and more reasonable commercial insurance premium pricing for the good vehicle owners who drive safely.

Description

technical field [0001] The present invention relates to the field of risk prediction, in particular to a driving behavior-based driving risk assessment method and device. Background technique [0002] With the rise of UBI Internet of Vehicles insurance and big data, there is an urgent need for a scientific method to evaluate the driver's driving risk. The evaluation results can be used as the support of the driving risk data of the test vehicle owner to remind and urge the owner to improve driving habits. , so as to improve the safety awareness of car owners, and can also provide a basis for insurance companies to formulate different levels of premiums. At present, the insurance evaluation of UBI at home and abroad is only after assigning appropriate weights to risk factors and doing simple fitting and calculation. But The evaluation results obtained by this method cannot accurately reflect the actual risk situation, nor can it provide a more accurate basis for insurance com...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q40/08
CPCG06Q10/04G06Q40/08
Inventor 帅勇
Owner 南京人人保网络技术有限公司
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