A vehicle feature data processing method and a vehicle risk prediction model training method

A technology for data processing and vehicle characteristics, applied in data processing applications, instruments, finance, etc., can solve the problems of low precision, incomplete data characteristics, and low accuracy of vehicle accident probability prediction.

Active Publication Date: 2019-06-04
NAVINFO
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the incomplete data characteristics and the fact that only one algorithm is used for calculation when training the model, the

Method used

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  • A vehicle feature data processing method and a vehicle risk prediction model training method
  • A vehicle feature data processing method and a vehicle risk prediction model training method
  • A vehicle feature data processing method and a vehicle risk prediction model training method

Examples

Experimental program
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Embodiment 1

[0029] In this embodiment, a method for processing vehicle characteristic data is provided, figure 1 is a flowchart of a method for processing vehicle characteristic data according to an embodiment of the present invention, such as figure 1 As shown, the method includes the following steps:

[0030] S101: Acquire at least one kind of raw data; where the raw data may include vehicle body data, driving behavior data, driving environment data, and the like. Specifically, use the existing Internet of Vehicles platform to obtain GPS track point data, a large amount of vehicle body data, rich driving behavior data and some driving environment data; use map data to obtain geographic information data, surrounding vehicle data such as road condition information data; use China Platforms such as the Weather Data Network provide access to weather data.

[0031] S102: Determine a variety of first characteristic factors from the original data, specifically, extract characteristic paramet...

Embodiment 2

[0063] An embodiment of the present invention provides a vehicle risk prediction model training method, Image 6 is a flowchart of a vehicle risk prediction model training method according to an embodiment of the present invention, such as Image 6 As shown, the method includes:

[0064] S601: Obtain a variety of first feature factors and / or second feature factors stored in association with feature points or lines between feature points obtained according to the above-mentioned vehicle feature data processing method; specifically, because the first feature factor and The feature points and the lines between the feature points are stored in relation to each other, and the first feature factors stored at different levels can be extracted. For example, the highway grade is stored in the low-level network structure, while vehicle body data features such as vehicle speed are stored in the high-level In the network structure, these first eigenfactors are obtained for model training...

Embodiment 3

[0071] The embodiment of the present invention provides a specific vehicle risk prediction system. The big data sources in the embodiment of the present invention are mainly through the Internet of Vehicles platform, map providers and third-party data sources (platforms such as meteorological data networks). Collect vehicle body data, behavior data, and some environmental feature data, GPS trajectory data, engine-related parameters of the vehicle body, four emergency parameters, atmospheric pressure, temperature, elevation, etc. from each vehicle through the Internet of Vehicles; obtain high-precision maps, Data such as standard maps and traffic conditions can be used to obtain information such as traffic light intersections, road grades, speed limit areas, and road conditions in the driving environment; weather and other data can be obtained through third-party data sources such as weather data networks to obtain weather characteristics of the driving environment. By adding di...

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PUM

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Abstract

The invention provides a vehicle characteristic data processing method and a vehicle risk prediction model training method. The vehicle feature data processing method comprises the steps of obtainingat least one kind of original data, determining a plurality of required first feature factors from the original data, then selecting feature points from the track points, performing hierarchical storage on the feature points, determining connection lines between the feature points corresponding to different levels, and performing associated storage on the plurality of first feature factors and thefeature points or the connection lines between the feature points; The vehicle risk prediction model training method comprises the steps of training a vehicle risk prediction model by using a plurality of pieces of sample data, wherein each piece of sample data comprises a sample mark used for representing whether the vehicle has an accident or not; and at least one first feature factor and/or atleast one second feature factor stored on the associated feature points or the connecting lines between the feature points corresponding to a certain track level, so that the problem of low accuracyof an existing vehicle risk prediction model is solved.

Description

technical field [0001] The invention relates to the field of automobile insurance, in particular to a vehicle characteristic data processing method and a vehicle risk prediction model training method. Background technique [0002] With the advent of the Internet era and the development of technology globalization, the mobile Internet is constantly penetrating into various fields of society and economy. Similarly, the Internet of Vehicles under the Internet is also penetrating into the automobile insurance industry. Therefore, the automobile insurance industry based on the Internet of Vehicles has Huge development prospects. Among them, Internet of Vehicles technology and big data technology are the core driving forces for the future development of the insurance industry. In such an era background, the research on the Internet of Vehicles insurance was carried out, and the UBI system research in the era of big data was proposed. [0003] In the prior art, vehicle body data i...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q40/08
Inventor 董丽王心宇许伟张文平赵谦益方绍伟么昌龙章正林
Owner NAVINFO
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