Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A user driving behavior analysis method and system

A behavior analysis and user technology, applied in the field of Internet of Vehicles, can solve the problem of insufficient and accurate analysis and prediction of user driving behavior, and achieve the effect of improving the accuracy of prediction and evaluation

Pending Publication Date: 2019-06-04
上海赢科信息技术有限公司
View PDF7 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a user driving behavior analysis method and system in order to overcome the limitations of the above three levels in the prior art that lead to insufficient and accurate analysis and prediction of the user's driving behavior

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A user driving behavior analysis method and system
  • A user driving behavior analysis method and system
  • A user driving behavior analysis method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0063] A user driving behavior analysis method, such as figure 1 shown, including:

[0064] Step 101. Collect vehicle driving data of several users, and calculate several index items for describing the driving behavior of the users according to the vehicle driving data.

[0065] Step 102, acquiring traffic accident information of the user.

[0066] Step 103, using the index item as a feature variable, analyzing the correlation between each feature variable and the traffic accident information, and selecting N feature variables with the highest correlation with the traffic accident information to form an N-dimensional vector.

[0067] Step 104: Using a nonlinear dimensionality reduction algorithm to reduce the dimensionality of the N-dimensional vector to obtain a variable set.

[0068] Step 105, using the variable set as an independent variable and the traffic accident information as a dependent variable, train a user's driving behavior evaluation model.

[0069] Step 106:...

Embodiment 2

[0109] A user driving behavior analysis system, such as image 3 As shown, it includes: a data processing module 31 , a feature selection module 32 , a model training module 33 and a model usage module 34 . The data processing module 31 includes: a user travel data sub-module 311 and a traffic accident data sub-module 312 .

[0110] The user travel data sub-module 311 is used to collect vehicle driving data of several users, and calculate several index items for describing the driving behavior of the users according to the vehicle driving data.

[0111] The traffic accident data sub-module 312 is used to obtain the user's traffic accident information.

[0112] The feature selection module 32 is used to use the index item as a feature variable, analyze the correlation between each of the feature variables and the traffic accident information, and filter out the N feature variables with the highest correlation with the traffic accident information , forming an N-dimensional ve...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a user driving behavior analysis method and system. The method comprises the steps of acquiring vehicle driving data of a plurality of users, and calculating a plurality of index items used for describing the driving behaviors of the users according to the vehicle driving data; Obtaining traffic accident information of a user; Taking the index items as characteristic variables, analyzing the correlation between each characteristic variable and the traffic accident information, and screening out N characteristic variables with the highest correlation with the traffic accident information to form an N-dimensional vector; Dimensionality reduction is carried out by using a nonlinear dimensionality reduction algorithm to obtain a variable set; Training a user driving behavior evaluation model by taking the variable set as an independent variable and the traffic accident information as a dependent variable; And evaluating the driving behavior of the to-be-analyzed user by using the user driving behavior evaluation model. The traffic accident information is used as a quantitative index for evaluating the driving behavior of the user, the user driving behavior evaluation model is trained, and the prediction and evaluation accuracy of the driving behavior of the user is improved.

Description

technical field [0001] The invention belongs to the field of Internet of Vehicles, and in particular relates to a user driving behavior analysis method and system. Background technique [0002] In the field of Internet of Vehicles, the analysis of user driving behavior has been the basis of many researches and applications in recent years. Due to the complexity of data sources, the huge amount of data and the variety of application methods, traditional statistical analysis methods are difficult to meet the requirements of accurate prediction and rapid iteration. Therefore, many machine learning and artificial intelligence technologies are introduced into it. While making great progress, the existing technology still has certain limitations, roughly in the following aspects: [0003] 1. Data source level: The data source used in the current technology is mainly the data transmitted in real time by after-installed communication equipment such as mobile phones, or the data co...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/30
Inventor 张伟吕兴杨治赵安宁
Owner 上海赢科信息技术有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com