A user driving behavior analysis method and system
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
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
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
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
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
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
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
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.
Login to view more 
Login to view more