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

Driver behavior recognition method based on multi-source information fusion

A technology of multi-source information fusion and recognition method, applied in the direction of neural learning method, character and pattern recognition, instrument, etc., can solve the problems of low reliability and weak anti-interference, and achieve strong anti-interference and high recognition Accuracy, enhanced applicability effect

Inactive Publication Date: 2022-04-08
HANGZHOU DIANZI UNIV
View PDF10 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention proposes a driver behavior recognition method based on multi-source information fusion for the problems of low reliability and low anti-interference of the existing driver behavior recognition methods, aiming to provide a basis for the research of man-machine co-driving technology. Solutions to improve driving safety

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
  • Driver behavior recognition method based on multi-source information fusion
  • Driver behavior recognition method based on multi-source information fusion
  • Driver behavior recognition method based on multi-source information fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] specific implementation plan

[0042] The following is attached Figure 1-5 The technical solution of the present invention is described in detail.

[0043] Such as figure 1 As shown, this embodiment provides a driver behavior recognition method based on multi-source information fusion, including the following steps

[0044] Step 1. Obtain the images or videos about the driver's behavior recorded from the driving simulator, as well as the vehicle motion state data.

[0045] Further, step 1 is realized in the following ways:

[0046] Step 1.1. Arrange the camera and display screen. Considering the small space directly in front of the driver in the real car is not conducive to focusing, the camera is planned to be placed in front of the driver's right. There must be no less than three display screens, which should be placed facing the testers at a certain angle. The specific positions should be adjusted based on the driving experience of the testers. The front view of...

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 provides a driver behavior recognition method based on multi-source information fusion. The driver behavior recognition method is characterized by comprising the steps that 1, images or videos related to driver behaviors recorded in a driving simulator and vehicle motion state data are obtained; step 2, inputting the processed driver behavior data into a fine-tuned Vision Transform first sub-model, and outputting a probability matrix P1 of four driving behavior categories; 3, preprocessing the synchronously recorded vehicle motion state data, inputting the data into the trained Bi-LSTM second sub-model, and outputting a probability matrix P2 of four driving behavior categories; and step 4, calculating the probability output matrixes P1 and P2 obtained in the step 2 and the step 3 to obtain information entropies H1 and H2 of the first sub-model and the second sub-model, and finally performing weighted decision fusion on Softmax function output probability values of different sub-models to realize final classification of the four driving behaviors. According to the invention, a plurality of driving behavior identification tasks are integrated, and the anti-interference performance is high.

Description

technical field [0001] The invention relates to the field of man-machine co-driving, in particular to a driver behavior recognition method based on multi-source information fusion. Background technique [0002] Cars are currently the most commonly used means of travel. With the increase in the number of cars, traffic accidents occur more frequently. Among them, irregular driving behavior has serious potential safety hazards and is also the main reason for more than 80% of traffic accidents. Therefore, monitoring the driver's driving behavior has extremely important application value. If the driver's unsafe driving behavior can be identified and the driver's potential danger in the driving process can be warned in time, the initiative of vehicle safety will be further enhanced. [0003] In addition, although the intelligent technology of automobiles is developing rapidly, it is difficult to realize automatic driving under all working conditions in the short term. Therefore,...

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): G06V20/59G06V10/764G06V10/80G06V10/82G06K9/62G06N3/04G06N3/08
Inventor 陈慧勤刘昊陈海龙
Owner HANGZHOU DIANZI UNIV
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