Supercharge Your Innovation With Domain-Expert AI Agents!

Identification method of traffic high-risk persons based on random forest algorithm

A random forest algorithm and person recognition technology, applied in character and pattern recognition, computing, computer parts, etc., to achieve the effect of strong interpretability, high and high-risk recognition accuracy, and improved model accuracy

Active Publication Date: 2021-09-17
JIANGSU ZHITONG TRANSPORTATION TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This model is widely used, but it has not been applied to the field of safety feature mining of traffic participants

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
  • Identification method of traffic high-risk persons based on random forest algorithm
  • Identification method of traffic high-risk persons based on random forest algorithm
  • Identification method of traffic high-risk persons based on random forest algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0047] The identification method of traffic high-risk personnel based on random forest algorithm extracts the characteristic attributes of personnel safety behavior from traffic violation records and fits the safety risk classification model to realize the identification of high-risk personnel and safety risk prediction based on illegal data; figure 1 , the specific method flow is:

[0048] S1. Based on the original traffic violation data and accident data, construct violation data sets, serious accident data sets, and minor accident data sets.

[0049] In the embodiment, the original traffic violation data and accident data in step S1 include relevant personnel certificate information; the violation data set is obtained after collecting and classifying the violation records; the violation data set is the full sample data of the violation records of the personnel, and the violation data The collected information includes personnel certificate number, number of violations, type...

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 present invention provides a method for identifying high-risk traffic personnel based on the random forest algorithm. Based on the original traffic violation data and accident data, an illegal data set, a serious accident data set, and a minor accident data set are constructed, and a random forest is used for high-risk personnel identification model training. It is of practical significance to improve the efficiency of traffic safety management and assist the traffic police in daily safety management to be more targeted and proactive.

Description

technical field [0001] The invention relates to a method for identifying traffic high-risk personnel based on a random forest algorithm. Background technique [0002] Creating a safe and orderly road traffic operating environment is an important link in the healthy and sustainable development of the city, and is of great significance to the protection of public life, health and property safety. However, with the increase in the level of travel motorization, the traffic safety situation is still severe. The "2016 Statistical Bulletin on National Economic and Social Development" released by the National Bureau of Statistics released 2.1 deaths per 10,000 vehicles in road traffic accidents. Data survey shows that the main cause of traffic accidents is caused by motor vehicle violations. Drivers' driving skills are uneven, and illegal driving is common, among which severe overloading, fatigue driving, and speeding are the most prominent. In this regard, traffic control is curre...

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 Patents(China)
IPC IPC(8): G06K9/62G06Q10/04G06Q10/06G06Q50/26
CPCG06Q10/04G06Q10/0635G06Q50/265G06F18/24323G06F18/214
Inventor 吕伟韬刘林陈凝张韦华
Owner JIANGSU ZHITONG TRANSPORTATION TECH
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com