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Accident risk prediction method for traffic participants based on ensemble learning

A technology that integrates learning and prediction methods, applied in the traffic control system of road vehicles, traffic control systems, instruments, etc., can solve problems such as difficult to implement traffic safety governance, mining the correlation between difficult personnel attributes and traffic safety, and achieve improvement Model performance, effect on guaranteed accuracy

Active Publication Date: 2021-05-28
JIANGSU ZHITONG TRANSPORTATION TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Traffic participants are the key to road traffic safety, but traditional research and management applications are limited by information collection and perception methods, and it is difficult to mine the correlation between personnel attributes and traffic safety, making it difficult to implement targeted measures. Traffic Safety Governance

Method used

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  • Accident risk prediction method for traffic participants based on ensemble learning
  • Accident risk prediction method for traffic participants based on ensemble learning
  • Accident risk prediction method for traffic participants based on ensemble learning

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Experimental program
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Embodiment

[0041] A traffic participant accident risk prediction method based on ensemble learning, such as figure 1 , the specific method flow is:

[0042] S1. Based on the original traffic violation data and accident data, construct illegal data sets, serious accident data sets, and minor accident data sets;

[0043] 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 preprocessing operations such as collection and classification of the original violation records; the violation data set is the full sample data of personnel violation records , the data set information includes the personnel certificate number, the number of violations, the type of violations, the deduction of points and fines, the occurrence of accident-related violations, and the period of violations.

[0044] The occurrence of accident-related illegal activities in S1 is obtained through corres...

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Abstract

The present invention provides an accident risk prediction method for traffic participants based on integrated learning, which uses an optimized sampling method to obtain traffic violation data and accident data samples, uses an integrated learning algorithm to train personnel traffic accident risk prediction models, and realizes automatic identification of high-risk personnel. Obtaining traffic participant accident risk prediction indicators can be applied to the management of traffic safety active prevention and control, improve the pertinence of traffic safety governance, and improve the efficiency of daily traffic safety management.

Description

technical field [0001] The invention relates to a traffic participant accident risk prediction method based on integrated learning. Background technique [0002] Traffic participants are the key to road traffic safety, but traditional research and management applications are limited by information collection and perception methods, making it difficult to mine the correlation between personnel attributes and traffic safety, making it difficult to implement targeted traffic safety management. At present, my country's traffic safety and regulatory work is mainly based on the investigation and punishment of violations, and a large number of traffic violation data resources of vehicles and personnel have been accumulated. Traffic violations are significantly correlated with traffic safety, so data mining of traffic violation data can extract the necessary information about the safety characteristics of traffic participants. [0003] Among the data mining methods, Ensemble Learn...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG08G1/0125G06F18/24
Inventor 刘林陈凝吕伟韬李璐
Owner JIANGSU ZHITONG TRANSPORTATION TECH