Identification method of high-risk traffic personnel based on xgboost algorithm

A person identification and high-risk technology, which is applied in the field of traffic high-risk person identification, can solve problems such as shortage, achieve the effects of preventing over-fitting, alleviating model accuracy, and ensuring the accuracy of recognition

Active Publication Date: 2021-09-07
JIANGSU ZHITONG TRANSPORTATION TECH
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AI Technical Summary

Problems solved by technology

It has a good performance advantage when applied to data classification, and it is applied to the processing of traffic violation data, which can mine valuable traffic safety information, but there is still a lack of such applications

Method used

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  • Identification method of high-risk traffic personnel based on xgboost algorithm
  • Identification method of high-risk traffic personnel based on xgboost algorithm
  • Identification method of high-risk traffic personnel based on xgboost algorithm

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Embodiment

[0047] A method for identifying high-risk traffic persons based on the XgBoost algorithm, which extracts the characteristic attributes of traffic participants' safety behaviors from traffic violation records and trains the model to realize the identification of high-risk persons and safety risk prediction; 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 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 violati...

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Abstract

The invention provides a method for identifying high-risk persons in traffic based on the XgBoost algorithm. Based on the original traffic violation data and accident data, the XgBoost algorithm is used to train and correct the identification model of high-risk persons, and the illegal attribute information of persons is input into the model to realize the identification of high-risk persons. The identification and prediction of traffic safety has practical significance for improving the efficiency of traffic safety management and assisting 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 an XgBoost algorithm. Background technique [0002] Most of the research in the field of road traffic safety focuses on the analysis of the relationship between external factors such as the environment, road infrastructure, and traffic flow operation status and traffic accidents, such as Chinese patents CN201710400521.X, CN201580075213.3, CN201611051192.4, etc. Distribution characteristics, or analyze the regular characteristics of traffic accidents from the perspective of environment, traffic control measures and other characteristics. Internal factors such as the behavior habits of traffic participants (motor vehicles, non-motor vehicle drivers, pedestrians), etc., due to their wide information dimensions and limited information perception methods, there is still a lack of in-depth research and analysis. The impact of accidents is an inevitable content of traffic ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/2458G06K9/62G06N20/20G06Q50/26
CPCG06Q50/265G06Q50/30
Inventor 吕伟韬刘林陈凝饶欢
Owner JIANGSU ZHITONG TRANSPORTATION TECH
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