Accident type and regulation violation type corresponding analysis method in traffic accident

A technology of traffic accidents and analysis methods, applied in data processing applications, character and pattern recognition, instruments, etc.

Active Publication Date: 2017-05-31
SOUTHEAST UNIV
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AI Technical Summary

Problems solved by technology

[0003] Due to the randomness of the causes of traffic accidents, the influence of the driver alone on traffic accidents is as many as dozens of items. The existing methods lack the study of different types of traffic accidents caused by drivers' fluke psychological factors from the perspective of drivers' traffic violations.

Method used

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  • Accident type and regulation violation type corresponding analysis method in traffic accident
  • Accident type and regulation violation type corresponding analysis method in traffic accident
  • Accident type and regulation violation type corresponding analysis method in traffic accident

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Embodiment

[0056] Such as figure 1 As shown, a method for corresponding analysis of accident types and violation types in traffic accidents, comprising the following steps:

[0057] S1. Define parameters and construct a traffic accident type-historical violation type matrix X; specifically include the following steps:

[0058] S11, define the data structure of traffic accident type: suppose all types of traffic accident collection A=(a 1 ,a 2 ,...a i ,...a m ),a i is a traffic accident whose accident type is i, and the number of drivers with various types of driving behavior faults in the traffic accident is set K=(k 1 ,k 2 ,…k i ,…k m ), k i is the number of people corresponding to the traffic accident whose accident type is i, i=1,...m, m is the total number of traffic accident types;

[0059] S12, define the data structure of the driver's historical violation type data structure: the driver's historical violation type set B=(b 1 ,b 2 ,...b j ,...b n ),b j is the traffic...

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Abstract

Traffic violation is an important factor which causes traffic accidents, and a traffic safety behavior risk is researched from the perspectives of traffic accident types and historical violation types. Normalization and a threshold value method are utilized to select a proper traffic violation type. Through Pearsons chi-square, relevance between traffic violation and traffic accidents is verified. A corresponding analysis method is adopted to research primary and secondary relevant violation types corresponding to different traffic accident types, and an influence degree model is established. Meanwhile, on the basis of an interaction influence of the primary and secondary relevant violation types, parts of traffic accident types and violation types are classified and combined. A result indicates that the traffic accident type and the violation type have correlation and a corresponding relationship, the precaution of the traffic accidents can be realized on the basis of the characteristics, and an accident type is anticipated.

Description

technical field [0001] The invention relates to a method and system for multi-dimensional correspondence analysis and research of drivers' traffic accident types and violation types. Background technique [0002] Statistics show that 90% of traffic accidents are caused by human factors. In addition to a small amount of unconscious unsafe driving behaviors, such as misjudgment, distraction, etc., 82% of human-made traffic accidents are caused by the driver's active driving behavior. This mentality is more reflected in its daily traffic violations. At present, many countries have adopted the policy of deducting points on the driver's license to regulate people's driving behavior. As important data for recording unsafe traffic behaviors of drivers, the relationship between traffic violations and driving negligence in accidents provides a new perspective for traffic accident analysis, prevention and control. ZHANG Guangnan, Kelvin K W YAU, etc. analyzed the quantitative relat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06Q50/30
CPCG06Q50/30G06F18/2321
Inventor 夏井新陆振波安成川
Owner SOUTHEAST UNIV
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