Highway outburst accident influence factor identification method based on negative binomial regression

A technology of influencing factors and identification methods, applied in data processing applications, complex mathematical operations, instruments, etc., can solve problems such as road identification difficulties, achieve simple and rapid identification, and improve safety conditions

Pending Publication Date: 2022-05-13
GUANGXI COMM PLANNING SURVEYING & DESIGNING INST
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  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The invention solves the problems of difficulty in identifying the inf

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  • Highway outburst accident influence factor identification method based on negative binomial regression
  • Highway outburst accident influence factor identification method based on negative binomial regression
  • Highway outburst accident influence factor identification method based on negative binomial regression

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Embodiment Construction

[0009] In order to make the object, technical solution and advantages of the present invention clearer, preferred embodiments are given to further describe the present invention in detail. However, it should be noted that many of the details listed in the specification are only for readers to have a thorough understanding of one or more aspects of the present invention, and these aspects of the present invention can be implemented even without these specific details. The present invention will be described in further detail below in conjunction with the accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0010] combine figure 1 As shown, the present invention provides a method for identifying factors affecting prominent highway accidents based on negative binomial regression, and the method for identifying the impact of accidents includes the following steps:

[0011] Step S1: road segment division, using the sliding window method to...

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Abstract

The invention discloses a road outburst accident influence factor identification method based on negative binomial regression. The method comprises the steps that a sliding window method is adopted to carry out road section analysis unit division on a road in a to-be-analyzed operation period; performing data extraction by taking the divided road section analysis units as units, and extracting a linear index variable and a traffic volume of each road section analysis unit; selecting a linear index variable and a traffic volume of the road section analysis unit as initial accident influence factors; assuming that all line shape condition index items corresponding to the road section analysis units to be analyzed are ideal line shape conditions, namely assigning null value items according to line shape index values under the ideal line shape conditions; and on the basis of the determined initial accident influence factor, analyzing the initial accident influence factor based on negative binomial distribution regression, and identifying the prominent accident influence factor of the road section to be analyzed from the initial accident influence factor. According to the invention, simple and rapid identification of accident-prone points of the high-grade highway is realized, and important guarantee is provided for safe operation management of the high-grade highway.

Description

technical field [0001] The invention relates to the field of identifying influencing factors of traffic engineering and accidents, in particular to a method for identifying influencing factors of outstanding highway accidents based on negative binomial regression. Background technique [0002] According to statistics, traffic accidents rank first in the number of non-disease deaths in the world. Therefore, the analysis, identification and management of prominent factors affecting road accidents during the operation period is a safety governance work that many developed countries need to carry out regularly. Although there are no clear regulations and requirements in this regard in our country, the identification of the influencing factors of outstanding highway accidents has always been one of the important tasks of the traffic management department in our country. Highway traffic accidents are often random, discrete, and independent events. According to the current mainstre...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06F17/18G06Q50/30
CPCG06Q10/06393G06F17/18G06Q50/30
Inventor 覃薇覃延春欧剑聪林婧梁才张燕侯泽群陈少峰其他发明人请求不公开姓名
Owner GUANGXI COMM PLANNING SURVEYING & DESIGNING INST
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